Project Code:
TD/2006/0330/a/b/c/d
Project Title:
Environmental and Energy
Management of Buildings using
Project
Start/Finish
Dates
01-July-2007/30-Septemer2010
Report Date
30-September-2010
Principal Investigator Report
for
Commercialisation Fund Projects
Please tick as appropriate
Interim Report
Final Report
9
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PI Report for
Commercialisation Fund Projects
PAYMENT WILL BE MADE ONLY WHEN THE PRINCIPAL INVESTIGATOR REPORT IS
RECEIVED AND ACCEPTED BY ENTERPRISE IRELAND. REPORTS SHOULD BE SUBMITTED
BY E-MAIL.
REPORT:
PERIOD COVERED
BY THIS REPORT:
01-JULY-2007/30-SEPTEMER-2010
PRINCIPAL INVESTIGATOR
TITLE AND NAME:
Dr. Marcus Keane (Lead PI)
ORGANISATION:
National University of Ireland, Galway (NUIG)
ADDRESS:
Department of Civil Engineering.
TEL. NO.
00-353-91-492619
E-MAIL:
marcus.keane@nuigalway.ie
COLLABORATIVE RESEARCHER (WHERE APPLICABLE)
TITLE AND NAME:
Prof. Karsten Menzel
ORGANISATION:
University College Cork
ADDRESS:
Department of Civil & Environmental Engineeirng
TEL. NO.:
00-353-21-4902523
E-MAIL:
k.menzel@ucc.ie
COLLABORATIVE RESEARCHER (WHERE APPLICABLE)
TITLE AND NAME:
Dr. Dirk Pesch
ORGANISATION:
Cork Institute of Technology (CIT)
ADDRESS:
Rossa Avenue, Bishopstown, Cork.
TEL. NO.:
021 4326377
E-MAIL:
dirk.pesch@cit.ie
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COLLABORATIVE RESEARCHER (WHERE APPLICABLE)
TITLE AND NAME:
Dr. Cian Ó Mathúna
ORGANISATION:
Tyndall National Institute
ADDRESS:
Lee Maltings, Prospect Row, Cork.
TEL. NO.:
00-353-21-4904088
E-MAIL:
cian.omathuna@Tyndall.ie
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SUMMARY OF RESEARCH WORK TO-DATE (200 WORDS MAX.)
BUILDINGS CONSUME 40% OF IRELAND’S TOTAL ANNUAL ENERGY TRANSLATING TO €3.5 BILLION (2004). THE
EPBD DIRECTIVE (EFFECTIVE JANUARY 2003) PLACES AN ONUS ON ALL MEMBER STATES TO RATE THE ENERGY
2
PERFORMANCE OF ALL BUILDINGS IN EXCESS OF 50M . ENERGY AND ENVIRONMENTAL PERFORMANCE MANAGEMENT
SYSTEMS FOR RESIDENTIAL BUILDINGS DO NOT EXIST AND CONSIST OF AN AD-HOC INTEGRATION OF WIRED
BUILDING MANAGEMENT SYSTEMS AND MONITORING & TARGETING SYSTEMS FOR NON-RESIDENTIAL BUILDINGS.
THESE SYSTEMS ARE UNSOPHISTICATED AND DO NOT EASILY LEND THEMSELVES TO COST EFFECTIVE RETROFIT OR
INTEGRATION WITH OTHER ENTERPRISE MANAGEMENT SYSTEMS. THE OBJECTIVE OF THIS PROJECT IS TO SPECIFY,
DESIGN, AND VALIDATE A DATA MANAGEMENT TECHNOLOGY PLATFORM THAT WILL SUPPORT INTEGRATED ENERGY &
ENVIRONMENTAL MANAGEMENT IN BUILDINGS UTILISING A COMBINATION OF WIRELESS SENSOR NETWORK
TECHNOLOGIES, AN INTEGRATED DATA MODEL AND DATA MINING METHODS AND TECHNOLOGIES.
STAFFING / BUDGET SUMMARY (200 WORDS MAX.)
Mandatory: List the names of all team members funded by this project during this reporting period.
National University of Ireland Galway (Dr. Marcus Keane)
Senior/Postdoctoral Researcher (James O’ Donnell, B.E (Civil, Hons))
•
James O’ Donnell started as a Senior Researcher on the commencement of the research project on
July 1st 2007 and completed his contract with BuildWise on June 30th 2009. James defended hi PhD
thesis in March 2009 and graduated with a PhD from University College Cork (UCC) in June of 2009.
James will be taking up a 2 year senior research post at Lawrence Berkeley National Alboratories
(LBNL) at UC Berkeley in October 2009.
PhD student (Andrea Costa, Master of Science (summa cum Laude), POLITECNICO DI MILANO, ITALY)
•
Andrea Costa is engineering graduate of the Politecnico Di Milano having graduated with 1st class
honours in Building Engineering with a joint B.E./MSc qualification. He is the designated as the NUIG
PhD student for the entire project and will now take over the technical project management role for
IRUSE-Galway. Andrea has acted as official observer for IRUSE-Galway on the EU BuildingEQ project
and has contributed substantially in the development of links with EU partners and the creation of an
EU consortium committed to developing a 4 year STREP proposal under FP7-2010-NMP-ENVENERGY-ICT-Eeb..
Internship (Edward Corry)
•
Edward Corry is a mature Third Year Civil Engineering student at NUI Galway having previously
worked as an analyst/prgrammer in the banking sector for a number of years. Edward, as part of his
Professional Employment Programme (PEP) at NUI Galway joined IRUSE-Galway and has contributed
signifcantly to the formal development of the BuildWise Building Information Model (PFT tool).
University College Cork (Prof. Karsten Menzel)
Post Doctoral Researcher (Dr. Martin Keller):
•
•
was already employed at UCC started to work on Buildwise in September 2007.
Dr. Keller’s expertise in Business Process Modelling was essential for the development of Deliverable
D1;
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•
Dr. Keller was offered a position with a leading European software developer and resigned in January
2008.
Ph.D. student (Umut Goekce, MBA):
•
•
was hired in August 2007. He holds a Bachelor in “Business Information Systems” from the
University of Istanbul (Turkey) and a MBA in Facility Management from Dresden International
University (Germany).
His expertise in Database Management Systems and his knowledge in FM are of great benefit for the
work in Buildwise.
Student Help (Zixiang Cong, MEngSc.):
•
•
Mr. Cong was hired to partially compensate the unexpected loss of Dr. Martin Keller
Holds a BSc. In Computer Science form Limerickk Institute of Technology and attended the
MEngSc.-programme “Information Technology in Architecture, Engineering and Construction” at UCC
from Sept. 2006 to Oct. 2007 and was conferred in Dec. 2007
MEngSc. Students (to be nominated):
•
•
Enterprise Ireland agreed to re-allocate the remaining funding of the Post Doctoral position in order
to strengthen the
Industry – University – Interaction through work placements.
UCC will recruite two MEngSc students for the Academic years 2008/2009 and 2009/2010. Students’
work will be emphasised on
interface development (Task 3.5, 4.2 and 4.3)
Tyndall National Institute (Dr. Cian O’ Mathuna)
Senior Researcher (Mr. Brendan O’ Flynn)
•
Brendan O’Flynn Has a M.Eng Sc and has worked in the Tyndall Institute since 2004, he is heading
up the wireless sensor Network Research Activities in the Microsystems Center. Brendans area of
expertise in the are of RF system integration and platform development and project management
Postdoctoral Researcher (Dr. Essa Jafer)
•
•
•
Dr Jafer was employed in 2008 as a poctdoctorate researcher developing the wireless sensor
networking technologies for the buildwise project;
He finished his PhD and Master of Engineering by research in 2004 and 2008 respectively from
Electronic and Computer Engineering Department (ECE), University of Limerick, Limerick-Ireland;
His experties is focused in the Design and Modelling of low power telemetry systems and sensor
interfacing technology.
Postgraduate Student (Wensi Wang)
•
•
Wensi is a PHD student working on the integration and development of Energy Harvesting platforms
for use in the Built environment;
The platforms that Wensi is developing are to be deployed in the ERI.
Internship (Brian McCarthy)
•
Brian is developing a wireless implemenation of a Energy Metering system which will be incorporated
into the Buildwise deployment as part of a short term internship prior to starting a PHD in October
2008.
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Cork Institute of Technology (Dr. Dirk Pesch)
Posdoctoral. Student (Alan McGibney)
•
Alan McGibney started to work on the project from July 1st, 2007. Alan holds a BSc degree in
Computer Applications from CIT and obtained his PhD in 2009 from CIT during the course of the
BuildWise project;
•
His expertise in the area of optimisation and modelling of wireless networks and his work on a WLAN
design tool were suitable as this has allowed the CIT team to leverage the wireless design tool
technology already available for modification towards wireless sensor network design;
Ph.D. Student (Rodolfo De Paz)
•
Rodolfo De Paz started to work on the project from November 1st, 2007. He holds a
telecommunications engineering degree from the University Miguel Hernandez of Elche in Spain;
•
Rodolfo’s expertise in communication systems modelling and design has been used to provide
effective transfer of communication protocol software development from the EI WISEN Emnets
project (ILRP/2006/301a). He is actively aupporting the testbed development of the BuildWise
project in the ERI building in UCC.
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PROJECT REVIEW
For each Work Package that follows, please describe the current status of the
project, including the following elements and any other relevant information in
the box provided:
•
Is work schedule in accordance with the stated milestones and deliverables
(discuss)
•
Outlook for the remaining period, if applicable
•
Where relevant, comment on how delivery or otherwise of milestones
will impact on ability to commercialise the technology
A detailed descripion of the final results of the project (both technical
and in terms of commercialisation) is attached at the end of this
section.
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WP 1
Requirements Specification
Start Date
Description
01/07/2007
Finish Date
30/09/2007
The Work Package aims on developing a requirements specification for the BuildWise
system.
Milestone(s)
including due
date and date
achieved
Technical Milestone 1(TM1): Specification of BuildWise Requirements
Date due: 30-Sept-2007
Date achieved: 30-Sept-2007
Date submitted to EI: 30-Sept-2007
This included sub-milestones achieved during the implementation of TM1:
TM1.1: Specification of the business process model that underpins holistic
environmental and energy management in buildings;
TM1.2: Specification of fundamental building environmental & energy management
scenarios that comprise the business process model defined in TM1.1;
TM1.3: Specification of a layered hierarchy of environmental & energy performance
objectives and metrics that underpin the scenarios defined in TM1.2;
TM1.4: Specification of the sensors/meters required to deliver the data streams that
support the environmental & energy performance objectives and metrics
hierarchy defined in TM1.3;
TM1.5: Specification of overall BuildWise technology platform architecture that
underpins TM1.1-1.4;
Commercial Milestone 1 (CM1): Liaison with Building Industry Advisory Group
(BIAG) members to verify Requirements
Specification from commercial needs perspective
Date due: 08-Nov-2007
Date achieved: 08-Nov-2007
Date submitted to EI: Mr. Andy Rhodes and Liam Sweeney attended on behalf of EI and
contributed to the 1 day meeting held at the Environmental Research Institute (ERI) at
UCC along with members of the BIAG
Deliverable(s)
including due
date and date
submitted
Describe the
progress of the
work package
to date and
future plans
Deliverable 1 (D1): Specification Report (Responsible Partner, IRUSE-Galway). This
can be accessed at http://zuse.ucc.ie/buildwise/index.html
Completed
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WP 2
Start Date
Description
Wireless Sensor Platform Development
01-Oct-2007
Finish Date
31-Dec-2008
•
•
•
•
•
Phase 0 and Phase 1 field test of integrated system based on commercial wireless
sensor motes;
Develop system design architecture for BuildWise Motes and Wireless Sensor
Network based on Tyndall platform and CIT communications/network platform;
Develop the input for a proposal to extend a well recognized international standard
for product and process modelling (IFC 2.x3 ISO 16 739) towards building
performance monitoring and control;
Develop an initial data warehouse model including all relevant extraction,
transformation, loading (ETL), aggregation and mining processes on a limited scope
(HVAC-systems);
Develop “Mock-Up” of user interfaces for desktop-based management and PDAbased inspection processes.
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Milestone(s)
including due
date and date
achieved
Technical Milestone 2(TM2): Prototype 1 of sensor & network platform using off-theshelf commercial motes
Date due: 30-Sept-2008
Date achieved: 30-Sept-2008
Date submitted to EI: 30-Sept-2008.
TM2 can be divided into a number of sub-millstones that have been achieved and those
that are outstanding within the scheduled timeframe of TM2. These are:
TM2.1 RF Characterisation of the ERI building and the Generic sensor Layer
Date due: 31-July-2008
Date achieved: 31-July-2008
Date Submitted to EI: n/a
TM2.2 Electricity Meters Interfacing
Date due: 30-Sept-2008
Date achieved: 30-Sept-2008
Date Submitted to EI: n/a
TM2.3 PIR sensors Zigbee Boards
Date due: 30-Sept-2008
Date achieved: 30-Sept-2008
Date Submitted to EI: n/a
Technical Milestone 3(TM3): Phase 1 results of field test evaluation of prototype in
the Environmental Research Institute (ERI) at
University College Cork (UCC).
Date due: 31-Dec-2008
Date achieved: 31-Dec-2008
Date submitted to EI: 31-Dec-2008
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Deliverable(s)
including due
date and date
submitted
Deliverable 2-1 (D2-1): Sensor & Network Platform Prototype (CIT, Tyndall)
Deliverable 2-2 (D2-2): Performance Data Model, Interface Specification (IRUSEGalway)
Deliverable 2-3 (D2-3): Data Warehouse and GUI Specification (IRUSE-Cork)
Deliverable 2-4 (D2-4): Report on Phase 1 installation and field test evaluation in ERI
(CIT, Tyndall)
Deliverable 2-5 (D2-5): System design architecture for BuildWise motes and WSN
(CIT, Tyndall)
Describe the
progress of the
work package
to date and
future plans
Completed
WP 3
Energy Management System Development
Start Date
Description
Milestone(s)
including due
date and date
achieved
Deliverable(s)
including due
date and date
submitted
01/01/2009
Finish Date
30/09/2009
The Work Package aims on completing the hardware system, developing the complete software system and
integrating both of them.
D 3-1, Completed Hardware-Software-Platform
(first version)
D 3-2, System Documentation
D 3-3, Proposal for ISO-Standard Extension
D 3-4, Installed “Demonstrator”
Date due: 30-Sept-2009
Date achieved: 30-Sept-2009
Date Submitted to EI: 30-Sept-2009
Describe the
progress of the
work package
to date and
future plans
Completed
WP 4
System Deployment and Testing
Start Date
01/08/2009
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Finish Date
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Description
Milestone(s)
including due
date and date
achieved
Deliverable(s)
including due
date and date
submitted
The Work Package aims on the installation and deployment of the demonstrator in a
“real world” environment (ERI-building on UCC campus). Ambient-intelligent interfaces
for mobile devices are finally implemented. BIAG members will have the opportunity to
evaluate the total system.
D 4-1, Evaluation Report and Future Development Plan
Date due: 30-Sept-2010
Date achieved: 30-Sept-2010
Date Submitted to EI: 30-Sept-2010
Describe the
progress of the
work package
to date and
future plans
Completed
WP 5
Management
Start Date
Description
01/07/2007
Milestone(s)
including due
date and date
achieved
Deliverable(s)
including due
date and date
submitted
Finish Date
30/09/2010
The Work Package aims disseminating the research results. A business plan will be
developed with BIAG members and up-dated at Workshops and Milestones.
D 5-1, Web-Site (including electronic evaluation tool)
D 5-2, Flyers, Posters (Roadshows),
D 5-3, Multimedia Presentation (trade fairs)
D 5-4, Business Plan
Date due: 30-Sept-2010
Date achieved: 30-Sept-2010
Date Submitted to EI: 30-Sept-2010
Describe the
progress of the
work package
to date and
future plans
Completed
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Summarise the current proposed IPR assets being developed in this project.
Comment on current or proposed publication plan (e.g abstracts, conferences,
IDFs, patent applications etc.) .
See attached report.
Summarise the current status of commercialisation and on the potential
opportunities and issues for this technology
See attached report.
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2009
delayed
WP2Prototype1:“Thermal System”
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T5.3:WorkshopsWebPublications
T5.2:Commercialisation&BusinessPlan.
T5.1:Project Management
WP5Management
T4.3:FieldTest completesystem: evaluation
T4.2:PrototypeInstationin:integration
T4.1:Final Systemintegration
WP4DeploymentandFieldTest
T3.5:Desktop&MobileInterface: implementation
T3.4:DataWarehouse:extensionof scope&load
T3.3:BuildingInformationModel: standardization
T3.2:Evaluationof BuildWiseWSN
T3.1:Integrationof BuildWiseWSN
WP3Implementationof Full System
T2.7:FieldTest Prototype1in: evaluation
T2.6:SystemsIntegrationInstallation
T2.5:Mock-UpUser Interfaces:development
T2.4:DataWarehouseCoreModel: development
T2.3BuildingInformationModel: development
T2.2:WirelessNetworkDesign/Tool Development
T2.1:SystemArchitecture, WirelessSensor Design
inprogress
finished
T1.2Analysis &HardwareSpecification
T1.3SystemSpecification
tobedone
T1.1ProcessAnalysis
WP1RequirementsSpecification
2008
2010
7 8 9101112 1 2 3 4 5 6 7 8 9101112 1 2 3 4 5 6 7 8 9101112 1 2 3 4 5 6 7 8 9
2007
Gantt Chart:
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BUILDING A SUSTAINABLE FUTURE
Wireless Sensor Networks for Energy and Environment Management in Buildings
Final Report
Date:
13.09.2010
Editors:
Marcus Keane and Andrea Costa
Contributions:
Informatics Research Unit for Sustainable Engineering
Marcus Keane
(IRUSE Galway)
Andrea Costa
James O’Donnell
Information Technology in Architecture, Engineering, and Construction
Karsten Menzel
(IT in AEC)
Ufuk Gocke
Tyndall National Institute of Technology
Essa Jafer
(Tyndall)
Brendan O’Flynn
Cian O’Mathuna
Cork Institute of Technology
Dirk Pesch
(CIT)
Alan McGibney
BuildWise – Final report
Table of Contents
1.
Executive summary ................................................................................................................. 5
2.
BuildWise project ..................................................................................................................... 5
2.1.
3.
Technology platform – Technical achievements..................................................................... 9
3.1.
4.
BuildWise objectives ........................................................................................................ 8
BuildWise technology platform architecture .................................................................... 9
3.1.1.
BIM based performance definition and Performance Framework Tool (PFT) ....... 10
3.1.2.
Performance Monitoring Platform (incl. Data Warehouse) .................................... 12
3.1.3.
Tyndall motes .......................................................................................................... 14
3.1.4.
Wireless Sensor Network and WSN design tool .................................................... 16
The ERI a living laboratory .................................................................................................... 22
4.1.
ERI - Performance Framework Tool .............................................................................. 22
4.1.1.
Geometric BIM - ArchiCAD ..................................................................................... 30
4.1.2.
HVAC BIM - DDS-CAD ........................................................................................... 32
4.1.3.
Performance Framework BIM - PFT ...................................................................... 32
4.2.
ERI - Data Warehouse ................................................................................................... 34
4.3.
ERI - Tyndall motes - BuildWise Sensor Board (BEM1) ............................................... 36
4.3.1.
System Architecture and Functional Units ............................................................. 36
4.3.2.
Occupation Sensor (Passive infrared PIR) ............................................................ 39
4.3.3.
Humidity/Temperature Sensor................................................................................ 40
4.3.4.
Acceleration and Motion Sensors ........................................................................... 41
4.3.5.
RS485 for Water Flow Meter Interfacing ................................................................ 42
4.3.6.
Water Pipe temperature Sensor Interfacing ........................................................... 43
4.3.7.
Magnetic Hall Effect Sensor for Detecting Windows/Doors status ........................ 44
4.3.8.
Actuation Capability ................................................................................................ 44
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BuildWise – Final report
4.4.
5.
ERI – Wireless Sensors Network ................................................................................... 45
4.4.1.
ERI Prototype Wireless Sensor Network................................................................ 45
4.4.2.
ERI Final Deployment ............................................................................................. 50
BuildWise related commercialisation activities ..................................................................... 54
5.1.
BuildWise project Commercialisation Activities– Executive Summary ......................... 54
5.2.
Exploitation Possibilities 2010-2012 .............................................................................. 56
5.2.1.
5.3.
Industry Interaction and BuildWise Industrial Engagement 2009-2010 ........................ 59
5.3.1.
5.4.
Summary of Commercialisation Activities for the Consortium ............................... 58
‘Engine for innovation’ clustering process flow chart ............................................. 61
Identification of commercial opportunities ..................................................................... 64
5.4.2.
Summary Analysis of Competitors and supply chain ............................................. 67
5.4.3.
Performance Specification Tool (PST) ................................................................... 68
5.4.4.
Data Warehouse ..................................................................................................... 70
5.4.5.
Networking Protocols/ Deployment Tools .............................................................. 75
5.4.6.
Wireless Sensing Platforms .................................................................................... 81
5.4.7.
Summary of Commercialisation Activities for the Consortium ............................... 87
5.5.
The Business Plan– How BuildWise is Adding Value to Ireland Inc ............................. 87
5.5.1.
Wirelite Sensors ...................................................................................................... 89
5.5.2.
HSG......................................................................................................................... 92
5.5.3.
UTRC ...................................................................................................................... 92
5.5.4.
Self-Build Partners (SBP) & Fewer Harrington Partners (FHP) – G House – Irish
SME Partnership ................................................................................................................... 92
5.5.5.
Irish Industry Engagement ...................................................................................... 94
5.5.6.
FP7 positioning of WSNs in future EU calls, industry engagement etc. ................ 95
5.5.7.
SME Clustering - FP7 SME Workshop................................................................... 98
5.5.8.
Potential Industrial Opportunities for further exploitation ..................................... 100
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BuildWise – Final report
6.
Bibliography ......................................................................................................................... 102
Appendix A .................................................................................................................................. 102
Appendix B .................................................................................................................................. 117
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BuildWise – Final report
1. Executive summary
The objective of this project is to specify, design, and validate a data management technology
platform that supports integrated energy & environmental management in buildings utilising a
combination of wireless sensor network technologies, an integrated data model and data mining
methods and technologies. This report present the developed technology platform, the results
associated to a real deployment in the Environmental Research Institute building at University
College Cork and finally the commercialisation activities and results that originated from this
Enterprise Ireland project.
2. BuildWise project
Lowering the world energy consumption is one of the major challenges of present day and
future generations. The combined energy amount used for buildings (residential and services) in
kilo tonnes of oil equivalent (ktoe) comprises over 40% of Ireland’s total energy consumption.
This amounts to a monetary value of €3.5 billion for the year 2004. It should be also noted that
this 40% energy consumption by buildings also translates into over of 30% of Ireland’s total CO2
emissions which may have a direct monetary value in the context of an emerging carbon tax
scheme under consideration by government at present. Figure 1 depicts the proportion of
energy consumed by buildings in Ireland.
Figure 1 Energy Flow in Ireland
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BuildWise – Final report
The emerging EU directives relating to energy (EU EPBD and the EU Directive on Emissions
Trading) now places demands on building owners to rate the energy performance of their
buildings. This will create a demand for integrated and reliable building environmental and
energy data. The EPBD came into law in January 2003. The EU EPBD places an onus on
building owners to rate the energy performance of their buildings (new and existing buildings in
excess of 50m²). Each member state is committed to implementing this directive into national
law by January 2006. This has been implemented in Ireland through the Building Control Act
early in 2006 and development and implementation of the rating schemes for residential and
non-residential applications is commenced from September 2006 under the stewardship of SEI.
Currently, energy performance rating of buildings is at best sporadic often consisting of an adhoc combination of off-the-shelf building management systems (BMS), distributed data metering
equipment ‘glued’ together by monitoring and targeting (M&T) software tools. This ad-hoc
combination presents many difficulties to building owners in the management and upgrade of
these systems as the building management systems can consist of a number of components
utilising various information exchange protocols that have to be integrated within the M&T
software packages. This often results in distributed data across different building management
systems and/or data logging equipment resulting in inconsistent and/or corrupted data and data
loss from malfunctioning BMS components (sensors, controllers, faculty wiring). Because these
are ‘wired’ systems the cost in retrofitting these systems in order to implement more energy
efficient management practices is cost prohibitive. It is estimated that the current cost of running
cables for sensors in buildings accounts for 50-90% of the overall cost of installing a sensor.
Also, there is little if any direct coupling of these systems in the monitoring/management of both
the energy consumption data and environmental performance of the conditioned spaces within
buildings.
Current building environmental & energy management systems are focused on building control
and automation. As long as building management systems (BMS) succeed in maintaining set
environmental conditions (e.g. temperature, relative humidity), the client has shown little interest
in accessing/analyzing the environmental and energy data being utilized by the BMS and
associated data logging meter equipment. In fact, it is widely known that most BMS only store
for a predefined time period and then discard it. Monitoring & Targeting software tools attempt to
address this situation when a client/facility manager requires this data. The M&T tools
‘communicate’ with a variety of data streams from stand alone and/or multiple building
management systems and data loggers usually in the form of ASSCII and/or CSV text files. This
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BuildWise – Final report
has resulted in ad-hoc fragmented systems development of building environmental & energy
management systems.
Most designs of M&T systems are reactive to existing installed BMS infrastructure. Also, clients
are not encouraged to retrofit such systems to effect better energy management because of the
prohibitive costs of these ‘wired’ systems. The limitations of current environmental & energy
management systems lie in their ‘wired’ infrastructure (cost restrictions) and in the unreliability
and inaccessibility of the environmental and energy related data across a fragmented BMS
infrastructure. Overall, existing building management systems have a number of key
shortcomings that prevent them from cost effectively addressing future market opportunities:
•
In non-residential buildings, energy performance rating is at best sporadic often
consisting of an ad-hoc combination of off-the-shelf building management systems
(BMS) and monitoring and targeting (M&T) software tools. This ad-hoc combination
presents many difficulties to building owners in the management and upgrade of these
systems as the building management systems can consist of a number of components
utilising various information exchange protocols that have to be integrated within the
M&T software pack-ages.
•
Because these are ‘wired’ systems the cost in retrofitting these systems in order to
implement more energy efficient management practices is cost prohibitive. It is
estimated that the current cost of running cables for sensors in buildings accounts for
50-90% of the overall cost of installing a sensor.
•
There is little if any direct coupling of these systems in the monitoring/management of
both the energy consumption data and environmental performance of the conditioned
spaces within buildings.
A promising approach to overcome some of these shortcomings is the implementation of
wireless sensor module platforms. Wireless sensor module platforms have, over the last 5
years, begun to proliferate within the worldwide research and industrial communities. In the
research community, motes have been principally used by computer scientists investigating and
developing the concepts and architectures to enable future ad-hoc wireless sensor networks.
Building management system companies are beginning to evaluate the technology but as yet, in
most cases it is at the development/evaluation phase with companies like Siemens and
Honeywell still only offering development kits of two to three motes. Most of these wireless
motes are based around the original Crossbow Inc. mote and are not, as yet, optimised in terms
of functionality or form factor for use in a dedicated application specific building management
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environment. Furthermore, these motes typically have a single sensor function which cannot be
easily customised. Actuating functionality is all together missing so far.
The robustness and reliability of the wireless sensor network is crucial for a reliable and
functional wireless building management system. However, the usual “put on wall and switch on
and it works” approach that is so often associated with wireless sensor networks will not deliver
a reliable wireless BMS. The installation process is currently the most time consuming and
challenging aspect of wireless BMS installation. The proper operation of a wireless network, that
comprises of sensor nodes and wireless gateways into a wired backbone, requires proper
design.
The BuildWise system will uniquely address the above issues by providing a turnkey solution
that can be seamlessly integrated into existing and future intelligent building management
systems. By utilising wireless sensor networking technology, an integrated, industry-standard,
data model and data warehouse technologies, a low cost, retrofittable solution will be able to
deliver a fully integrated energy & environmental management capability.
2.1.
BuildWise objectives
Principally targeted at the operational life cycle of large public and private buildings such as
offices, schools, hospitals and apartment complexes, it is envisaged that the BuildWise platform
will provide a dramatic improvement over existing disparate hardware/software technologies
currently utilised in the management of energy in buildings, leading to increased energy
efficiencies in buildings in the range of 15-20% (Piette et al. 2001). Customers for the system
include building management system developers and suppliers, installation and commissioning
companies and facility management companies/organisations.
In addressing these objectives, the project will develop a wireless sensor network based
Building Management System using a backend management and control system based on
standards compliant to suitable Building Information Models. This consists of a technology
platform and graphical user interface front-end which provides facility management personnel
with access to the building operation data and trend analysis as well as allowing the end user to
configure the sensor network to monitor and deliver the required data at the required
granularity/frequency. This technology platform, illustrated in Figure 2, is based on the
combination of four key elements:
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•
A data warehouse platform that stores, manages, and analyses all building performance
data retrieved from the network using appropriate building industry standard protocols
and formats, such as the Industry Foundation Classes.
•
A building information model for the acquisition and storage of sensor data in order to
perform short term data monitoring as well as long-term trend analysis relating to the
optimum operation of the building over it’s life cycle.
•
A wireless sensor network to enable efficient and effective communication between the
sensors modules and the central data processing unit.
•
A 3-dimensional or smart card format wireless sensor module for data acquisition
relating to building energy usage and environmental comfort data.
Figure 2 BuildWise technology platform
3. Technology platform – Technical achievements
3.1.
BuildWise technology platform architecture
The objective of this project was to develop an integrated wireless energy & environmental
management technology platform (BuildWise) to support life cycle facilities management of
buildings. This comprises simple context sensitive user interface to the data warehouse for
facility management activities. It also supports the development of customised monitoring and
targeting activities that explicitly link environmental, energy, and economic life cycle analysis. In
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addition two novel computer aided design tools. The first tool, named Performance Framework
Tool (PFT) was developed for documentation and specification of building performance
requirements; this is presented in section 3.1.1. The second tool, named the Performance
Monitoring Platform, provides access to classified and categorised Building Performance Data
through context-sensitive web-based user interfaces (section 3.1.2). The third tool, named WSN
design tool, allows the design of power efficient and reliable indoor wireless sensor networks for
use in Building Management Systems was. This tool (section 3.1.4) also simplifies the
installation of such networks determining the optimum positions of sensor nodes.
3.1.1.
BIM based performance definition and Performance Framework Tool (PFT)
A Building Information Model (BIM) consists of two major components: a three dimensional
graphical reproduction of the building geometry and a related database in which all data,
properties, relations are stored (Simpson 2008).
The value of BIM created during design and construction phase is well documented and can
result in an estimated 30 percent reduction in total construction costs (J. R. Watson et al. 2009).
Throughout the typical Building Life Cycle there are series of discontinuities in the transmission
of building data that occur. Transitions from design to construction to operation result in loss of
data, added cost to reconstitute the data, and overall reduction in data integrity. The impact,
growing at each handover, culminates with the handover to the facility operator and therefore to
the energy manager. In financial terms it was reported that in the US the annual cost (in 2002)
associated with inadequate interoperability among computer-aided design, engineering, and
software systems was $15.8B. Owners and operators shoulder almost two thirds of that cost,
which is incurred during ongoing facility operation and maintenance (O&M) (Gallagher et al.
2004).
With the implementation of the asset building energy rating certification process, driven by the
EPBD (European Union 2002), this cost is likely to increase in the EU market due to the
difficulty of gathering stock data for existing and new buildings for which an energy certificate is
now mandatory. The loss of information relative to the HVAC and BMS/BAS systems also
affects the effectiveness of the energy manager in understanding the operation of the system
and, more important, in using available measurements to monitor systems efficiencies and
energy end uses. This results in reducing the already low monitoring capabilities of BMS/BAS
systems that are currently mainly designed only for control and automation rather than
monitoring (Raftery et al. 2010).
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The methodology proposed in this research project uses BIM technology to define and store
performance related information that are associated to specific building geometry objects (e.g.
building, floor, zone, wall…) or to specific HVAC system objects (e.g. pipe, air duct, pump,
AHU…) and their relative metrics. The required underpinning sensors/meters are also
instantiated and defined in the BIM. All these information are stored through the use of a tool
named “Performance Framework Tool (PFT)” that has been implemented within the project in
accordance with the requirements defined by O’Donnell in his PhD thesis (O'Donnell 2009). The
performances are structured in performance objects, objectives, metrics, aspects and scenarios
(Figure 3). A performance objective can be thought of as a qualitative objective that may be
assigned to a particular performance object (building object). The easiest example of
performance objective is “monitor” a parameter, but more complex performance objectives
include qualifiers such as “maintain”; in this case a benchmark value has to be defined
accordingly. For example, a building manager may wish to maintain the temperature within a
particular zone, within a building. This objective can be quantified by associating it with a
performance metric, while the zone itself may be considered a performance object.
A building may have hundreds of performance objectives, so it makes sense to categorise them
under particular performance aspects. In this way, similar performance objectives can be
viewed together, in order to provide a clearer picture for the building manager. The five defined
performance aspects are: building function, thermal loads, energy consumption, system
performance and legislation. A scenario is a collection of associated performance objectives,
concerned with a particular aspect of the building operation.
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Figure 3 Example of a BIM based performance definition structure
Concerning the current technical implementation, the PFT tool takes an Industry Foundation
Class (IFC) file as its input, defines and appends scenario definitions, and exports the file in IFC
format again. The output of this process is a formal description of the building and system
measurement framework available and the associated measured data required to monitor the
prescribed performance. The measured data can be stored in a standard manually implemented
data base or in an automatically implemented data warehouse that is IFC compatible.
3.1.2.
Performance Monitoring Platform (incl. Data Warehouse)
The objective was to develop a web-based platform to support the integration, classification,
categorisation, and finally presentation of Building Performance Data. The core of this
application is the Data Warehouse application capable of compiling performance data from
multiple heterogeneous sources, using descriptive data from the BIM (see section 3.1.1) and
from other Business Process Modelling Systems (BPM) to classify and categorise the
Performance Data according to multiple criteria, such as time, location, organisational unit.
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Finally, classified and categorised data is aggregated according to the requirements of three
stakeholder profiles, Tenant/User, Facility Manager, and Building Owner.
As part of the BuildWise project our work emphasised on the following features:
(1) Development and implementation of a comprehensive methodology and related tools to
extract, transform, and load data from different Building Management Systems.
(2) Development and implementation of a Meta-Data structure which supports the integrated,
holistic management of Building Performance Data (Fact Data) and descriptive data from BIM
and BPM (Dimensional Data).
(3) Development and Implementation of methods and tools for the aggregation and analysis of
the compiled Building Performance Data, and
(4) the Mock-up, Evaluation, Design, and Implementation of Graphical User Interfaces for both
desktop and mobile devices.
Graphical User Interface
[Mobile Application Tool]
Graphical User Interface
[PC Desktop Application Tool]
Fact-Data
ETL TOOLS
Performance Framework
[Specification Tool]
{BIM}
Operational Data Store
Wired Sensor Data
[CSV File Format]
{BMS}
Wireless Sensor Data
[MySQL]
{WSN}
Extraction
Transformation
Loading
Building Information
[CAD Design Tool]
{BIM}
Figure 4 Major Components of the Data Warehouse Platform and Data Processing Activities
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The data model for the Data Warehouse Platform is compliant to the IFC.2x3 standard. All IFCattributes relevant for Energy Management are implemented in the model. Furthermore, the
identified “dimensions” are compliant with the “Performance Aspects” defined in the PF-Tool.
Therefore, a comparison of Performance Specification Data (PF-Tool) and measured data
(Performance Monitoring Platform) can be easily performed by end-users.
Data access and manipulation is organised and implemented with standardised models and
languages, such as SQL 3.
A second emphasis was given to the development of the web-based user interfaces. We
followed a xx-stage approach; (i) Mock-up development, (ii) Evaluation and discussion with
industry representatives, (iii) Detailed interface design, (iv) Implementation. In terms of datacentric interfaces to the data warehouse an SOA-approach was chosen to provide a flexible,
easy adaptable and extendible application programming interface for further commercialisation.
3.1.3.
Tyndall motes
The objective was to develop multi-sensor wireless modules in 3-D and planar formats to be
robust and reliable within a ‘real’ building environment. The final development consists of a 25
mm sensor module. The aim of this sensor module is to provide a novel 3-D programmable
modular system that could be used as a toolkit for ambient systems research (such as robotics,
autonomous agents and neural networks, telemetry, transducer networks, etc). The target
objectives for the 25 mm cube module are to develop:
•
A low volume prototyping and experimentation platform.
•
A platform for sensing and actuating through physical and chemical parameters.
•
A scalable, re-configurable distributed autonomous sensing platform.
•
Intelligent, re-configurable algorithms for scalable ambient Intelligence (AmI) Systems.
The first and second objectives incorporate the creation of a platform that is robust, available as
a low volume prototype, and has the ability to interface to a broad range of physical and
chemical transducers. This will provide a foundation for the third aim, provision of functional low
volume prototypes for implementation and evaluation in case study application areas. The fourth
objective is a reconfigurable development tool for distributed autonomous transducer networks
that are then to be investigated as a building block technology for ambient intelligence.
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Figure 5: Tyndall Wireless Platform
The Figure 6 shows the modules identified as being critical in the design. The schematic shows
that both digital and analogue type sensors are being considered. The signals that they produce
are conditioned for interfacing to the processing and communications modules. The conditioning
circuitry may contain amplification or analogue filtering to reduce noise for example.
For processing there is a field programmable gate array (FPGA) module. This allows intensive
digital signal processing (DSP) tasks such as moving average filters, Fast Fourier Transforms
(FFTs) to be implemented on the sensor node and this can even support intelligent applications,
such as spiking neural nets for miniature robotic control.
The communications layer has a microcontroller and RF transceiver. The micro-controller can
support less intensive processing tasks, stand-alone or can act as a co-processor to the FPGA
section. The microcontroller also handles analogue to digital conversion of sensor data and the
communication networking protocols for interfacing with the RF transceiver.
The Tyndall mote is based on the ATMEGA128L and ATMEGA1281 microcontrollers and
Chipcon CC2420 Zigbee transceiver.
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Figure 6: 25mm Cubic Tyndall Wireless Platform
3.1.4.
Wireless Sensor Network and WSN design tool
Within the BuildWise project a Wireless Sensor Network (WSN) is required to provide the
environmental and energy related data from the building to the Building Information Model
(BIM). The WSN is based on i) an existing wireless network protocol to support rapid
prototyping of the BuildWise WSN and ii) a simple power efficient, self-configuring protocol
stack aimed at addressing potential limitations of the standards protocol when deployed in real
life building scenarios.
The WSN architecture used is based on the outputs defined within the EmNets project. Figure 7
presents the proposed scalable network architecture whilst observing the main application
space within BuildWise – environmental & building monitoring and control. In such network
configuration, clusters of wireless sensor mesh network are connected via a wireless backbone
IEEE802.11 network and the fixed TCP/IP network to the IFC BIM. Each sensor network cluster
covers a self-contained part of the environment such as a floor of the building. This
heterogeneous architecture will provide a scalable approach in which clusters of WSN can be
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added when required. With this topology in mind, we have proposed the EmNets architecture as
shown in
Figure 7 - EmNets Proposed WSN Architecture
The network is built with a combination of existing platforms such as Tmote and Tyndall 25mm
both running TinyOS 2 with an existing wireless network routing protocols. Tmotes comes with
integrated humidity, temperature, and light sensors. Tyndall 25mm can be expanded by the
various sensor boards. The WSN gateways are connected by USB2.0 cable possibly via
USB2.0 Hubs to TCP/IP gateway nodes, also known as “Supernodes”. The Supernodes are
based on standard industrial Embedded PC such as Soekris (www.soekris.com). The
Supernodes have Wi-Fi connectivity and thus can form the Wi-Fi mesh network if required. The
Soekris embedded PC have been chosen as a suitable platform for the Supernode devices as
they are cost effective and have a small footprint.
The positioning of wireless sensor nodes is critical to maximise the performance of WSN. In
order to aid in this difficult task a software design tool is required. This can be achieved by
developing a software package that incorporates site-specific constraints, accurate propagation
modelling and optimisation models that enables an automated design of the wireless sensing
infrastructure to support building monitoring. Figure 8 presents the components of the design
tool that have been developed.
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Pre-Processing
Building
Geometry
Optimisation
IFC
Sensor Placement
AUTOMATIC
Constraints
OPTIMISATION
Sensor/Application
Requirements
Sensor/Sink
Candidate Positions
Automatically
generated
Propagation
QOS
Modelling
Parameters
Manually Defined
using Design Tool
Figure 8 - WSN Design tool Components
Using the planning tool a system specification can be created including a description of the
environment where the WSN will be deployed, definition of sensor types and relevant
parameters. The planning tool will then automatically optimise and suggest positions for
placement of wireless sensor nodes to achieve a WSN that is ideal for both data accusation and
communication. The design tool can also be used to visualise propagation from sensor nodes.
Once deployed the WSN design can be validated by carrying out measurements, the results of
which can be used to re-optimise WSN during prototyping.
3.1.4.1.
Building Information Model and Wireless Sensor Network design tool
Building Information Models (BIM) are the most appropriate medium for storing building data
across the entire life cycle of a project. To support deployment a sensor network design tool
requires that certain pre-processes are performed before it can elicit the relevant information
from an interoperable BIM environment. Building geometry must be instantiated in the BIM. A
performance hierarchy that defines the sensor requirements in a building must also be
instantiated and are in turn passed to the sensor network design tool. The environment
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description is used as an input for a propagation model that estimates the electromagnetic
propagation throughout the environment, therefore walls with various materials that influence
signal prediction need to be defined, to make it easier for the designer typical wall types are
defined and should be included as part of the BIM, these include heavy, light, glass or metal.
This propagation prediction can then be used to estimation of the quality of communication
links.
To integrate the design tool with the BIM it is possible to extract 3D building geometry from an
Industry Foundation Classes (IFC) file. IFC is an open specification of a BIM and is used to
share and exchange BIMs in a neutral format among various software applications. The
availability of the IFC data model makes it an ideal method to gather the environment data for
the WSN design tool for building energy management. The IFC model is composed of entities,
which are associated with properties and relationships. Entity attributes are mostly defined by
other entities. Due to the highly hierarchical structure, a raw IFC file is extremely complex to
handle. The architecture of the developed IFC parser to manage this complexity is shown in
Figure 10.
Ruby Interface
IFC2SVG
(Ruby)
IFCsvr ActiveX Component
SVG file
IFC file
Figure 9 - IFC Geometry Extraction for WSN Design Tool
The
environment
data
is
extracted
using
the
IFCsvr
ActiveX
component
(http://tech.groups.yahoo.com/group/ifcsvr-users/). IFCsvr is a freely available component which
handles interaction with the IFC data file. The combination of this ActiveX component with an
interface written in Ruby reduces the difficulty of dealing with the IFC data file directly. As the
current implementation only requires 2D information, the design tool converts the 3D data into a
2D model of the building using a stacked approach for a multi-floor building. The floor geometry
is defined by walls, windows and doors. Although the IFC data model is the primary source of
input for the environment description, the design tool also supports drawing capabilities and the
import of AutoCad drawings. Figure 10 shows an example of the imported ERI lower ground
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floor from an IFC file to the required format for WSN design. This capability significantly reduces
the time required to capture environment data and hastens the design process.
Figure 10 - Version 1.0 IFC to SVG for WSN Design Tool
Another important element that influences the design of a sensor network is the definition of
“demand zones”. A demand zone represents the areas within the building that are of interest to
the BMS, and corresponds to sensor placement constraints and application requirements To
define optimisation requirements for the WSN design tool an approach shown by Figure 11 is
used. A sensor region should be defined within a zone (area of interest for sensing).
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Sensor Region
Demand Zone
Figure 11 - Sensor Placement Constraints/Requirements
This sensor region defines potential locations of sensors and should be created in terms of
accurate sensing (e.g. the sensor zone reflects that in a room a temp sensor should only be
placed on wall X etc). Therefore a sensor region defines positional constraints for required
sensors, additionally there needs to be defined sensor specific constraints/requirements such as
sensing interval, measurement precision and value threshold. By collating all site specific
information at this stage of the design makes it possible for application developers, network
designers and building managers to get a complete overview of the monitoring infrastructure
that will be deployed within the building.
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4. The ERI a living laboratory
As part of the project, the technology platform described in section 3, was deployed for the final
system of the BuildWise “living laboratory” in the Environmental Research Institute (ERI)
building on UCC campus. The BuildWise WSN-components, BIM, Data Warehouse, the
analysis and management interfaces were integrated for the fully operational system “upscaled” to multiple building services. The next sections present the ERI demonstration case
study in relation to the 4 key aspects: Building Information Model, Data Warehouse, Tyndall
motes and Wireless Sensors Network.
4.1.
ERI - Performance Framework Tool
Capturing the Performance Framework within the building information model involves the
following steps: create a geometric BIM, enhance geometric BIM with HVAC functionality and
then enhance the BIM with Performance Framework and sensor definitions with a top down
approach whereby the choice of the performance objective and metrics drives the choice of the
measurement streams (from sensors/meters) required to underpin them. As shown in Figure 12
and in the flowing paragraphs, in our case we have used ArchiCAD (Graphisoft 2010) for
geometry and construction, DDS-CAD (Data Design System 2010) for HVAC component and
finally the PFT for performance scenarios including sensors and meters.
Figure 12 - BIM based performance definition overview
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Within BuildWise three performance scenarios have been developed and can be listed as
follow:
•
•
•
Scenario 1 – Heating in 4 different reference zones.
Scenario 2 – Lighting strategy in 4 different reference zones.
Scenario 3 – Operation of AHU number 5.
For scenario 1 and scenario 2, four reference zones have been identified to reduce the number
of new sensors required for the developed of the Wireless Sensor Network (WSN) based
measurement framework. These four zones intend to be representative of the whole building as
they include the main zone types: one laboratory room (Z_G.05: Immunology lab), one office
room (Z_1.23: Open Plan Office), one meeting room (Z_1.28: Seminar Room) and also a
circulation space (Z_1.28: Seminar Room - break out space). Different types of exposition are
also considered as both the main exposition are represented by the selected zones: north
facade (Z_G.05: Immunology lab) and south facade (Z_1.23: Open Plan Office and Z_1.28:
Seminar Room). Figure 13, Figure 14 and Figure 15 show the dislocation across the three floors
in the ERI building of the additional sensors required to underpin the performance scenarios
number 1 and 2.
LG06: Main
Plant Room
LG09: Switch
Room
Figure 13 - Lower ground floor sensor/meters placement overview
Z_G05:Immunology Lab
UFH Manifold 0.02
Figure 14 - Ground floor sensor/meters placement overview
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UFH Manifold
1.03
Z_1.28: Break
Out Space
UFH Manifold
1.01
Z_1.23: Open Plan
Office Space
Z_1.28: Seminar
Room
Figure 15 - First floor sensor/meters placement overview
The overall approach of the scenario definition has been holistic; the idea is to capture cause
and effect in terms of building usage and energy consumption. For this reason the sensors and
meters required focused on energy flow measurements and occupancy levels at the zonal and
sub-zonal level in order to identify the interdependencies of different parameters such as: zone
occupancy, windows and doors opening, lighting levels and lighting switches operation,
environmental comfort and energy consumption. These two scenarios were developed as part
of the BuildWise 1 ‘large scale’ deployment. This deployment required an 88 node deployment
with a range of sensors to meet the full requirements of the ERI data set building model
development. The installation of wireless sensors and the collection of the data sets was part of
BuildWise and is currently being continued as part of the ITOBO project for building operation
optimisation purposes. A more detailed schematic of the sensors position within the identified
zones is also described in section 4.4.2 and Appendix A, this appendix documents also the full
data set required to underpin these 3 scenarios and in particular the 88 new wireless sensors
deployed within this project. As example we document in this section Scenario 2 and 3 whereas.
For these two scenarios the documentation consists of MS Visio diagrams and MS Excel
spreadsheets only as the PFT tool implementation was too difficult because of HVAC – IFC
problems. However scenario 3 (AHU number 5) is a demonstration of a full utilisation of the
Performance Framework Tool (PFT) and an IFC building information model. This scenario is
based on a data set provided by data points of the currently installed Building Management
System (BMS). These are all data points based on wired sensors distributed across the
building.
Table 1, Figure 16 and Figure 17 outline the definition of scenario 2 and related performance
objectives and metrics that is carried out with MS Visio diagrams and an MS Excel spreadsheet.
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As mentioned already, this scenario intends to evaluate the performance of the artificial lighting
strategy in the chosen reference zones within the building. To achieve this goal, electricity
meters are required on the lighting circuits to determine and record the artificial lighting usage
profile and energy consumption. Outdoor lighting levels and lighting levels on the work planes
are also required, in order to measure them a novel type of wireless sensors (named Tyndall
motes) has been deployed by Tyndall National Institute as part of this project. These motes
have also the capability to measure and log CO2 concentration and Passive Infrared (PIR)
signal for monitoring the occupancy profile over time.
Table 1 - Scenario 2 – Lighting strategy in 4 different reference zones - Complete list of
performance objectives and metrics
1
1
1
1
1
1
1
1
1
1
Energy Consumption
Legislation
System Perfomance
Thermal Loads
Building Function
Perform ance Aspect
Qualitative
Perform ance
Objective
Perform ance Object
Quantitative
Perform ance
Metric
PM Unit
Site
Monitor
Z_G05: Immunology Lab
Monitor
Z_G05: Immunology Lab
Monitor
Z_G05: Immunology Lab
Monitor
1 Z_G05: Immunology Lab
Monitor
Z_1.23: Open Plan Office SpacMonitor
Lighting levels
Lighting levels
Zone Occupancy
Zone Occupancy
Lighting
Lighting levels
Outdoor Lighting level
Lux Level at Working plane
CO2 Level
PIR
Lighting Electricity
Lux Level at Working plane
Lux
Lux
PPM
kWh
Lux
Z_1.23: Open Plan Office SpacMonitor
Z_1.23: Open Plan Office SpacMonitor
1 Z_1.23: Open Plan Office SpacMonitor
Z_1.28:Seminar Room
Monitor
Zone Occupancy
Zone Occupancy
Lighting
Lighting levels
CO2 Level
PIR
Lighting Electricity
Lux Level at Working plane
PPM
kWh
Lux
1
Z_1.28:Seminar Room
Monitor Zone Occupancy
CO2 Level
PPM
1
Z_1.28:Seminar Room
Monitor Zone Occupancy
PIR
-
Monitor Lighting
Monitor Lighting levels
Monitor Zone Occupancy
Monitor Zone Occupancy
Monitor Lighting
Lighting Electricity
Lux Level at Working plane
CO2 Level
PIR
Lighting Electricity
kWh
Lux
PPM
kWh
1
1
1
1
1
1 Z_1.28:Seminar
Z_1.28:Seminar
Z_1.28:Seminar
Z_1.28:Seminar
1 Z_1.28:Seminar
Room
Room_b
Room_b
Room_b
Room_b
Measurem ent Stream
Datum1
Datum85
Datum82
Datum81
Datum83
F(Datum101 and
Datum102)
F(Datum97 and Datum98)
F(Datum95 and Datum96)
Datum99
F(Datum129 and
Datum130)
F(Datum124 and
Datum126)
F(Datum123 and
Datum125)
Datum127
Datum143
Datum140
Datum139
Datum141
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Scenario 2 – Lighting Strategy in 4 reference zones
Performance
Aspect
Performance
Object
Qualitative
Performance
Objective
Building
Function
Site
Monitor Lighting
levels
Outdoor
Lighting level
Lux
Sensor
Z_G05:
Immunology Lab
Monitor Lighting
levels
Lux Level at
Working plane
Lux
Sensor
Monitor Zone
Occupancy
CO2 Level
CO2
Sensor
Motion
PIR
Sensor
Z_1.23: Open
Plan Office Space
Z_1.28:Seminar
Room
Z_1.28:Seminar
Room_b
Quantitative
Performance
Metric
Sensor/Meter
Formula
Monitor Lighting
levels
Lux Level at
Working plane
Lux
Sensor
Monitor Zone
Occupancy
CO2 Level
CO2
Sensor
Motion
PIR
Sensor
Monitor Lighting
levels
Lux Level at
Working plane
Lux
Sensor
Monitor Zone
Occupancy
CO2 Level
CO2
Sensor
Motion
PIR
Sensor
Monitor Lighting
levels
Lux Level at
Working plane
Lux
Sensor
Monitor Zone
Occupancy
CO2 Level
CO2
Sensor
Motion
PIR
Sensor
Figure 16 - Diagram of scenario 2 – Lighting strategy in 4 different reference zones - Performance
objectives and metrics relating to the building function aspect
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Scenario 2 – Lighting Strategy in 4 reference zones
Performance
Aspect
Performance
Object
Qualitative
Performance
Objective
Quantitative
Performance
Metric
Energy
Consumption
Z_G05:
Immunology Lab
Monitor Lighting
Lighting
Electricity
Electricity
Meter
Z_1.23: Open
Plan Office Space
Monitor Lighting
Lighting
Electricity
Electricity
Meter
Z_1.28:Seminar
Room
Monitor Lighting
Lighting
Electricity
Electricity
Meter
Z_1.28:Seminar
Room_b
Monitor Lighting
Lighting
Electricity
Electricity
Meter
Sensor/Meter
Formula
Figure 17 - Diagram of scenario 2 – Lighting strategy in 4 different reference zones - Performance
objectives and metrics relating to the energy consumption aspect
A complete example of the PFT documentation process relating to one AHU (the number 5) in
the ERI building is shown in the next sections and in Figure 18, Figure 19, Figure 20 and Figure
21. With this scenario we intend to monitor the performance of AHU 5 considering the
environmental conditions of the served rooms, the outdoor air temperature and also the AHU
components (thermal wheel, supply fan and exhaust fan) performances.
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Scenario 3 – AHU 5 operation
Performance
Aspect
Building
Function
Performance
Object
Qualitative
Performance
Objective
Quantitative
Performance
Metric
Sensor/Meter
Formula
Z_Tissue Culture
Ref 2.12
Monitor
Temperature
Air Temperature
Air
Temperature
Sensor
Z_Dry Specimen
Storage Area
Monitor
Temperature
Air Temperature
Air
Temperature
Sensor
Z_First AID
Monitor
Temperature
Air Temperature
Air
Temperature
Sensor
Z_Cleaner Store
Monitor
Temperature
Air Temperature
Air
Temperature
Sensor
Figure 18 - Diagram of scenario 3 - AHU 5 operation - Performance objectives and metrics relating
to the building function aspect
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Scenario 3 – AHU 5 operation
Performance
Aspect
System
Performance
Performance
Object
Qualitative
Performance
Objective
Quantitative
Performance
Metric
Sensor/Meter
Formula
Site
Monitor
Temperature
Outdoor Air
Temperature
Air
Temperature
Sensor
AHU_5
Monitor
Temperature
Supply Air
Temperature
Air
Temperature
Sensor
Monitor
Temperature
Return Air
Temperature
Air
Temperature
Sensor
Monitor
Temperature
Exhaust Air
Temperature
Air
Temperature
Sensor
Monitor Fresh Air
treatment
Air Temperature
Difference
Formula (see
spreadsheet)
Monitor Overall
AHU contribution
Air Temperature
Difference
Formula (see
spreadsheet)
Monitor
Operation
Thermal wheel
signal control
BMS
Datapoint
Monitor efficiency
Sensible heat
efficiency
Formula (see
spreadsheet)
AHU_5
Thermal_Wheel
Figure 19 - Diagram of scenario 3 - AHU 5 operation - Performance objectives and metrics relating
to the system performance aspect
Scenario 3 – AHU 5 operation
Qualitative
Performance
Objective
Quantitative
Performance
Metric
Performance
Aspect
Performance
Object
Energy
Consumption
AHU_5
Supply_Fan
Monitor Energy
Consumption
Electricity
consumption
Electricity
Meter
AHU_5
Return_Fan
Monitor Energy
Consumption
Electricity
consumption
Electricity
Meter
AHU_5
Thermal Wheel
Monitor Energy
Consumption
Electricity
consumption
Electricity
Meter
Sensor/Meter
Formula
Figure 20 - Diagram of scenario 3 - AHU 5 operation - Performance objectives and metrics relating
to the energy consumption aspect
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1
1
1
1
1
1
1
1
1
1
1
1
1
Energy Consumption
Legislation
System Perfomance
Thermal Loads
Building Function
Perform ance Aspect
Perform ance Object
Qualitative
Perform ance
Objective
Site
Monitor Temperature
Z_Tissue Culture Ref 2.12
Monitor Temperature
Z_Dry Specimen Storage Area Monitor Temperature
Z_First AID
Monitor Temperature
Z_Cleaner Store
Monitor Temperature
1 AHU_5_Supply_Fan
Monitor Energy Consumption
1 AHU_5_Return_Fan
Monitor Energy Consumption
1 AHU_5_Thermal Wheel
Monitor Energy Consumption
AHU_5
Monitor Temperature
AHU_5
Monitor Temperature
AHU_5
Monitor Temperature
AHU_5_Thermal Wheel
Monitor Operation
AHU_5
Monitor Fresh Air treatment
(Heating or Cooling)
AHU_5
Monitor Overall AHU
contribution (Heating or
Cooling)
AHU_5_Thermal Wheel
Monitor efficiency
Quantitative
Perform ance
Metric
PM Unit
Measurem ent Stream
Outdoor Air Temperature
Air Temperature
Air Temperature
Air Temperature
Air Temperature
Electricity consumption
Electricity consumption
Electricity consumption
Supply air temperature
Return air temperature
Exhaust air temperature
Thermal w heel signal control
Air Temperature Difference
ºC
ºC
ºC
ºC
ºC
kWh
kWh
kWh
ºC
ºC
ºC
%
ºC
Datum1
Datum150
Datum151
Datum152
Datum153
Datum74
Datum75
Datum76
Datum70
Datum71
Datum72
Datum73
Datum70 - Datum1
Air Temperature Difference
ºC
Datum70 - Datum71
Thermal w heel Sensible heat
efficiency (only w hne it is
operated)
-
(Datum70 - Datum1) /
(Datum72 - Datum71)
Figure 21 - Diagram of scenario 3 - AHU 5 operation – Complete list of performance objectives and
metrics
4.1.1. Geometric BIM - ArchiCAD
Many software vendors supply excellent software for the generation of geometric 3-D models of
buildings. All the geometrical components of the building are defined in the application, for
example, walls, slabs and roofs are defined with their construction type and relation to each
other, while materials are defined with their associated properties, such as δ - Density [kg/m3],
cp - Heat Capacity [kJ/(kg*K)], λ - Thermal Conductivity [W/(m*K)]. It is possible to be very
specific with regard to how the building components interact with each other and the materials
and properties they are made from. Although thermal properties of wall and windows are very
important for energy simulation applications, of particular interest to us is the manner in which
floors, zones and space objects may be defined and utilised by the Performance Framework
Tool in order to assign to them specific performance objectives and metrics.
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Figure 22 - ArchiCAD representation of ERI building (construction and geometry)
The 3-D visualisation capabilities of the tools provide great scope for the designer to get a feel
for how a building will look and most tools provide a clash detection system to ensure that errors
and contradictions common in 2-D drawings can be avoided.
Figure 23 - Geometric IFC Tree View in ArchiCAD (left) and
IFC file output in IFC Quick Browser (right)
CAD design tools are extremely powerful and can be used to capture all manner of technical
information about a building. The IFC record highlighted refers to the window WD – 232,
identified in the explorer window above. This geometric file is the first critical part of the Building
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Information Model. It can now be built on using further applications. A critical part of this process
is the interoperability between different applications, allowing a seamless transfer of data
between proprietary systems using an open, standardised data model.
4.1.2. HVAC BIM - DDS-CAD
Not all geometric design tools allow users to create HVAC models with the geometric model and
a central part of this research in any case is the interoperable nature of the BIM, so, using a
standard HVAC design package, it is possible to import the .ifc output file from the geometric
design package and display this using the HVAC software. Furthermore, this BIM can be
supplemented with further HVAC design information.
Figure 24 - DDS-CAD representation of ERI building (HVAC objects)
Again, great detail can be captured regarding the HVAC components and this data can be
exported in an IFC format, whereby the application maps its proprietary data model to the IFC
data model. Figure shows the ERI building with the 5 AHU on the roof, all their technical
specification have been added to the BIM and then exported as an .ifc file.
4.1.3. Performance Framework BIM - PFT
Finally, the Performance Framework Tool can be used to add performance data and sensor
definitions to the BIM. Figure and Figure show the example of a real implementation of the
AHU 5 scenario achieved following the process described in paragraph 3.1.1.
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Figure 25 - Scenario 3 (AUH 5) implemented in the PFT – building function and energy
consumption aspects
Figure 26 - Scenario 3 (AUH 5) implemented in the PFT – system performance aspect
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4.2.
ERI - Data Warehouse
The Data Warehouse Platform has been implemented using the Data Warehouse Engine from
Oracle, ensuring that implemented work is easily transferrable into a commercial product.
ETL-tools were customised using Java as implementation language. Again, this ensures that
the source code can be easily deployed on different platforms.
A pilot implementation was set-up to compile building performance data from UCC’s ERI
building. Initially, data from the existing CYLON-BMS platform (including approx 180 sensors
and actuators, an outdoor weather station, gas meter, electricity meter and water meter) has
been compiled since Summer 2008. The reading interval of most of the sensor s of the BMS
platform is 15 minutes. In a second phase wireless sensors from Tyndall were added to the
platform (see section 3.1.3). The reading interval of these sensors has been set to 5 minutes.
Back in Summer 2010 approximately 23 mil data sets from both, the wired and wireless systems
were compiled, classified, categorised and aggregated in the data warehouse platform.
Performance Data can be accessed through web-based interfaces. We discuss two interfaces
exemplarily in the following sections. The Facility Managers User Interface is depicted in Figure
27 below.
Figure 27 – Facility Manager’s User Interface
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The FM interface provides the maximum level of detail to the end user. The top left part of the
interface supports a “zone-based” navigation. The bottom left part then displays all available
sensors meters in this zone. The lower right part allows the Facility Manager to specify a start
date and an end-date for the interval in which data should be displayed. Finally, the top right
part displays the graph with the sensor or meter readings.
Figure 28 – Owner’s User Interface
The Owner’s interface displays building performance data in the most compressed form. On the
top left the user can select if she wants to display aggregated consumption data for a building, a
selected zone of the building, an organisational unit occupying building(s) or the aggregated
energy consumption for certain equipment (e.g. all AHU). On the centre right the user can
specify the period for which she wishes to aggregate data (day, week, month, year).On the top
right the result is displayed. Finally, on the lower right part the user can select for what “media”
she wishes to get aggregated consumption data (e.g. gas, water, or electricity).
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4.3.
4.3.1.
ERI - Tyndall motes - BuildWise Sensor Board (BEM1)
System Architecture and Functional Units
The mote is designed in modular mode. As Figure 29 shows, the system contains four main
units, these are data processing unit, RF communication unit, sensors/meters and actuation unit
and power supply management unit. The data processing unit can make valid control for other
units.
Figure 29 Top level system block diagram of the WSN mote
To have deeper look into the developed system, the block diagram of the mote functional units
is shown in Figure 30. The multi-sensor layer was designed to interface with number of selected
sensors as well as incorporating additional capability for use within the Building environment.
This includes dual actuation capabilities for any AC/DC system using an external high power
relay based system for devices which consume up to 280 V and 25 A (to turn on and off
appliances) as well as an onboard low power switch to enable the actuation facility. The type of
on-board sensor is either digital communicating with the microcontroller through serial bus
interface like I2C or analogue connected with any of the ADC channels.
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Figure 30 - Block diagram of the mote functional units
The two external sensors/meters interfaces are dedicated to any meter using MODBUS protocol
and
variable
resistance
temperature
sensors.
The
MODBUS
meter
is
exchanging
data/commands through RS485 serial communications.
This interface layer was also designed to incorporate external flash memory (Atmel
AT45DB041). The layer features a 4-Mbit serial flash for storing data, measurements, and other
user-defined information. It is connected to one of the USART on the ATMega1281. This chip is
supported by TinyOS and embedded C which uses this chip as micro file system. This device
consumes 15 mA of current when writing data.
ATMega1281 is a high performance, low power AVR 8-bit microcontroller with advanced RISC
architecture and owns rich hardware resources. The CC2420 was used because of its excellent
RF performance and low power consumption .The photos of both the RF and sensor layers are
shown in Figure 31. The complete 3 layers stackable 25mm mote is shown as well.
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Figure 31 - Photos of the (a) Developed sensor layer, (b) Zigbee and processor layer, and (c) The
complete 25mm stackable mote
The main sensors and units selected for the layer is listed in the Table 2 below showing the
required functionalities.
Table 2 - Sensors and units selected with their fucntionalities
Part
Functionality required
Atmel Data Flash
AT45DB041B, 4MB
SHT11 Humidity Sensor
Used for remote re-programming
Digitally Calibrated humidity/temperature sensor using I2C bus
RS485 Half Duplex
Differential Transceiver,
To interface with any MODBUS device using RS485 port
MAX3471CUA
RELAY, PHOTOMOS, 350V
OP AMP, LOW NOISE,
LMV771MG
Can be used to control switching of low current AC load
Low
power
opamp
required
for
the
water
pipe/radiant
temperature sensor interface
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SMD photodiode Ambient
light sensor, APDS-9004020
Ambient miniaturized light sensor with low power consumption
3-Axial Accelerometer,
LIS302DL, Low Power
Used to monitor the status of doors/windows
Sensors are hardware devices that produce measurable response to change in physical
condition. In this section, the different types of sensors and interfaces designs selected for the
building monitoring application are illustrated. The main objective of these sensors besides
recording the building data is to make the mote reliable for large scale deployment with low cost
and low power consumption.
4.3.2. Occupation Sensor (Passive infrared PIR)
All objects constantly exchange thermal energy in the form of electromagnetic radiations with
their surrounding. Radiation from the human body is considered to lie in the range of 8-14 µm,
hence infrared sensors that are sensitive in this range would be able to detect humans within
their detection area.
Detecting the occupancy of the rooms inside the building was one of the essential requirements
to be monitored, there was need to find suitable PIR sensor module. The Panasonic AMN44122
was selected for this purpose since it provides the required functionality in a module that is
smaller, more convenient and of lower energy consumption than the custom circuitry used in the
prototype. Furthermore, the module provides a digital detection output that is used to trigger an
interrupt on the processor when activity registers on the sensor. Analog sampling of the PIR
signal and software detection processing is no longer required as the interrupt signal is a digital
one. According to the datasheet of the PIR sensor, it has detection distance of maximum 10m
(32.808ft) and detection range of 110° in horizontal and 93° in vertical.
A simple lab test has been performed to identify actual performance of the PIR sensor and
obtained similar results to those in the datasheet. However, it was found that the actual
detection region with high reliability is a little smaller than the detection region specified in the
datasheet. Table 3 shows the comparison between the performance of PIR sensor provided in
the datasheet and the real performance obtained by our lab test.
Table 3 - The comparison of the AMN44122 PIR sensor with reference to date sheet
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Items
Datasheet
Detection Distance
10m (32.808ft) 9m (29.528ft)
Detection Horizontal 110°
Lab Test
90°
Range
Vertical
93°
90°
4.3.3. Humidity/Temperature Sensor
Relative humidity (RH) is an important indicator of air quality in buildings. Extremely low or high
humidity levels (the comfort range is 30 - 70% RH) can cause discomfort to workers and can
reduce building longevity. Humidity control also dictates building energy consumption during
heating seasons.
Conventional sensors determine relative air humidity using capacitive measurement technology.
For this principle, the sensor element is built out of a film capacitor on different substrates
(glass, ceramic, etc).The dielectric is a polymer which absorbs or releases water proportional to
the relative environmental humidity, and thus changes the capacitance of the capacitor, which is
measured by an onboard electronic circuit.
The Temperature and Humidity sensor SHT11 [11] shown in Figure 32 was used on the sensor
board which integrates signal processing, tiny foot print and provide a fully calibrated digital
output. It uses I2C serial interface to communicate with the microcontroller and provide either
the humidity or temperature data based on the received commands.
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Figure 32 - Typical application circuit of the SHT11
4.3.4. Acceleration and Motion Sensors
The detection of the windows/doors status was one of the building parameters required to be
monitored by the WSN node. 3-axis accelerometer was selected for this application since it can
provide useful angle information which helps to know how wide door/window is opened or
closed. The LIS302DL is an ultra compact low-power three axes linear accelerometer was
integrated in the node design. The device can be interfaced through either I2C or SPI serial
protocol. The mote orientation can be easily calculated using the accelerometer data providing
additional feature for future applications. In order to test and calibrate the sensor, special
Labview GUI was developed to display the sensor measurements and control all device units
through writing into the specified registers as shown in Figure 33.
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Figure 33 - 3-Axis accelerometer LABVIEW GUI
Figure.7: 3-Axis accelerometer LABVIEW GUI
The main design challenge with using the accelerometer is that the microcontroller has to be
continuously active to record sensor data which means high current consumption and short
batter life time. In order to overcome this problem, a mechanical vibration sensor with very small
package was used in this design to provide an external interrupt to the Atmel microcontroller
when there is any kind of motion at any direction.
The vibration switch is consuming negligible current and using simple analog circuitry to
generate the interrupt pulse.
4.3.5. RS485 for Water Flow Meter Interfacing
It is required to get the flow rate measurements from different locations inside the building
where pipes made from different materials and have wide scale diameter size. The ultrasonic
non-introductive was found to be the optimal solution for measuring the water flow rate of the
water on building pipes since it is not disturbing the existing pipes installation and gives flexible
testing option. One of the four miniaturized on-board connectors was dedicated to the water
flow meter interfacing. Half duplex RS485/RS232 IC was used to interface the water flow meter
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with the Universal Asynchronous Receiver Transmitter (UART) of microcontroller using the
standard industrial MODBUS protocol.
The STUF-300EB from Shenitech was used for this application. It provides excellent capabilities
for accurate liquid flow measurement from outside of a pipe. The proprietary signal quality
tracking and self-adaptation technologies allow the system to optimally adapt to different pipe
materials and liquid property changes automatically. The STUF-300EB has a surge-protected,
isolated RS485 interface with MODBUS support makes it suitable for reliable flowmeter
networking.
The Modbus can be implemented in two different modes: RTU (Remote Terminal Unit) and
ASCII. The water flow meter uses the ASCII mode with the frame format given below:
Figure 34 - Modbus ASCII Message Frame
A Modbus message is placed by the transmitting device into a frame with start and end
headers. The receiver will use identify the beginning and end of the message using the two
headers and apply error checking using the Longitudinal Redundancy Checking (LRC)
algorithm.
4.3.6. Water Pipe temperature Sensor Interfacing
The monitoring of the water temperature that is passing in the building pipes was needed as
part of the wireless sensor system. Surface Mount Temperature Sensor from SIEMENS was
selected for this application as non-introductive units and can be mounted directly on a pipe inlet
to sense the temperature of water passing through.
The temperature sensor here acts as a resistor whose resistances varies with the temperature.
Voltage divider based circuit was designed to interface the node with the sensor through one of
the on-board connectors. A low noise amplifier with a certain gain factor is used in the circuit to
adapt the range of the output signal to be suitable for the ADC channel.
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The sensor performance was compared with the existing wired sensors read by the Building
Management System (BMS) as shown in Table 4. It is very clear that the wireless sensor
displays a comparative performance to the wired one and can provide useful data from number
of pipe sites inside the building. It has to be mention that the temperature of the pipe surface is
always higher than the water by a few degrees. This will be taken into account in the calibration
process by the mote to get accurate readings.
Table 4 - Verifying the readings of the wireless pipe temperature sensor with the existence BMS
wired sensor
Temp
ºC Temp
ºC Temp
(BMS)
(Sensor)
Sensor)
20.25
19.01
20.01
23.12
21.03
22.03
30.45
29.5
30.5
45.21
43.2
44.2
48.87
47.62
48.62
ºC
(Calibrated
4.3.7. Magnetic Hall Effect Sensor for Detecting Windows/Doors status
The A3214 is integrated circuit is an ultra-sensitive, pole independent Hall-effect switch with a
latched digital output. It is especially suited for operation in battery-operated, hand-held
equipment. A 2.4 to 5.5 V operation and a unique clocking scheme reduce the average
operating power requirements – the A3214 to 14 µW (typical, at 2.75 V).
The A3214 switch has been incorporated in BEM1 platform to be used for the application of
detecting the status Windows/Doors
4.3.8.
Actuation Capability
The wireless control of switching on/off different types of AC loads in the building is meant to be
the second application for the node beside the data monitoring. The base station will be
responsible of collecting and processing the different types of sensors data and send the
commands to some of designated nodes to perform actuation like switching on/off light, heat
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pumps, water valves or radiators. To achieve this goal on a miniaturized node, number of
design options was considered taken into consideration many aspects like the effect of AC high
voltage on the low power circuitry of the node and also the possible ways to interconnect with
different types of single/three phases loads. The current design provides two options, first
controlling small current, up to 2 Amps, ac loads like PCs using on-board PHOTOMOS relay
which is optoelectronic device drives a power MOSFET. Second option is providing the ability
to connect an external relay that derives higher current loads through one of the on-board
connectors.
4.4.
ERI – Wireless Sensors Network
Responsible: CIT
WSN design, field tests and deployed WSN
4.4.1.
ERI Prototype Wireless Sensor Network
The BuildWise - ERI Prototype 1 is focused on environmental and energy management
scenarios. To support these scenarios, reduce wiring costs and setup time, several wireless
measurement data streams are required. A number of steps are necessary to realise this
prototype, the first step is the definition of application requirements. Each scenario is described
by performance aspects which are in turn assigned Performance Objects, Objectives, Metrics
and sensors that will deliver associated data streams. This section is focused on the wireless
network to support the deployment procedure. As part of the application requirements
deployment schematics indicate the proposed locations in the Environmental Research Institute
(ERI) for wireless sensors in the specified locations LG04 LG06, LG09, G05 Immunology Lab,
1.23 Open Office room, 1.28 Seminar Room and 1.28 Seminar Room and Breakout Space.
The sensor positions are predefined to ensure appropriate sensed data is measured from the
correct areas of the environment to enrich the building management system with more
environmental data. However the position of gateways and repeaters to ensure reliable data
communication to the data warehouse requires further analysis. An experienced designer set
out the devices and gateway positions to create an initial network topology and ran some tests.
During this testing phase a number of potential problem areas were identified surrounding the
influence of the environment on packet reception rate and required further analysis. To support
this effort a site survey was undertaken within the ERI to evaluate the environment influence on
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signal propagation and the data can be used to tune the prediction model of the WSN Design
tool to aid the designer with further enhancements to the wireless infrastructure.
Currently the wireless nodes deployed in ERI have been place by an experienced designer
however there are some difficulties getting data back to gateway node and requires the position
of a repeater. The designer is interested in evaluating positioning constraints and variations to
ensure a reliable network as it expands across other areas of the building. Figure 35 shows the
distribution of nodes on 2 floors of the ERI during RF tests.
Figure 35 - Nodes deployed in ERI during test period
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4.4.1.1.
Measurement Results
Approximately 56 measurements were taking at various locations within the ground and first
floors of the ERI using measurement tools developed at CIT.
Ground Floor Scenario 1.0:
This scenario involved basic measurements to ensure the site survey tools are working
correctly. Node 002 was placed on the desk in ERI Room G.04 (Office) and some measurement
was done along the corridor.
Ground Floor Scenario 2.0:
Three client nodes were deployed in the areas’ of interest for currently deployed data nodes on
the ground floor. The scenario investigates if it is possible to reach the gateway or another node
along the path to the gateway from the node deployed on manifold (0003). The results of the
measurement are shown in Figure 36.
Figure 36 - All Measurements taken on the ground floor
The data that was collected was used to compare with the propagation model used as part of
the WSN design tool, an example of results of which are presented in Figure 37 and Figure 38.
It can be seen that the prediction closely matches the real measured data, therefore the design
tool can provide an accurate link estimate to establish the optimal position of repeater and
gateway nodes. It can be recommended based on these measurement campaigns that a
repeater is required to ensure a high quality link between node 0003 and the gateway on the
ground floor. Therefore there is no need to deploy an additional gateway.
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Figure 37 - Node 0002 Prediction Difference (Power Offset – 29dBm)
Figure 38 - Comparison between Design tool prediction and Measurement
Scenario 2.1:
This scenario asks what signal level can be received on the first floor from nodes deployed on
the ground floor? Figure 39 shows the results of the measurement campaign.
Figure 39 – 1st Floor Measurements from node 4 deployed on Ground floor
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Although signal level could be received from node 0004, this is due to an open stair well. The
received signal strength remains low and a threshold of -85dBm would not be guaranteed.
Therefore it would not be feasible to have nodes on the ground floor send data to a gateway on
the second floor. This is due to the material type on the floor, it is extra heavy poured concrete
therefore attenuates the signal greatly.
Ground Floor Scenario 2.2:
This scenario is interested in the orientation of the device. What influence does having node
0004 deployed on top of the cable tray as opposed to facing down attached to the bottom of the
cable tray. It was found that close to the area where the node was deployed a better signal can
be received +5dBm (Figure 40). This may not be significant as it is below the -85dBm threshold.
Further along the corridor towards the currently deployed gateway the signal level appears
better when the node is on the top of the cable tray. The difference can be attributed to the
cable tray acting as a wave guide along the corridor or other influences such as people moving,
door opened, the difference between the node orientations in this environment seems to be
negligible. I would suggest the device should be to placed face down if possible particularly in
the instance where it may act as a repeater to other nodes in its vicinity.
Node 4 Face Down Ground Level
Node 4 Face UP Ground Level
Figure 40 - Measurement from node 4 with different orientation
First Floor Scenario 3.0
Measurements were taken on the first floor to evaluate if nodes that will be placed in the
seminar room, breakout space and on the manifold in the toilet can communicate to the
gateway in the stairwell area. The position of the gateway is restricted to this area for two
reasons, firstly the availability of a power sockets and secondly to support the ad-hoc WiFi
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backbone back to the BMS server. Based on the measurements presented in Figure 41 it is
recommended a repeater node should be placed in the corridor marked with X on the map
below to ensure connectivity.
X
Figure 41 - First Floor Measurements (30-58)
The measurement campaign that was undertaken within the ERI provided a valuable insight into
the complexities and constraints associated with deploying a large network in a building to
support environment monitoring. Also it provided important data for tuning the prediction models
used in the WSN Design Tool.
4.4.2.
ERI Final Deployment
The following section images give a brief overview of the wireless sensors/meters placement
for the deployment of a larger scale WSN incorporating additional sensing capability. Figure 42
to Figure 46 show an overview of the ERI deployment expansion and the measurement streams
required for efficient building management
Z_G05:Immunology Lab
UFH Manifold 0.02
Figure 42 - Ground floor sensor/meters placement overview
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UFH Manifold
1.03
Z_1.28: Break
Out Space
UFH Manifold
1.01
Z_1.23: Open Plan
Office Space
Z_1.28: Seminar
Room
Figure 43 - First floor sensor/meters placement overview
Figure 44 - Detail Z_G05: Immunology Lab
Figure 45 - Detail Z_1.23: Open Plan Office Space
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Figure 46 - Detail Z_1.28: Break Out Space and Z_1.28: Seminar Room
At the current stage, a total of (60) nodes were deployed in the selected three main zones within
the ERI building to perform sensing and monitoring of the following room parameters: light,
temperature, humidity, occupancy, CO2 level, close/open window/door status and Radiant
temperature according to the needs of these zones as specified by the civil engineers. The
nodes are located as follows:
- Seminar Room and Break-Out Space on the first floor:
- Open Office space on the first floor:
- Immunology lab on the ground floor:
Some of the motes act as intermediate nodes maintaining connectivity to the gateway. The
sensors data were validated and calibrated using number of methods depending on the
availability of an identical wired sensor or the proper measuring tool.
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Table 1 Calibration and validation methods used for the deployed sensors
Sensor Type
Data Calibration/Validation
Light
LUX Meter
Air Temperature/Humidity
BMS and Humidity meter
PIR Occupancy
Manual validation
CO2 Level
BMS
Window/Door Status
Manual validation
Radiant Temperature
BMS
Photos of the different sensors deployed at the three zones are shown in Figure 47:
(a)
(b)
(c)
Figure 47 - Deployed sensor (a) radiant temperature, (b) Window close/open, and (c) light
The motes are operating with duty cycle of 1 reading every 12 minutes to help minimizing power
consumption with the exception of the PIR which is configured to run more rapidly in order to
detect any unexpected events. The network is stable and continuously providing data to the
BMS for analysis.
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5. BuildWise related commercialisation activities
5.1.
BuildWise project Commercialisation Activities– Executive Summary
The Enterprise Ireland funded BuildWise project has, over the last 3.5 years, had a catalytic
impact on the development of an internationally-recognised cluster of companies and
academics operating in the area of smart buildings.
The EI BuildWise academic partners have led the establishment of a critical mass of focused
activity within the Cork-led SMART Building cluster with complimentary funding (€25m to date)
from the Higher Education Authority (NEMBES), Science Foundation Ireland (ITOBO) and EU
FP7 (e.g. E4U, Reeb, InTube and ME3GAS).
This SMART Building cluster incorporating and initiated by the BuildWise project has now
established itself as one of the leading multi-disciplinary research clusters worldwide in
addressing the end-to-end challenges associated with the application of ICT to optimised
management and operation of energy use in large-scale buildings. In particular, the consortium
now represents an international industry-academic consortium focused on addressing the
development and implementation of next-generation intelligent building energy management
systems encompassing monitoring and control of lighting, heating and air-conditioning powered
to a large degree from renewable micro-generation.
The academic partners now represent many of the key players in Ireland in wireless sensor
infrastructure, civil, mechanical and complex engineering systems as well as data management
and data mining. They include leading experts in UCC, CIT, NUIG, TCD and UCD.
The industry partners represent a cross-section of scale from multi-nationals based in Ireland
(IBM, Intel, UTRC) and abroad (ARUP, HSG) to Irish SMEs (Cylon Controls, EI Electronics,
Vector FM) and new start-ups (Wirelite Sensors, WOW Energy). It also includes public bodies,
Cork City Council and Cork University Hospital.
A unique and strategic element of the consortium is the fact that the industry partners have
been selected to represent all elements of the supply chain thereby presenting significant
opportunities for complimentary research and synergy in terms of the identification of, and
engagement in, future, multi-partner business opportunities.
The consortium has identified and developed IP in the different technology research spaces in
which they are operating, specifically these are in the areas of PF-Tool development, Energy
Management web services (DW), WSN design tool and Lower Low-power IP based wireless
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sensor network protocol suite as well as Energy Management Platforms using WSN
technologies
All of the Institutes involved in the BuildWise Consortium have through discussions with their
respective TTO offices identified IP in their respective areas of research and are actively
pursuing commercialisation routes through tech transfer mechanisms such as licensing and
development of Invention Disclosure Forms (IDFs) with the vision that these will develop in to
full patents, material transfer agreements, etc.
The key success of the BuildWise Consortium has been the engagement with Wirelite Sensors
Ltd., an Irish start-up company, BIAG member, in the energy demand management space. As
part of an EI-funded Innovation Partnership, funded during the BuildWise project, Wirelite plan
to demonstrate, using Tyndall’s WSN hardware platform, an integrated energy demand
management solution in the commercial/retail market, both in Ireland and Europe. One licence
agreement has already been put in place to improve network reliability for wireless actuation
and control and further licensing agreements are expected to follow.
The critical mass of research activity, established around the cluster, has already delivered
significant impact as evidenced by the announcement, in April 2010, by United Technology
Research Centre (UTRC), to establish a research centre in Cork (with staff compliment of 35
people) and the parallel announcement by the Government of the establishment of the
International Energy Research Centre in Tyndall (with a staff compliment of more than 50
people). UTRC have already confirmed their intention to be the first industry partner in the
IERC.
Discussions are ongoing with further potential partner companies including ESB Networks, Glen
Dimplex and QinetiQ North America. Most recently, Irish start-up Resourcekraft and Cork-based
ARUP have partnered Tyndall in the FP7 ME3GAS project funded by EI and the EU under the
Artemis programme.
The following represents feedback from Sean O'Driscoll, CEO, Glen Dimplex following a visit, in
October 2009, to Cork: "I did not expect to see the level of joined-up thinking that I have seen
this morning. I've not seen anything like this from any other university in Ireland. There is great
work going on here and we already have a few ideas that we want to pursue. We will be back
before the end of November with thoughts on how to move forward."
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5.2.
Exploitation Possibilities 2010-2012
This document summarises the success and the long-term vision of the SMART Building
consortium. The cluster, which has evolved out of BuildWise, will deliver value to Ireland
through the development of advanced technology platforms and through the nurturing and
facilitation of an international business eco-system for Irish companies in the emerging space of
intelligent buildings. Significant value has already been delivered and further opportunities to
further scale the impact should be explored.
To drive all of these activities to further success and growth we need a number of
commercialized/large scale WSN activities to operate over a prolonged period to define
business models and address technical challenges related to such deployments. This is also
required to prove that potential savings can be sustained.
The cluster plans to sustain and grow its research activities and its impact on enterprise and
innovation in Ireland through the following initiatives:
o The objective of the establishment of a large-scale, multi-site test-bed is to provide Irish
industry – particularly the SMES operating as part of the Wisen Industry led research clusterwith the capability to demonstrate, validate and qualify their next generation technology
platforms and products and services in the Building Energy Management/Smart Building
space. This presents a very significant opportunity for Ireland to grow companies in this
emerging sector across the full supply chain including electronics hardware development,
Building and HVAC control systems, Data warehousing services and facility management.
The smart building cluster proposes the establishment of the test bed infrastructure within the
UCC/CIT campus. The outline specifications for the proposed test-bed are that a 1,000 to
10,000 node wireless sensor and actuator test-bed for building energy management will be
established. It will be a multi-site network encompassing multiple buildings on the UCC/CiT
campuses. The consortium proposes to leverage the test bed infrastructure with existing and
future collaborations such as the recently funded IERC and FP7 projects leading to
heterogeneous networks at different industry and academic client sites, and multiple sites
across Europe.
o Refinement and expansion of the industry clustering model which the project has operated
over the last 3 years whereby multi-nationals, SMEs and start-ups can establish strategic
partnerships to engage in new business joint venture opportunities in the emerging market of
intelligent systems for building management. Other targeted clusters which present unique
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opportunities in Ireland include lighting (domestic and street lighting), data centres, public
buildings (schools, hospitals and offices) and social housing.
Funding for those clustering activities could fit within either a multi-partner innovation
partnership program or within a centre of competency model. The multi partner IP
provides immediate engagement of industry partners and a more direct, short term route to
commercialisation and exploitation of funded research through appropriate technology
transfer mechanisms.
o Active engagement within the International Energy Research Centre to be established at
Tyndall – it is anticipated that the SMART Building cluster, in collaboration with other
strategic research providers throughout the country, will be the key partner and champion of
a research strand in ICT for demand-side management in the built environment.
o Ongoing and expanded engagement in FP7 and the follow-on FP8 EU research
programmes. Energy is a central theme in the EU programmes and related Technology
Platforms. All the SMART Building cluster partners have demonstrated their ability and
commitment to enhance their funding through European collaborations. They have also
demonstrated a commitment to bring Irish industry partners into European consortia, thereby
enabling Irish companies to establish and develop international partnerships and market
opportunities for new products and services.
o Creating future FDI opportunities as well as growing those already created and supported in
the work to date (e.g. UTRC, HSG Zander)
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5.2.1.
Summary of Commercialisation Activities for the Consortium
Commercial
Strategic alliances
Patent
opportunities
PS-Tool
/
Product / Service
Other
License
AEC3 (BIM standardisation)
In discussion
Product
Enerit (ISO 16001 management)
with
version* (May 2010)
IBM - Green Sigma Product
TTO
Cylon
Controls-active
NUIG
*beta
Possible service to
energy
follow
product
Wirelite (Data structuring)
Energy
Intelligent use of energy information
In discussion
Product
Management
and innovative business models
with
version* (May 2010)
energy
web
Glen Dimplex
TTO
Possible service to
developed
follow
industry
service
(DW)
UCC
ESB
*beta
Desktop
interfaces
for
management
with
selected
partners
(Cylon,
Vector-FM, Wirelite, Intel)
WSN
design
tool
Salto
In discussion
Product
“beta
EnOcean
with CIT TTO
version”
providing
UTRC
manual
Wirelite
automatic
HSG Zander
capabilities
and
design
Arup
Low-power
Analog Devices
In discussion
Porting and tuning of
based wireless
Decawave
with CIT TTO
implementation
sensor network
Benetel
currently under way
protocol
UTRC
for TinyOS 2.x. Agent
with
IP
suite
adaptive
agent
based
power
EuroTech
approach
validated
Partnership Project through TEC
Ltd.
(Innovation
through
computer
Centre)
simulation.
management
Energy
SMEs:-
Management
Cylon,
Resourcekraft,
Platforms
Selfbuildpartners,
Episensor,
tech,
Excelsys,
Powervation,
MiPower,
Wirelite,
FMC
Chipsensors,
SensL,
Western
Innovation
“Low cost” application
SME
Partnership
specific BEM board
coordinated with EI (Sean
under
implemented
Burke)
In discussion
Automation, Nualight, Ei Electronics
with
MNCs:- EMC, Moog, TI, Glen
TTO
Dimplex,
IBM,
Intel,
way
with Wirelite
€)
(~100
program
event
3 Artemis/Catrene Projects
approved/under evaluation
UCC
Texas
Instruments, Analog Devices
Discussions by phone
SMEs:- Ikon Semi, Ircona, Litewave
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5.3.
Industry Interaction and BuildWise Industrial Engagement 2009-2010
A key differentiator in the engagement with industry by the Smart Building cluster research
partners is the methodology used to guide the applications-driven, solutions-orientated
research. The following sections address the consortiums continuing activities in the areas of
engagement with Industry
•
Direct engagement with Irish and foreign companies
•
Industry clustering
•
Interacting with Irish industry in the context of leveraging external funding e.g. FP7 and
other EU funding opportunities.
The 1st step in this process is to talk with industry and understand their needs. This of course is
coupled with sharing with industry the existing and emerging technology solutions available
either through the BEM partners or their network of contacts. From such engagement
opportunities for both one-on-one research (e.g. innovation partnerships) and collaborative
engagement (e.g. industry cluster, FP7 partnerships) arise.
It is beyond the scope of this document to outline all the discussions and opportunities but the
following tables provides a top level overview of the Irish based companies approached and a
broad-brush cluster categorization.
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CONFIDENTIAL - Potential Clusters - Irish companies
Cluster 1
Cluster 2
Cluster 3
Cluster 4
WSN Retrofit in
Buildings
Data centre/computing energy efficiency
Smart sensors
Large scale deployments
Resourcekraft
EMC
Western
Automation
BGE
DHS
Dell
Alps
ESB
SensL
IBM
Wirelite
Wow-Energy/Integrated
Green
Wirelite
Google
Episensor
Airtricity
Cylon
Cisco
Solarprint
Cisco
Episensor
Excelsys
SELC
HSG Ireland
Intel
FMC tech
Alcatel/Lucent
Accenture
Resourcekraft
BNM
UTRC
UTRC
Wirelite
Enerit
FMC tech
Resourcekraft
Arup
E4U
(power/control)
Smart/energy efficient
factories
Energy
Efficiency
lighting
Green house/school
On Semi
DePuy (Vistakon)
Nualight
Selfbuild partners
TI
Pepsi
Coradata
Fewer Harrington Partners
Excelsys
Boston Scientific
Excelysis
Velux Ireland
Powervation
Apple
Wirelite
Wain Morehead Architects
Western
Automation
EMC
Ikon Semi
Glen Dimplex
UTRC
Moog
SELC
Kingspan
Rockbrook
Cable plan
Emerson
Convertech
APC
Contacted and potentially
interested
Contacted but not
discussed yet
abc
Target
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5.3.1.
‘Engine for innovation’ clustering process flow chart
The process flowchart (ref (a)-(b) below) is developed on the basis of the industry engagement
to date and how this can be used to drive research that adds value to Irish industry and
ultimately creates growth in revenue and new jobs.
The chart flows from left to right, starts with industry engagement and if appropriate, the type of
related clustering activity involved. Top to bottom it also roughly flows from short-term to long
term activities and resultant impact.
It is significantly different to the model used by most universities and research centres where the
1st step is traditionally to look at the funding mechanisms available, find some work of interest
and then goes looking for industry sponsors. If the research is relevant to industry it makes
more sense to retrofit the industry need into the available funding mechanisms. It also
involves immediately understanding the impact before devising the technology proposal. The
plan is to share this flowchart with industry and use it as a tool to help researchers understand
business needs and potential impact whilst allowing industry to understand the scope for
engagement with researchers and other industry collaborators as well as determining the
resourcing and funding options available.
This is the model used for the interaction with Wirelite Sensors from initial interactions as part of
the BuildWise BIAG, identifying their requirements as the relationship between the SME and
consortium matured, identifying collaborative commercial opportunities and the development of
an innovation partnership proposal funded by Enterprise Ireland with associated licensing of
technology developed as part of the Wisen funded research program - (see section 5.1).
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Buildwise/ITOBO/IERC–
Engine for Innovation Process Overview
CLUSTER
ACTIVITY
COMPANIES
1. Identify company
need
- Cluster or one on one
partnership
MARKETS
PLATFORMS
/GOAL
TIMELINE
RESOURCE
2. Determine
target market
of company/ 3. Determine
cluster
goals and
FUNDING
6. What is
impact and
benefit to
funder(s)
impact
- Technology and
commercial 4. Short term - seize
growth/niche
opportunity
Long term – increase
core skills, develop 5. Goals defined
strategy
- Execution speed
Demand management
in buildings
- Tech transfer
- Knowledge
retention
Smart Districts
Smart Cities
Smart Grids
EV
Energy Supply
(Macro & Micro)
(a) Top level process flow
Buildwise/ITOBO/IERC–
Engine for Innovation Process Detail
CLUSTER
ACTIVITY
COMPANIES
MARKETS
PLATFORMS
/GOAL
TIMELINE
RESOURCE
FUNDING
Commercial
Prove/Integrat
e
Technology
Short
Industry
placement
VCs
EE lighting
Start-ups
EE data
centres
Factories
EE HVAC
SME
(mature)
Utilities
MNCs
-electricity
-water, gas
Smart factories
State/
Semi-state
Public
Buildings
-Schools
-Hospitals
-Universities
-Libraries
Structural
Residential
(housing)
Safety
-leased
-private
-public
Demand management
in buildings
EV
Student
placement
(in industry)
Prove new
business
models
Medium
Understand
stakeholder
needs
Masters
Develop
Technology
+ roadmaps
EI/IDA
-PoC, CFTD
-IP, C+
IRCSET
SEIA/
Government
Postdoc
- End to end
solutions
Environmenta
l
Private Co.
-Mature
-New technology
IERC
Cluster/Network
PhD
Long
Smart Districts
Smart Cities
Smart Grids
EU
-PPPs,PSPs
-SME clusters
-Artemis
-ENIAC,CATRENE
Energy Supply
(Macro & Micro)
(b) Detailed process flowchart
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Buildwise/ITOBO/IERC–
Engine for Innovation Example
CLUSTER
ACTIVITY
EE
lighting
COMPANIES
MARKETS
PLATFORMS
/GOAL
TIMELINE
Commercial
Prove/Integrat
e
Technology
Short
Start-ups
MNCs
State/
Semi-state
Private Co.
EI/IDA
-PoC, CFTD
-IP, C+
Prove new
business
models
Public
Buildings
Medium
-Schools
-Hospitals
-Universities
-Libraries
FUNDING
VCs
-Mature
-New technology
Factories
SME
(mature)
RESOURCE
Masters
IRCSET
SEIA/
Government
Postdoc
IERC
Cluster/Network
PhD
Develop
Technology
+ roadmaps
Demand management
in buildings
-PPPs,PSPs
-SME clusters
-Artemis
-ENIAC,CATRENE
Smart Districts
Smart Cities
Smart Grids
EV
EU
Energy Supply
(Macro & Micro)
(c) Energy efficient lighting cluster example
Buildwise/ITOBO/IERC–
Engine for Innovation Example
CLUSTER
ACTIVITY
EE data
centres
COMPANIES
MARKETS
PLATFORMS
/GOAL
TIMELINE
RESOURCE
FUNDING
Commercial
Prove/Integrat
e
Technology
Short
Industry
placement
VCs
Private Co.
-Mature
-New technology
SME
(mature)
MNCs
Student
placement
(in industry)
Prove new
business
models
Medium
Understand
stakeholder
needs
Masters
Demand management
in buildings
EV
Smart Districts
Smart Cities
Smart Grids
-PoC, CFTD
-IP, C+
IRCSET
SEIA/
Government
Postdoc
- End to end
solutions
Develop
Technology
+ roadmaps
EI/IDA
IERC
Cluster/Network
PhD
EU
-PPPs,PSPs
-SME clusters
-Artemis
-ENIAC,CATRENE
Energy Supply
(Macro & Micro)
(d) Energy efficiency data centre cluster example
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5.4.
Identification of commercial opportunities
5.4.1.1.
Market Analysis and Market Benefit, (Frost & Sullivan 2006)
Efforts in the research and development of wireless sensors have resulted in the availability of
commercial products. However the market is fragmented with the presence of a number of
participants and applications. The adoption process has been slow, as there are a number of
challenges posed versus the compelling benefits offered by the wireless technology.
Though the adoption has been slow, there is a constant R&D taking place in the wireless
sensors technology that has resulted in overcoming major drawbacks such as reliability. The
adoption is expected to increase only through end-user awareness that is by demonstrating its
ability to solve some of the real world applications where wiring is impossible or hazardous.
Moreover companies have started to address some of these applications and thus wireless
sensor technology is promising to be more interesting by creating more opportunities.
Competitive Analysis
The market for wireless sensors and transmitters is populated with small, mid-sized as well as
new sensor companies. The newer companies focus on advanced wireless sensing, that helps
place the sensor on a chip, and incorporate a microprocessor. However traditional sensor
companies that have forayed in to the wireless world focus on sensor technology and
applications where they have expertise. Major companies purchase the technology and build
their own products and in some cases look to buy the products and resell them. Among the
various types of participants, there are sensor manufacturers who build their own wireless
sensors and there are sensor manufacturers who purchase the communication components and
then integrate it with their sensors. The manufacturers of Radio Frequency (RF)
communications buy the sensors from a third party and then integrate their proprietary
communications components on to it. Large companies and some smaller companies are
expected to venture into joint undertaking and acquisitions. The interest and activity in the
wireless sensors is mainly among early adopters and the competitive nature of this market is
expected to increase further when the technology evolves and adoption of this technology
increases.
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Building and Home Automation
The figures below show the Building and Home Automation end-user segment revenue
forecasts for the world wireless sensors and transmitters market for the period 20 02-2012.
Wireless Sensors and Transmitters Market: Revenue Forecasts for Building and Home
Automation (World), 2002-2012
Wireless Sensors and Transmitters Market: Revenue Forecasts for Building and Home
Automation (World), 2002-2012
Note: All figures are rounded; the base year is 2005. Source: Frost & Sullivan
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The building and home automation end-user segment generated revenues of $6.4 million in
2005 and the growth rate was 13.4 percent. A continuous supervision and monitoring is required
for an efficient HVAC system in manufacturing, university, hotel, hospital and other commercial
building operations. Any interruption to such systems could cause inconvenience to customers,
interfere with production or may result even in the shutdown of operations. However a cost
effective means for monitoring a broad range of HVAC processes and systems is provided by
wireless solutions. The wireless solutions in HVAC processes and systems also help in
optimizing efficiency and in avoiding catastrophic events.
Top Growth Areas
Wireless sensor networks are rapidly gaining a stronghold in various industrial sectors such as
building automation and industrial automation. With its obvious benefits and new innovations in
the wireless space, this technology is all set to grow very rapidly, expanding the market to
various other sectors such as home control and medical devices. The top growth areas are
expected to be energy for metering, building automation, home automation, energy control, and
industrial control (industrial automation).
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5.4.2.
Summary Analysis of Competitors and supply chain
The figure below shows the supply chain identified during the course of the BuildWise project.
The supply chain mainly consists of companies targeting products and services associated with:
•
•
•
•
•
Building Control Automation;
Monitoring and Targeting;
Facilities Management (FM);
Management Consultancy;
System Component Manufacturer;
The different Products and Services features offered by each company are listed in the top row
•
•
•
•
•
•
•
•
•
Web Service Application M&T;
Real Time Analysis;
Wireless Data Logging;
Desktop Application M&T;
Handheld Option;
Advanced Data Processing;
Stakeholder Specific Configurations;
Performance Benchmarking;
Multi-Stakeholder Data Management;
Building Control Automation
Lightwave Technologies
Building
Control
Automation
Satchwell
Cylon
Siemens
System / Managem. Monitoring and Component FM
Consult.
Targeting
Manufacturer
Johnson Controls
ResourceKraft
Monitoring
Wirelite
and
Targeting
Hawksbury ESightenergy
FM
Vector FM \ Spokesoft
IBM Green Sigma
Management
Intel
Consultancy
EI Electronics
System
Component
EPI Sensor
Manufacturer
enocean
BuildWise
W
e
Ap bs
pl erv
ica ic
tio e n M
&
T
Re
al
T
im
e An
al
ys
W
is
ire
le
ss
D
Lo
gg ata
in g
De
sk
to
p Ap
pl
M ica
t
&
T ion
Ha
nd
he
ld
O
pt
io
n
Ad
va
nc
e
Pr d D
oc
es ata
sin g
St
ak
eh
ol
Co de
nf r S
ig pe
ur
c
at ific
Pe
io
ns
rfo
Be rm
nc an
hm ce
ar ki
ng
M
ul
ti Da St
ta ake
M h
an old
ag er
em en
t
Co
m
pa
ny
Analysis of competitors and supply chain (CM4)
Yes
Yes
No
No
No
Yes
No
Yes
Yes
No Demand
Yes
No
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
No
No
Yes
Yes
Yes
Yes
Yes
No
No
Yes
Yes
No
No
No
No
No
Yes
Yes
Yes
No
No
No
No
No
Manager/ Field Crew Expert and Basic
Manager / Technician
Not Relevant
Yes
No
No
No
No
No
Yes
Yes
No
No
Yes
Not Relevant
Not Relevant
Not Relevant
Not Relevant
Not Relevant
Not Relevant
Yes
Intranet
Yes
No
Yes
No
Yes
No
No
Yes
No
Not Relevant
Not Relevant
Not Relevant
No
No
Yes
No
No
No
No
No
No
Yes
No
No
No
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Fire Systems
Historical Data
Historical Data
Historical Data
Historical Data
Historical Data
Historical Data
Historical Data
Historical Data
Not Relevant
Historical Data
Normalised Historical Not Relevant
Not Applicable
Not Applicable
Flexible Sources
No
No
No
No
No
No
No
No
No
No
No
No
No
No
Yes
The last row of the figure depicts the Product and Services features addressed by BuildWise.
This clearly demonstrates that the BuildWise technology platform has the potential to address
ALL of the features that are only partially delivered by competitor companies in the different
building energy management sectors
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5.4.3.
5.4.3.1.
Performance Specification Tool (PST)
Product offering,
The PST has been developed to provide building owners, designers, commissioning experts
and building operators with a tool to systematically specify, deploy and monitor environmental
and energy behaviour of buildings across the building life cycle. The PST is underpinned by a
standardised (ISO) data model (IFC 2.3) that facilitates the integration of the various industry
standard representations of buildings that includes 3-D CAD models, material constructions,
HVAC systems and multiple data streams. The PST tool data structure that underpins the PST
enables data visualisation by multiple building stakeholders leveraged through data
warehousing technologies. The PST has focused primarily on supporting energy mangers in
buildings at the operation stage of the building. The PFT successfully represents the various
forms (3D-CAD, HVAC, BMS) of the building into formal building operation strategies that
comprise best practice in holistic environmental and energy management.
5.4.3.2.
Unique Selling Point
The PST provides energy managers (and other building stakeholders) with a tool that
systematically structures and visualises best practice holistic environmental and energy
performance of buildings. The building environmental and energy performance is structured in
systematic best practice performance scenarios and delivered using easily understood and
navigable metaphors that include 3-D CAD models, League tables and Traffic Light Systems
underpinned by real-time data leveraged from ‘wired’ and ‘wireless’ Building Management
Systems. The data model underpinning the PST has been developed to underpin seamless
interoperability between industry standard tools (e.g. 3-D CAD), data acquisition technologies
(BMS) and data warehousing tools that are currently used to represent building performance at
ALL stages of the building life cycle.
5.4.3.3.
IP identification, patent searches, freedom to operate
The PST was developed as part of a PhD thesis (O’ Donnell, 2009) and the methodology has
been identified as BuildWise IP. This IP has been described in a recently developed Invention
Disclosure Form (IDF) submitted to NUIG TTO (April 2010) and forms the basis as background
IP to the ITOBO SRC.
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5.4.3.4.
TTO discussion/IDF’s
Discussions with NUIG TTOs are ongoing to establish commercial opportunities presented in
4.3.3.
5.4.3.5.
Market Analysis and Market Benefit,
BuildWise has actively engaged with its Industry partners through the BuildWise Building
Industry Advisory Group with regard to both technical and market implications of the research
activity. The PST tool has been developed in line with continuous market analysis with direct
input from industry members.
5.4.3.6.
Potential licensees.
Discussions with a number of companies in the BuildWise BIAG have been on-going throughout
the BuildWise project. These specifically include IBM and Cylon Controls. There is an intention
to submit (September 2010) IRCSET Enterprise Partnership Scheme (EPS) with IBM to extend
the PST data model and develop a series of visualisation mechanisms in the context of the IBM
Green Sigma product offering. Discussion have been initiated with Cylon Controls with respect
to their Active Energy product offering
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5.4.4.
Data Warehouse
5.4.4.1.
Product offering,
Based on an analysis of Information Models (e.g. IFC 2.x3) and user requirements with Industry
Partners (BIAC and ITOBO) the information requirements for the Data Warehouse have been
identified. Additional information objects with respect to the Management of Building
Performance Data were added when required. A data structure and partitioning strategy was
developed to allow optimal data processing of bulk data. The system has been tested under
operation since with approximately 22 million data sets autumn 2008
Market opportunity
ƒ
Information Schema: Capable to manage high-volume bulk-data, to import data from
inhomogeneous data sources.
ƒ
Efficient Classification and Characterization: Capability to import CAD-.related data for
classification of performance data
ƒ
Failure Identification: Capability to identify failures and inconsistencies in bulk data
stream during loading.
ƒ
Standardised Format: Management of Building Performance Data and Classification
Data in one single IT-system.
5.4.4.2.
Unique Selling Point
The BuildWise Data Warehouse Platform is unique since it is capable to integrate two different
types of data streams, (1) the Building Performance Data Stream compiled from temporary
archives of Building Management Systems or directly from wireless sensors, meters (also called
fact data) and (2) the Performance Classification and Categorization Data compiled from Design
and Management Systems, such as CAD or ERP systems (also called Dimensional Data).
The Data Warehouse Schema consists of 3 parts with currently a total of 30 information objects.
PART 1: Staging Area:
The part of the DW-schema is introduced to ensure that bulk data and classification data from
different external sources can be imported in the DataWarehouse core area in a consistent way.
Data cleansing and consolidation is processed in the staging area.
Continuously compiled data is accessible for “ad-hoc” usage through the staging area.
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PART 2: Core Area: Fact Data Management
Fact Data is managed in horizontally partitioned tables. In case of increasing number of
applications fact tables can be partitioned vertically to enable optimal processing of different
types of performance data, such as temperature, humidity, lux-levels, presence, etc.
Horizontal partitioning allows optimisation of the management, back-up, and restoration of
performance data. Vertical partitioning has two advantages (1) selected data can be processed
quicker for domain-specific analysis (e.g. lighting systems only) and (2) performance data can
physically distributed across multiple machines but is still part of one consistent
logical
database schema.
PART 3: Aggregated Data
This part of the Data Warehouse manages aggregated and categorized data which is provided
to the end user. Navigation is supported through the introduction of multiple dimensions. Data of
appropriate granularity can be accessed. For example, building owners can access the total
energy consumption for all buildings they own on a campus on a weekly, monthly or yearly
basis. Whereas tenants could access consumption data per Group, Department, floor, or zone
used per day, week or month.
The implemented and tested Data Warehouse is built on the Oracle DataWarehouse Engine. By
using a commercially available product as core for the implementation we can guarantee
robustness and secure investments for potential clients. We have ensured compatibility to other
commercially available systems by complying with ISO/IEC 9075 (SQL) in its latest version SQL
2008 ISO/IEC 9075-11:2008.
a. User interfaces for commercial applications
In collaboration with BIAG members we have identified three stakeholder profiles and
developed three sets of graphical user interfaces for each stakeholder,
(1) The building owner perspective:
This view addresses both, owners of a single residential building or owners of multiple
commercial buildings. Meter readings related to the owner’s properties are accumulated
and presented in multiple time dimensions.
(2) The building operator perspective:
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This view addresses companies with a profile in Facilities Management and Energy
Management. It allows to “drill down” to individual readings of sensors and meters and to
support information acquisition for “in-filed-diagnosis” of Building Management Systems.
Additionally, Building Operators can use this view to compile documentation for tenants
indicating that a certain “Quality of Service” was provided (e.g. room and zone
temperature within limits).
(3) The building user perspective:
This view addresses the information needs of occupants and tenants and allows the
representation of Building Performance Data of an individual zone. Additionally, users
can submit their feed-back (e.g. “I feel cold”). This feed-back data can be used for
analysis in diagnosis software (not part of BuildWise) to finally optimises the set-points of
BMS.
5.4.4.3.
IP identification, patent searches, freedom to operate
The Data Warehouse Schema, the algorithms for data cleansing and consolidation as well as
the algorithms for data loading and aggregation were identified as “IP” in BuildWise.
IDF are currently under development and will be completed by the end of July 2010.
5.4.4.4.
TTO discussion/IDF’s
UCC, CEE in collaboration with the BuildWise IDF is in the process of establishing routes for
commercialisation for this IDF, including licensing opportunities with industry parties on a non
exclusive basis. The ESB and HSG zander Ireland were identified as partners with strong
interest for commercialisation.
Centralised, consistent Building Performance Data Management is primarily required to support
the following “Use Cases”:
(1) To assist the operator of Building Management Systems (BMS) to optimise set-points
and the “operational strategy” in general (occupier of residential facilities, operator of
commercial facilities). In this case building performance data can be stored and
managed locally by the tenant, remotely by the Energy Provider or a Third Party (e.g.
Google).
The analysis of Building Performance Data and the adjustment of set-points can
contribute to Energy Savings of up to 15%.
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(2) To assist the owner or operator of BMS to identify malfunctioning or abnormal
performing systems and components, As a result, relevant maintenance or replacement
activities can be initiated.
(3) To inform and contribute to load balancing in energy distribution grids. Zone-based
sensed and metered data can be used to calculate customised energy demand profiles.
It can be jointly used to adjust the demand to “Supply Profiles” usually provided in form
of “Flexible Energy Tariffs”.
This use case contributes to improved load balancing in grid operation and is required to
manage the increasing number of renewable Energy Sources integrated in BMS and
Energy Distribution Networks.
All use cases enable businesses to provide Value Added Services to their clients. A market
analysis has identified multiple innovative Business Models including potential benefits for the
relevant stakeholders:
(a) Total Facilities Management; in this case the portfolio of “traditional” FM providers is
extended to the area of Energy Management. FM-services are usually provided as “Joint
Ventures” or “Subcontracts” between large large-scale FM-coordinators and SMEs
acting as “Service Providers” in the field. Required IT-services (e.g. Data Warehouse
Operation) are usually “outsourced” to specialised IT-providers, again in the size of
SMEs.
Both, FM-providers and Service Providers, benefit from the availability of Building
Performance Data, since they can offer consultancy services, inspections and
maintenance contracts to their clients. Additionally, all parties can optimise the efficiency
of maintenance works by compiling an advanced knowledge base about replacement
cycles, failure types, etc.
(b) Private Public Partnerships; in this case construction companies or investors take over
the “Risk of Ownership” for a fixed term (usually 15 to 25 years). Building users, usually
from the public sector, enter a long term rental agreement for the building. Part of this
long term rental agreement is a detailed Service Level Agreement. The detailed
documentation of the building performance, compiled from (wireless) sensors and
meters, becomes an essential requirement to fulfil these types of contracts but also to
optimise the “Cost of Ownership”.
(c) Energy Service Companies (ESCO); in this case either stakeholders from the
construction sector (e.g. HOCHTIEF) or from the BMS-sector (e.g. Honeywell) or from
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the Energy Sector (e.g. RWE) offer “total energy service provision” contracts. The
business model of these contracts is usually based on the assumption to share the
benefits from energy savings. Energy savings are expected from improving the
infrastructure,
improving
the
“Operational
Schema”
or
from
the
optimised
purchases/usage of different forms of energy generation and energy purchases (e.g.
combine solar thermal generation with gas boiler).
Both, the tenant and the ESCO have an essential need to understand the “Performance
Profile” in a detailed way in order to allow the optimised usage of the different energy
usage. Additionally, ESCO can offer consultancy services to their clients by analysing
the performance profiles.
5.4.4.5.
Potential licensees.
We have identified the following potential forms for licensing agreements:
(1) Data Warehouse Core (Server License)
The server application could be licensed running on a Data Warehouse Server focusing
on the compilation and analysis of the “bulk data” collected from the sensor network and
the BMS. A run-time license for the Data Warehouse is required on top of the UCCBuildWise license cost for server application.
The license should include the so called “middleware”, i.e. the interfaces to download
and upload data. These interfaces are web-based interfaces using the “SOA-paradigm”
(service oriented architecture).
(2) Monitoring Clients (Client License)
The Graphical User Interfaces (client application) are Java-based application. A Java
runtime environment needs to be installed on each PC. Usually, these Java packages do
not require any license fee.
The UCC-BuildWise Monitoring clients could be licensed for a cost below Euro 100 per
installation or could be bundled with the server license.
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5.4.5.
Networking Protocols/ Deployment Tools
5.4.5.1.
Product offering,
There are clear advantages of WSN to support building management systems, namely the
associated lower cost of installation, flexibility of a wireless solution and the unobtrusive
installation that is possible in a retrofit deployment with small wireless devices.
Although these benefits are highly desirable to the building management sector there remains
some limitations that obstruct the deployment of large-scale WSN networks including network
lifetime, Quality of Service (QoS) and reliability. Unfortunately these drawbacks are intensified
as a result of substandard design and the lack of standards based energy efficient networking
protocols.
The Industry Need:
Based on industry interaction and discussions with experts of the WSN community a number of
common problems have been identified that need to be overcome before large scale adoption of
wireless solutions can be realised, these include:
1. Indoor environments pose a significant challenge when deploying wireless devices. The
position of sensors greatly affects the performance of a network both from a sensing
perspective and a communications perspective.
2. To be cost effective WSN need to have a “plug and play” approach, they cannot require
an experienced wireless expert to design and deploy the network.
3. There are no support tools for the designer, experienced or not.
4. Lack of integration with Industry standard tools.
5. The network must last a significant period of time without changing batteries to be viable.
While trying to address the issues outlined above two specific components of the WSN lifecycle
have been recognized to present potential market opportunities for BuildWise outputs,
A Deployment Support Tool:
Current WSN deployment methods are often based on a “try it and see” approach which are
limited for use in small scenarios. Large scale indoor wireless sensor networks require formal
design, deployment and verification methodologies in order to deliver the required sensor
network Quality of Service (QoS) targets.
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The WSN Design Tool developed by CIT incorporates an accurate propagation model which
predicts the characteristics of the wireless channel parameters within the indoor environment
where a WSN is to be deployed. It also includes an optimisation algorithm which automates and
accelerates the design process with minimum user configuration. The tool can be used by a
designer of any level of experience to automatically optimise the number and position of
devices, expected link quality, network lifetime and topology layout required to meet the
application specific requirements of the WSN. Currently there are no WSN design support tools
available for indoor WSN that focus on their application to the energy management space.
Adaptive Energy Efficient Networking Protocols
IEEE 802.15.4 protocol has been identified a promising standard for WSNs due to its flexibility
to fulfil the requirements of a variety of application patterns and scenarios, by adequately tuning
its communication parameters. Although there are many research works that have employed
algorithms that adapt separately the different metrics that impact the power consumption of
IEEE 802.15.4 sensor nodes, none of them have jointly considered all of them. The adaptive
agent based power management for IEEE802.15.4 sensor networks developed by CIT is a
software component that configures these parameters during run time, without the need of
human intervention, with the aim of providing energy efficiency while fulfilling application
requirements.
As there is no other solution that considers all metrics together we can thus say that the
adaptive power management for IEEE802.15.4 based sensor networks is the first to create a
cross layered structure where all subsystems cooperate to achieve the required quality at the
lowest energy consumption. This achieves the joint optimum rather than individual optimum in
power consumption.
5.4.5.2.
Unique Selling Point
WSN Design Tool - Software support from Design to Deployment
With the WSN Design Tool, users are able to aid designers in all phases of the planning
process as shown in Figure 48. This approach ensures that the user considers the impact of the
deployment environment, application requirements, device types, etc on network performance.
The design tool can also be used to evaluate network expansion or the viability of new wireless
applications with minimal experience required.
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Figure 48 - WSN Design Process
The main advantages of the design tool can be summarised as follows:
9 Can be used by non-experts to design high-quality indoor wireless sensor networks.
9 Accelerates and automates the design, deployment and verification processes in WSN
design.
9 Imports AutoCAD and Industry Foundation Classes (IFC) standard drawing formats to
be compatible with industry standards.
9 A design can be created prior to a building even being constructed.
9 Includes Accurate Propagation Models and Novel Optimisation Algorithms
9 Can be used to evaluate network expansion or the viability of new wireless applications.
9 Non-proprietary – can be used with any wireless sensor network hardware system.
Adaptive Power Management Protocol for improved network lifetime
Although planning tools are essential to get a good baseline pre-deployment it is not possible to
consider all possible influences on how a WSN performs, for example a new wall is added, a
WiFi network is installed that may cause interference. However, sensor nodes are typically
configured once and deployed and hence do not lend themselves to be resilient against
unknown interferers or changes in the operating environment. Therefore an adaptive networking
protocol is required to ensure reliable operation of the WSN once deployed regardless of
environmental influences.
Much of the current research considers the optimization of individual parameters of
IEEE802.15.4 standard to improve battery consumption such as setting operating channel and
transmit power, with some success. However there are a large number of metrics, often be
conflicting therefore the optimization of one local parameter will not result of a global operational
optimal for the entire network particularly in large scenarios.
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By employing the adaptive agent based power management for IEEE 802.15.4 networks that
considers a number of these parameters together during the operation of the network, an
organisation will have a robust and power efficient wireless sensor network without the need of
a wireless expert to configure the IEEE 802.15.4 parameters to its scenario and application
requirements. Therefore the developed technology has the potential to interest any company
which needs to design or use a WSN within a building.
The main advantages of the Adaptive Agent Power Management Protocol can be
summarised as follows:
9 Offers a protocol that can achieve data rates that can cope with the high activity periods
of a WSN.
9 Protocol allows for underlying wireless channel errors to be managed.
9 Employs radio chips with multiple data rates to increase data rates and hence lower
energy consumed.
9 Offers a cross-layered structure which combines all of the current “state-of-the-art”
approaches to ensure that all subsystems cooperate to achieve the required QoS at the
lowest energy consumption (up to 50% less).
9 Reduces the total time and cost of the WSN deployment, operation and management
phases.
5.4.5.3.
IP identification, patent searches, freedom to operate
Patent search resulted in the following patents:
US20080280565 Indoor Coverage Estimation and Intelligent Network Planning
US2002006799 Method and system for analysis, design, and optimization of communication
networks
US20030014233 System for the three-dimensional display of wireless communication system
performance
The first two US patents protect the key intellectual property of Wireless Valley Communications
CAD tool SitePlanner and LANPlanner (now Motorola).
These patents only pertain to radio propagation modelling in indoor environments and how this
can be used for performance assessment of Wireless Local Area Network designs. The
developed tool is based on a different propagation model and approach, there is no conflict
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AU4103801 & WO0193617 System for indoor cellular networks automatic frequency planning.
These two patents protect intellectual property with respect to indoor cellular network frequency
planning, which is an extension of this key planning aspect of cellular systems into the indoor
space. The patents subject area relate to a feature of the proposed work but will not cause a
conflict as the envisaged optimisation approach is fundamentally different to the one protected
by the two patents. The outcome of the initial patent search has found there is no IP impediment
found that could conflict with proposed solution.
5.4.5.4.
TTO discussion/IDF’s
Meetings with relevant industry were arranged through the CIT TTO and two IDF have been submitted
covering the Design Tool and Adaptive Network Protocol. The TTO officer for these IDF’s is in the
process of establishing routes for commercialisation, including licensing opportunities with
relevant industry parties on a non exclusive basis.
5.4.5.5.
Market Analysis and Market Benefit,
There is very little tool support for WSN in indoor environments, the majority of the wireless
planning tools focus on the deployment of Wireless Local Area Networks (WLAN) or WiFi. While
WiFi is in a different market segment, it can nevertheless provide some indication on the market
potential for WSN design and deployment support tools.
The market for WLAN equipment is growing rapidly. According to a WLAN Market Share Report
available at (WLAN 3Q08 WLAN Market Share Report, Analyst: Victoria Fodale, December
2008) showing figures for 3Q08, worldwide revenue for the WLAN market increased by 15.1%
Year-over-Year (YoY), up from $1.17 billion in 3Q07 to $1.24 billion in 3Q08. This indicates that
more and more businesses are installing and becoming reliant on wireless networks as a critical
business asset. Currently most organisations have little expertise in designing and optimising
wireless networks. Purchasing expertise is expensive, for example for a design of approximately
8000msq for a department in CIT campus was quoted as a daily rate of €1000 with a minimum
three day design. Stand alone WLAN planning support software such as AirMagnet costs in the
region of €5,000.
There are three market categories/routes that the Design tools and protocols can fall under
including wireless sensor network hardware providers, wireless application providers and
wireless sensor network design and management companies.
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Hardware providers that currently have a set of management tools can utilise the developed
optimisation algorithms to extend their current product offering.
Application providers such as energy management applications can utilise the tool to tailor a
network to their specific application requirements.
The Design Tools can provide advanced capabilities to wireless network design companies
by offering an affordable service to ensure a robust network that offers reliability, capacity and
performance.
5.4.5.6.
Potential licensees.
The IP of the design tool has been captured through an IDF currently being processed by the
CIT TTO. On the basis of discussions with industry partners, various networking events,
demonstrator activities and attendance of conferences and workshops, Industrial partners
potentially interested in licensing the software components described above include such
companies as Cylon Controls, EnOcean, Wirelite Sensors, UTRC, HSG Zander, and Salto
Systems Ltd. Many of these companies see design support tools as an integral part of driving
the uptake of their innovative wireless technology solutions. All of these are being actively
approached by the CIT TTO office.
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5.4.6.
Wireless Sensing Platforms
5.4.6.1.
Product offering,
Based on industry interaction and definition by industry contacts within the BIAG – the
specification requirements for wireless sensing platforms in the built environment have been
identified.
Market opportunity
ƒ
System Specification: - BIAG specified form factor and sensor requirements for
integrated BEM platform.
ƒ
Low Maintenance/Long Lifetime: - Low power design and potentially energy harvesting
incorporated in ruggedized reliable platform.
ƒ
Low cost: - Need to apply high volume DFM, DFT & DFC principles. Reduce to smart
card or miniaturized cube form factor.
ƒ
Ruggedized: - Minimise number of components and interconnect. Miniaturization and
integration research strands will help this.
5.4.6.2.
Unique Selling Point
BuildWise – Sensors/Meters interfacing layer for Wireless network deployment in Building
environment
The new designed flat profile mote (called BEM2) is the second generation of the 25mm2
stackable version mote (called BEM1). The board has been designed to target the various
wireless sensors and meters monitoring in building environment and perform wireless
communication system for communicating with neighbouring motes. To be compatible with a
small form factor standard BMS installation “look and feel”, the dimensions of the new wireless
sensor board are 45.4 x 81.0mm which is slightly smaller than a credit card standard format (54
x 85.6mm). The new mote consists of number of sensors, Meters interfaces and extra flash
memory that can be used for remote node re-programming. In addition to the sensing capability,
the system can be used as an actuator to control the operation of any AC/DC load with high
load current through an external relay. The mote can be powered using batteries or through
USB connection which can be used for battery charging. The different on-board sensors can be
switched on/off by the Microcontroller to minimize and handle the system power consumption
under different operating conditions. The new mote has been interfaced to water flow meter
allowing full control of the meter and forming a novel wireless integration according to the
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attached patent search. In addition the incorporation of all the following functionalities on one
single low form platform makes the mote a novel tool to be used for various applications in
building environment Wireless Sensing and Control.
•
On-board sensing and actuation according to industry recommendations
•
Bidirectional RF communication (Zigbee/802.15.4 CC2420)
•
USB Programming capability and Batter charging circuitry
•
Sensors/Meters data processing handling (Atmega1281)
•
Powering ON/OFF different on/off-board sensor and Meters units
•
Embedded C and TinyOS code programming
•
External connection to other Sensors, Meters and Relays (actuators)
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b. How it works and commercial applications (short paragraph)
The BEM2 design is based on the combination of the Atmega1281 (processor) and Zigbee
CC2420 transceiver (RF). The two units can be full controlled and configured under the control
of an embedded application. The different on-board sensors are communicating with the
microcontroller through either analog or digital interfaces. The analog sensors readings are
calibrated and processed before the date sent wirelessly to the base station. The node has the
capability of remote re-programming using the extra flash memory unit. The node can send data
and receive commands to perform actuation and control the operation (on/off) of other external
devices. Also the layer can be interfaced to any device that uses Modbus RS485 protocol like
Electricity meter and water flow meter.
In case of the water flow meter, commands can be generated and sent by the wireless mote to
configure all the device settings and start receives the required data. Such formation can be
used as a heat meter as well by incorporating the interface readings of the water pipe
temperature sensor as shown in the diagram below. The on-board resistive interface can be
used to connect and obtain readings from any type of standard Pt100 temperature sensor. Both
water flow rate and temperature data will be processed/calibrated by the microcontroller and
used to compute an accurate value of the water heat.
It is designed to consume low power and performs wide range of sensing, actuation and remote
re-programming in a developed Wireless network. In addition the technology of using water flow
meter as wireless device is considered to be novel and provides dual applications in the
Building environment.
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5.4.6.3.
IP identification, patent searches, freedom to operate
Patent No
Date
Source Title
7,437,596
October 14,
2008
US
Self-healing control network for building
automation systems
7,360,413
April 22, 2008
US
Wireless water flow monitoring and leak detection
system, and method
7,306,008
December 11,
2007
US
Water leak detection and prevention systems and
methods
6,941,193
September 6,
2005
US
Sensor system for measuring and monitoring
indoor air quality
6,874,691
April 5, 2005
US
System and method for energy management
US2008242314
(A1)
02/10/2008
US
PORTABLE WIRELESS SENSOR FOR
BUILDING CONTROL
WO2008080745
(A1)
10/07/2008
EU
BUILDING EQUIPMENT CONTROL SYSTEM
US2007241928
(A1)
18/10/2007
EU
Wireless Remote Control
US
Jul 28, 2005
2006/0063522 A1
US
Self-powering automated building control
components
CN2864844 (Y)
31/01/2007
China
Automatic meter-reading wireless signal
transmission device for water meter, gas meter
and electricity meter
CN2763911 (Y)
08/03/2006
China
Wireless transmission type multi-function threephase electricity meter
5.4.6.4.
TTO discussion/IDF’s
Based on the Product offering and associated identified market (customer) requirements an
Invention disclosure form (IDF) has been developed in consultation with UCC Technology
Transfer Office (TTO). The case manager for the BuildWise IDF is in the process of establishing
routes for commercialisation for this IDF, including licensing opportunities with industry parties
on a non exclusive basis.
5.4.6.5.
Market Analysis and Market Benefit, (Frost & Sullivan 2006)
Wireless sensors are required in HVAC primarily to reduce installation time, increase profit,
maintain the original architecture, and increase the system performance. Issues such as floor
plan changing, architecture, and bid risk are now easily overcome using wireless sensors. The
key areas where wireless sensors are of extensive use in HVAC are in:
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ƒ
Flexibility
ƒ
Installation
ƒ
Architecture
ƒ
Bids
Flexibility is considered as the most important benefit in using wireless sensors for HVAC
applications. System performance and customer comfort can be optimized by locating/
relocating the sensors. Evolving floor plans can be easily adapted to through the wireless
sensors. Customer preferences/contractor needs in both retrofit and new constructions are
easily addressed using the flexibility offered by the wireless sensors. With no wires to sensors,
installation in HVAC is quick and easy. Installation in HVAC is made quick as there are no
obstacles that usually slow down the installation. This is due to the elimination of the wire that
runs from the controller to the sensor. A quick and easy installation in HVAC applications
enables fast track schedules to be met with less interruption to the working environment. Thus a
quick and easy installation results in a faster job completion, thereby increasing the customer
satisfaction. Architecture is a crucial factor to be considered, especially during the up gradation
of a HVAC system. Problems encountered with marbles, hardwood walls, firewalls, solid
ceilings, and specialized constructions can be solved using the wireless sensors. Time and
costs associated with labour and asbestos can be decreased significantly. Installing /mounting
wireless sensors does not require penetrating existing walls and therefore the bids for wireless
installations in HVAC are more as the risk involved is less. Coordination with the trades is easier
as fewer unexpected conditions are encountered while installing wireless sensors. Thus easy
installation, flexibility, adaptability to changing floor plan, and predictability to install and support
makes the wireless sensors well suited for HVAC. Wireless sensor networking capabilities are
required in building automation for energy management, HVAC networking, and guest room
controls in hotels. Existing devices can be wirelessly networked by RS-485 protocols thereby
broadening product offerings and capitalizing on new markets and opportunities. Expensive
installation and maintenance costs can now be reduced as sensors and actuators can be
wirelessly controlled and monitored in building maintenance systems. The RS-485 cables that
were used to connect the controller with the thermostats have been replaced. Building access
control is one area where there is significant potential for the wireless technology to be used. In
building automation there are a number of applications that can take advantage of the wireless
sensors. Mostly in retrofit applications for the existing buildings and access control is absolutely
one of those. Wireless sensors are used in large buildings and factories to monitor climate
changes. This is done by deploying temperature sensor nodes and thermostats all over the area
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of the building. Wireless sensors are also used for vibration monitoring to avoid any damage to
the building structure. The ability of the wireless technology to reduce costs of installing data
acquisition and control systems in building automation is a key driver for its growth besides its
mobility. Installation costs consume about 20.0 percent to 80.0 percent of the cost of a sensor
point in a HVAC system. Low cost wireless sensors reduce the overall cost of the sensor and
increase the usage of the sensors. Improved monitoring and control, which is a key requirement
for an effective and efficient building operation is thus achieved by deploying more such low
cost wireless sensors. Wireless sensing of indoor conditions have now become inevitable
promoting more localized and personalized control of indoor climates. Deployment of the
wireless sensors would be based on cost advantages and the flexibility to relocate thermostats
and sensors. Wireless communication in building automation can be accomplished using
various communication protocols. Cost plays an important role in the usage of these for data
acquisition for HVAC monitoring, diagnostics and control. Bluetooth and 802.11b have been
widely accepted in this regard. By 2012 the revenues from this end-user segment are expected
to increase to a high of $25.7 million at a compound annual growth rate (2005-2012) of 22.1
percent.
5.4.6.6.
Potential Licensees.
On the basis of discussions with our industry partners in the BIAG, and the various networking
events, demonstrators activities and networking events described in this document, Industrial
partners potentially interested in licensing the platform based technology described in the IDF
include such companies as Cylon Controls, Wirelite Sensors, UTRC and Glen Dimplex, and
these are being actively approached by the UCC TTO office.
Wirelite's sensors have agreed to license the low power consumption hardware which as
resulted from BuildWise associated research within the Smart Buildings Cluster.
The TTO office at UCC intend to
1 Capture all the IP in detail in IDFs and log them onto the TT system
2 Create a brochure of each item of IP
3 Present the IP to the industry partners initially for licensing (likely to be on a non-exclusive
basis as it is platform based enabling IP rather than specific application IP) and subsequently to
the wider community.
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5.4.7.
Summary of Commercialisation Activities for the Consortium
Commercial
Strategic alliances
opportunities
PS-Tool
Patent
/
Product / Service
Other
License
AEC3 (BIM standardisation)
In
Product
*beta
Enerit (ISO 16001 management)
discussion
version*
(May
IBM - Green Sigma Product
with
2010)
Cylon Controls-active energy product
TTO
NUIG
Possible service to
Wirelite (Data structuring)
follow
Energy
Intelligent use of energy information
In
Product
*beta
Desktop
Management
and innovative business models
discussion
version*
(May
energy
web
Glen Dimplex
with
2010)
developed
ESB
TTO
Possible service to
industry
follow
Vector-FM, Wirelite, Intel)
service
(DW)
WSN
design
tool
UCC
Salto
In
Product
“beta
EnOcean
discussion
version”
providing
UTRC
with
manual
and
Wirelite
TTO
CIT
automatic
HSG Zander
interfaces
for
management
with
selected
partners
(Cylon,
design
capabilities
Arup
Low-power
Analog Devices
In
based wireless
Decawave
discussion
of
sensor network
Benetel
with
currently under way
protocol
UTRC
TTO
with
IP
suite
adaptive
agent
based
Porting and tuning
CIT
implementation
for
TinyOS
EuroTech Ltd. (Innovation Partnership
Agent
Project through TEC Centre)
validated
2.x.
approach
power
computer
management
simulation.
through
Energy
SMEs:- Resourcekraft, Wirelite, Cylon,
Innovation
“Low
Management
Episensor, FMC tech, Selfbuildpartners,
Partnership
application specific
coordinated with EI (Sean
Platforms
Excelsys, Powervation, Chipsensors,
under way
BEM
Burke)
MiPower, SensL, Western Automation,
with
implemented (~100
3 Artemis/Catrene Projects
Nualight, Ei Electronics
Wirelite
€)
approved/under evaluation
MNCs:- EMC, Moog, TI, Glen Dimplex,
In
IBM, Intel, Texas Instruments, Analog
discussion
Devices
with
Discussions by phone
TTO
cost”
board
SME
program
event
UCC
SMEs:- Ikon Semi, Ircona, Litewave
5.5.
The Business Plan– How BuildWise is Adding Value to Ireland Inc
The BuildWise consortium is endeavouring to add value to Ireland Inc through its activities in the
EI sponsored program BuildWise through a number of different mechanisms. Through
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conventional commercialisation routes such as endeavouring to Investigate Commercial
Opportunities for BuildWise “Products” through development of Intellectual Property with
associated, Licensing Opportunities, and the identification where appropriate of Startup
Opportunities with the developed technology.
The consortium additionally sees mechanisms which add value to Ireland Inc, particularly in
these economic times through the development of exports and protection of Jobs, support of
existing industry and SMEs attraction of inward investment to support and develop indigenous
Irish industry. These include the development of further Synergistic Spin off funded projects,
through the Enterprise Ireland Commercialisation Fund and Innovation Partnership scheme, as
well as Artemis/Catrene/ENIAC programs.
The BuildWise consortium is also endeavouring to bring Irish companies into European
networks and markets supported by EU funding (Clusters of SMEs) and associated Networks of
Excellence (NOE’s).
The BuildWise Business planning activities are also endeavouring to develop partnerships
between Irish SMEs and Venture-Capitalists as well as the clustering an networking activities
attempting to bridge the gap between who has the money and the small SME’s who the ideas
The following section summarises the key highlights of the current and recent commercialization
activities of the Smart Building cluster and their relevance in relation to the ambitions stated
above. (Further examples are listed in the accompanying table). It is envisaged that many more
similar stories will emerge from the continued support of the BuildWise commercialization
activities.
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5.5.1.
5.5.1.1.
Wirelite Sensors
Innovation Partnership
Energy demand management (EDM) solutions typically offer electricity bill savings in the region
of 8-10% by installing sensors and meters to gather usage information, providing the user with
energy usage patterns. However to maintain such savings on an ongoing basis needs regular
vigilance, monitoring the data on a regular basis and modifying the algorithms accordingly.
Additionally there is a further potential to offer savings in the order of 20-30% if actuation and
control systems can be integrated into the EDM cycle.
Wirelite Sensors Ltd has recognised a market niche to offer such EDM solutions but requires a
wireless sensing and actuation platform to minimise deployment costs, maximise ease of
installation and accelerate return on investment savings. This platform would also provide a
higher degree of flexibility in terms of the sensor/meter placement and in many cases resultant
accuracy. Small to medium supermarkets, cold store rooms, hospitals and process
manufacturing machinery optimisation are some of the key niche application areas for Wirelite
Sensors. Supermarkets such as SuperValu are a particularly good model as they typically
comprise a customer/premises owner who has a relatively large utility bill but also has the
autonomy to make local decisions regarding capital investment and the day-to-day management
of the facility.
To achieve this, Wirelite Sensors has partnered with Tyndall to develop the hardware platform.
The use of wireless technology reduces the installation cost but for an EDM deployment to be
sufficiently attractive for a potential investor the payback period should be in the region of 12-24
months.
The introduction of WSN motes with actuation and control capability further improves the energy
and cost saving potential by enabling the WSN motes to interface with energy loads. This is a
critical function required to enable sufficient savings to justify the WSN EDM deployment.
Based on discussions within the BuildWise umbrella, the relationship with Tyndall started in
2008 with a Feasibility Study, successfully trialling the existing Tyndall mote technology at a
hotel premises, adding an interface layer for inter-operability between Wirelite’s smart meters
and EDM software platform.
On the basis of this an Innovation Partnership was developed and approved by EI in 2009 to
develop as commercialized version of the Tyndall WSN mote platform to the following outline
specification
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•
70% reduction in mote hardware cost
•
sensor/sub-meter interface layer for lighting, HVAC and refrigeration
•
actuation and control capability
•
Zigbee compatibility to enable inter-operability and ease of installation with a large
numbers of existing devices and systems
To date the 1st prototype design has enabled the installation of the EDM platform into (i) a
supermarket premises to optimise electricity costs and (ii) a manufacturing plant to monitoring
and optimise the operation of some process machinery.
For the supermarket a sophisticated set of control algorithms was adopted as follows:(i)
scheduled control (based on optimised tariff selection)
(ii)
active control for non essential refrigeration
(iii)
active control for lighting
(iv)
active control for HVAC
(v)
active control for essential refrigeration
These algorithms comprise a key differentiator Vs many other wireless EDM solutions being
offered. Wirelite has already attracted significant VC and seed capital investor interest on this
basis. The 1st supermarket deployment is near completion with most of the abovementioned
control algorithms recently in place.
Tyndall has recognised that is not enough to simply supply hardware and pass over to Wirelite,
Tyndall must also be intimately involved in the architecture specification, system integration and
commercialisation of this hardware such that a commercial realisable solution is being offered,
maintaining logs of lesson learnt, creating checklists to help be better prepared for future
deployments, etc. Wirelite enjoys a double impact as it is being used both as a source for
understanding the technical/practical/logistical challenges associated with the deployment as
well as a commercial showcase to demonstrate to potential investors what can be done.
Based on early results (monthly energy billing reports) it appears that savings of the order of
around 20% are already realizable, very promising, but a longer timeframe is required to verify
that such savings are sustainable.
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5.5.1.2.
Wirelite - Synergistic Funding Leveraged from BuildWise
As an extension of their interaction with the BuildWise Consortium and the resultant innovation
partnership activity, Wirelite is also sponsoring an IRCSET funded UCC/Tyndall PhD student in
the area of 3D visualization for energy demand management. The idea is to create quickly
configurable and usable 3D models than can help users better understand energy profiles (e.g.
temperature, heat, cold air, lighting, etc) and predict the extent to which savings can be made in
advance of the deployment. The model can also be used to optimise the number and placement
of the required wireless sensors. This will be become a very powerful tool to persuade
customers as well as capital seed investors to invest in Wirelite through giving return on
investment predictions before any customer capital is needed for a given deployment as well as
providing user friendly user interfaces once the deployment has been installed.
5.5.1.3.
Wirelite - Licensing of BuildWise Technology
Another related UCC/Tyndall activity is the signing of a licence agreement with Wirelite Sensors
based on a UCC developed multi-hop WSN algorithm from the related research undertaken by
Prof. Cormac Sreenan, Dept. of Computer Science. This uses a flooding technique to improve
the reliability of the WSN infrastructure. This is particularly valuable for the reliable transmission
of critical data and execution of actuation and control commands. This patent is also valuable in
securing Wirelite’s entrance into the US market.
5.5.1.4.
Wirelite Industry Engagement
All of these combined programs are enabling Wirelite to bridge the ‘valley of death’ between
high technology HPSU and fully commercialized profit-making and growing SME. Wirelite plan
to grow from 2 to 40 people with €10M annual revenue within the next 3 years on this basis.
(This ‘valley of death’ is a much overlooked area where industry and research should engage
more actively and is one of the critical key areas where further commercialization of the outputs
of BuildWise must be seriously considered).
Wirelite has been a very pro-active industry partner in BuildWise and looks to be set to reap the
rewards from such engagement. Discussions are also underway to explore opportunities in EU
funded projects and in industry-lid clusters in energy efficiency (ref. ‘engine for innovation
process flow chart’ later in this document).
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5.5.2.
HSG
HSG Zander is the largest facility management company in Germany. HSG is an established
partner in the SFI-funded ITOBO project and, through this activity, has become aware of the
related Smart Building cluster partners and activities (BuildWise, ITOBO, NEMBES, etc).
HSG Zander can clearly see the value of being in close proximity to such a cluster and is
working on a proposal with IDA to move beyond their existing small Dublin-based premises to
establishing an Irish R&D entity. One of the main activities of this group will be the development
and establishment of a technical and commercial infrastructure, based on a successful business
model, for the retrofit and management of wireless sensors and actuators for clients of HSG
Zander to enable energy efficiency and cost savings in the operation of commercial buildings.
5.5.3.
UTRC
As part of the UTRC IDA proposal, UTRC Ireland will engage in direct funded research activities
with Tyndall, UCC and CIT in the development of sensing technologies in the areas of energy
management, security and networking. In particular the CIT developed design tool will form part
of the collaboration focussing on localisation in wireless sensor networks. This presents an
opportunity to license the technology to UTRC to enable UTRC to use it together with the
technology developed as part of the direct funded technology development.
5.5.4.
Self-Build Partners (SBP) & Fewer Harrington Partners (FHP) – G House – Irish
SME Partnership
SBP is a recently established Wexford-based company specializing in providing a one-stop
shop for people planning to build their own eco-friendly house. They offer a timber sealed-panel
construction technique for which they hold the Irish rights.
FHP is a Waterford based architectural firm that is co-developing the passive house concept
(‘G-house’) with SBP. They have also been working together on a similar concept for next
generation low CO2 footprint schools.
Over the past few months, the Smart Building cluster has had several meetings with these 2
Irish SMEs to explore collaboration opportunities based on their low CO2 footprint ‘G house’,
collaboratively designed by them.
They have been discussing their plans with a range of potential industry partners (e.g. Velux,
Glen Dimplex, Kingspan) and the establishment of a demonstrator of this technology for both
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commercialization and research activities. On the basis of this a draft proposal outline is being
prepared by the BEM cluster, ref extract below:========================================================
The idea behind this concept is to provide a stable test-bed for a prolonged period for research
and industry partners to try out
(i) energy models
(ii) building envelope (e.g. walls, floors, windows, doors, insulation systems, etc) and energy
systems (e.g. solar panels, HVAC, ground floor heating, electric heaters, LED lighting, etc)
(iii) ICT infrastructure to enable the enable the most efficient operation of the energy
systems (WSN motes, electricity, gas, water meters, CO2 sensors, presence detectors, etc)
This helps industry overcome 3 significant barriers:(i) How to model and physically test energy efficient systems
(ii) How to gather data over an extended period in a stable environment against a specified norm
(built according to standards and/or a reference passive house)
(iii) Get hands on experience in addressing the challenges and realizing the benefits of energy
systems and related ICT infrastructure.
Initial demonstrator
This will comprise the use of 2 passive houses from SBP/FHP, one as a reference model and the other
as the variable model. This will focus on systems (HVAC, heating, cooling, lighting, wireless sensing) to
allow direct comparison Vs the reference and gather evidence of the individual and cumulative effects of
energy efficient techniques over a sustained period.
Role of research partners:Provide systematic calibrated energy models to predict energy usage behaviour in a house and estimate
improvements in energy efficiency (NUIG/UCC)
Provide ICT infrastructure (WSN motes, meters, routers, RF deployment tool) to enable the wireless
retrofit of both houses and capture of energy efficiency behaviour. (TYN/CIT)
Perform initial installation of WSN infrastructure and support as required. (TYN/CIT)
If a suitable 'non-passive' reference site can be made available the researchers can also model this and
provide ICT infrastructure.
Role of industry partners:-
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Provision of 2 reference physical test sites (reference model) and experimental model)
Provide data storage and resources to run and gather data during the deployment
Install various energy efficient systems.
Longer term demonstrators
It is envisaged that the demonstrators be extended to facilitate experiment using different materials and
infrastructure, variation in design of windows, sealed panelling, insulation material and system, blinds,
shutters, etc. This benefits the industrial partners in providing unbiased evidence of improvements in their
latest materials as well as giving the research partners the opportunity to extend further the energy
models based on (IFC) standards and correlate them against real-life results.
Outcome/benefits/vision
Energy efficient solutions can only happen through collaboration between the research and industry
partner to examine the entire systems and devise 'end to end' solutions. This ties in extremely well with
the vision the recently announced IERC at Tyndall/UCC and based on feedback to date this would be a
critical applications research strand to help address the challenges listed above. The technologies have a
'home' and will strengthen the interaction between research and industry partners.
It is clearly premature to determine the outcome of these discussions and the level of interest by
other partners but is a good example of the type of collaboration opportunities possible and how
they can be linked to activities such as the IERC. It also demonstrates the continued relevance
of WSN technology and the need to engage in technical and commercialisation activities to
accelerate the commercial update of this, establishing Ireland in a leading role. One meeting
has already involved Velux (Ireland and UK representatives) and they are very interested in
learning more both about the IERC as well as the G house proposal as well as creating a link
between Velux corporate (Denmark) and the BEM cluster. Others are already involved in similar
activities (e.g. Wain Morehead (Passivhaus) & Velux (Active House)) but none of this is coordinated at a national level and no synergies are being extracted
5.5.5.
Irish Industry Engagement
As detailed in section 3, the BuildWise consortium activities in the areas of engagement with
Industry include Direct engagement with Irish and foreign companies, Industry clustering and
Interacting with Irish industry in the context of leveraging external funding e.g. FP7 and other EU
funding opportunities.
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5.5.6.
5.5.6.1.
FP7 positioning of WSNs in future EU calls, industry engagement etc.
E4U
E4U – ‘electronics enabling efficient energy usage’ – is an F7 roadmap document recently
completed by a Eutema-led consortium that involved Tyndall as a project partner.
www.e4efficency.eu.
The idea behind the study was to determine opportunities for the exploitation of power
electronics and control to enable energy efficiency savings.
Tyndall contributed to each of the segments reviewed (e-mobility, electrical drives, building and
lighting, power supplies) and led the investigation into ‘energy in buildings and lighting’. WSN
technology is considered to be a significant sub-set of power electronics technology in this
space as it relates to wireless sensing, actuation and control of energy loads in buildings.
As well as the releasing the report, a series of case studies was presented including one based
on deployment in a newly built German hotel using a Siemens-based control system illustrating
a return on investment within 3 years. For existing buildings WSN technology would play a
critical ingredient in retrofitting such technology and the payback period is expected to be
shorter (lower installation costs + greater energy savings – old buildings will be less efficient).
As part of this study, the potential for the further exploitation of power electronics technology to
improve energy use in buildings, not only from the direct technical contributions but also the role
of power electronics in clusters such as energy efficient lighting, data centres, electric vehicles,
etc was outlined and the need for stakeholders from various sectors such construction, power
electronics, energy, computing and ICT to work together and solve problems holistically.
It was also clear from the study that there is a lack of engagement by the power electronics
community in developing strategic research roadmaps in energy efficiency so a proposal was
made in the E4U roadmap for a power electronics orientated ETP (European Technology and
Innovation Platform). An industry-led version of this has already been started by ECPE
(European Centre for Power Electronics), one of the consortium partners.
The group (represented by Tyndall) also presented the E4U story at an EC workshop on ‘energy
positive neighbourhoods’ ELSA (European Large Scale Actions) in Sept 2009 that will ultimately
lead to E4U contributions to future FP7 and FP8 inputs, particularly in the areas of ICT and
energy.
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Ireland has a key role to play in this ‘energy efficient buildings’ area and several players
involved in programs such as BuildWise and ITOBO are seeking collaborative engagement at
an EU level to be more pro-actively involved in such projects. This also links very strongly with
the IERC (Irish Energy Research Centre) strategic initiatives. The outcome of these efforts is
the increased engagement by Irish research and industry partners in energy efficiency projects
as well as their involvement in defining content in future EU calls. In terms of EU engagement
one recent success has been the ME3Gas Artemis FP7 project (ref below) , securing both
national and EU funding for Arup, Resourcekraft and Tyndall as well as spring-boarding their
engagement with new partners to an EU level.
5.5.6.2.
FP7 Genesi
The aftermath of too many dramatic events involving public structures and private buildings
collapse makes imperative to ask ourselves whether anything can be done to mitigate their
effects or avoid them and save the lives taken as a result of their occurrence. Wireless sensor
network (WSN)-based systems for structural health monitoring could be the answer to this
crucial question were they able to provide long lasting monitoring and robust and reliable data
delivery as requested by increasing safety demands. This is unfortunately unavailable today.
The GENESI project proposes research addressing all the critical barriers and challenges that
prevent the application of WSNs for monitoring structures, buildings and spaces. In particular,
by combining new hardware and software design, the GENESI will produce systems for
structural health monitoring that are long lasting, pervasive and totally distributed and
autonomous, new wireless sensor nodes will be build that are capable of achieving virtual
infinite lifetime through a well-balanced combination of cutting edge technologies, such as
energy harvesting from multiple sources, the first small factor fuel cells, low-cost radio triggering
for minimizing idle energy consumption and algorithms for smart interference management.
New software will complement the GENESI hardware in the quest of long lasting system lifetime
by taking into account the “when” and “how much” of energy availability. At the same time, end
user requirements will be met according to a newly defined application driven Quality of Service
concept. Novel task allocation algorithms, cross-layer protocol stacks, situation awareness and
context discovery mechanisms complete the definition of a system that addresses the major
challenges of the ICT theme of FP7. Finally, involving end users directly into the research cycle
as key players, GENESI is poised to address realistic societal needs while fostering technology
transfer and market exploitation.
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5.5.6.3.
FP7 Artemis ME3Gas
ME3Gas is an Artemis FP7 funded project led by Gas Natural in Spain and involving 17
partners from Germany, Spain, Ireland, Italy, Sweden and Slovenia. The project has 2 visions:(i) develop an open source middleware platform with energy context awareness to enable
energy efficiency savings
(ii) develop next generation smart gas meters
Tyndall’s role in the project is to lead the work package activities in the area of wireless sensor
network hardware, middleware and business GUIs and work closely with other partners in the
deployment and system integration of WSN hardware in various commercial and residential
pilots. Tyndall has also brought Irish partners, Arup Cork, and SME Resourcekraft Limerick, who
are using the project to develop/increase their core competence in wireless actuation and
control and business GUIs respectively.
Resourcekraft Quote:“By engaging in this program, ResourceKraft stands to achieve a quantum leap in its
understanding and use of state-of the art business middleware as it pertains to energy. We also
seek the opportunity to influence the roadmap of the MEEE platform in a direction that is
compatible with its goals in the Energy Cost Control Systems (ECCS) sector. This is also a
great opportunity to network with other groups actively working in this area and help to work
together, combine technologies to devise energy efficiency solutions and help them find new
market opportunities at both national and European levels. The serviceable market for Energy
Cost Control Systems (ECCS) is over 300,000 businesses in the UK and Ireland alone. This
project provides ResourceKraft with significant opportunities to accelerate its growth by
targeting the higher value enterprise customers across Europe as a whole, and later the United
States.”
Arup quote:“Key advantages for Arup in being involved in the ARTEMIS MEEE Program include:
•
Enhancement of our design product in relation to energy systems, alternative energies,
automation of environmental control systems and integration with fenestration and facade
systems
•
Further development of specialist in-house engineering expertise to leading edge, best-
in-class levels, particularly for key staff in the area of energy monitoring, actuation and control.
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This will also improve our understanding of the broader stakeholder requirements and their
influence and scope in optimising energy efficiency in buildings.
“Providing us with a competitive edge which allows us to further export our skills to Europe and
beyond. Currently, fees generated by work outside of Ireland ranges between 5-10% of annual
turnover. Over the next 2-3 years we plan to increase this to 10-15%.”
This is a great example of the value that engagement in such projects brings to Irish based
industry partners.
All of this has arisen from networking and engagement directly or peripherally in collaborative
efforts such as BuildWise, not only focusing on the technical contributions but also the
networking and project management activities that evolve from such engagement.
5.5.6.4.
FP7 ENIAC funding
Several WSN related ENIAC funding opportunities were identified in 2010 and Irish partners
found: - (further details available if required)
(a) ERG - Energy for a green society: from sustainable harvesting to smart distribution. equipment, materials, design solutions and their applications – ST Microelectronics led
consortium - Tyndall, Solarprint and FMC tech involved in outline proposal submission, full
proposal under consideration
(b) SMARALD – smart networked and control home and office appliances– Infineon led
consortium, Tyndall and Intel involved in project outline submission Apr 2010, full proposal
under consideration
(c) Air4Us - Air Quality Sensors-Systems for Energy Efficiency and Healthy Lungs- Philips led
consortium, Tyndall and Chipsensors involved in project outline submission Apr 2010, full
proposal under consideration
5.5.7.
SME Clustering - FP7 SME Workshop
In Oct 2009 Tyndall and EI co-ordinated an FP7 SME workshop at Tyndall. The purpose was
(i) to inform SME of the funding opportunities within FP7,
(ii) to establish opportunities for SMEs to collaborate with other Irish and EU SMEs as well as
Irish researchers
(iii) to stimulate networking and clustering amongst the SMEs and research partners
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(iv) to offer networking and project management support to the SMEs to help them secure
funding and find project partners.
Over 15 SMEs attended the event (listing available) and several one-one and multi-party
meetings were facilitated (e.g. a meeting between Nualight, Excelsys, Wirelite and Tyndall to
explore opportunities for clustering in energy efficient lighting). Since this event Resourcekraft
have already secured funding in FP7 ME3Gas and FMC tech and Solarprint are involved in FP7
ENIAC proposal submissions. Many more examples are expected to emerge in the next 6-12
months directly or indirectly from this and related activities.
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5.5.8.
Potential Industrial Opportunities for further exploitation
Initiative
Next steps
Smart Building cluster role
Potential Impact
Wirelite
Continue
Innovation
Create opportunities for Wirelite
€10M, 40 people SME by 2013
partnership
partnership + IRCSET.
to participate in large scale
Involve Wirelite in many
deployments and clusters
opportunities below
SBP/FHP
Develop
partnership
proposal
G-house
Funding support for initial WSN
‘Magnet’ and showhouse for
deployment
industry to trial existing and
emerging
technology
on
a
sustained basis
UTRC
ITOBO inviting UTRC to
Support activities such as IERC
Fuel growth for UTRCI. Create
partnership
join
& 1K mote deployment
links with other IERC partners
ESB
Identify
retrofit
Longer term ID opportunities for
Major
partnership
opportunities
ESB
large scale actuation & control
embedded in WSN and BEM
deployments,
research
WSN
at
sites
QinetiQ
Organise
relationship
meeting – CIT/Tyndall?
Glen Dimplex
Organise
Relationship
E4U
follow-up
follow-up
meeting
–
address
inter-
utilities
player
and
operability challenges
commercialisation
Link to commercial deployments
Major
partner
for
IERC.
Potential set up in Ireland?
Link
to
commercial
Major partner for IERC
deployments, G house, etc
UCC/Tyndall?
Create
WSN
retrofit
Create/support commercialised
Funding + growth engine for
WSN deployment opportunities
many Irish based companies.
Offer Irish deployment
Tie in a networking event if
Networking opportunities with
site in the program
ME3Gas team visits??
new EU partners
Help identify suitable partners
Networking and EU funding to
and roles
support strategic research and
success stories to feed
to the EC
ME3Gas
ENIAC
Continue
partnerships
proposals
working
on
growth
FP7 SME calls
Continue
clustering
Provide
technical,
and
project
activities for upcoming
management
networking
SME & SME cluster
support. Help identify synergy
Irish SMEs get EU funding and
find
EU
partners
to
help
leverage new technologies and
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calls
opportunities
together
by
bringing
stakeholders
growth
with
complementary interests
Compile
IDFs
IDFs
from
Support proposed T&Cs
Licence
BuildWise work
Industry visits
Compile
lists
agreements
industry
of
potential clusters
Link/co-ordinate activities:-
Increase industry interaction in
IERC, FP7, 1K motes, G-house,
EU FP7 research in ICT &
Energy
etc
for Share the concept with Start 1-2 mini-cluster projects Technical,
Engine
innovation
industry
initially with EI funding.
Glen
Dimplex,
FMC-tech,
identify
diligence
partners
and
management
infrastructure
to
commercialisation
drive
of
WSN
technology & IERC activities
Wirelite source funding opps
Due
commercial
project
Help companies such as EMC,
Process chart
IERC
to
and
Advice and support to IERC
Ireland = leader in energy
and
drivers.
research
research, attract new MNCs,
commercial
grow existing and new SMEs,
roles
strands.
Identify
Provide
pool
guidance.
of
world
leading
researcher
1K
mote ITOBO to nail down BuildWise
deployment
to
develop
1-2
Ireland = leading test-bed for
sites
for
large
detailed proposal (multi-
industry-based
site)
integration into the deployment
scale
BEM
research
pilots.
Minimise
‘valley
of
death’
exposure to potential WSN
users
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6. Bibliography
European Union, 2002. European Performance of Buildings Directive, Available at:
http://europa.eu/scadplus/leg/en/lvb/l27042.htm [Accessed November 24, 2008].
Gallagher, M.P. et al., 2004. Cost Analysis of Inadequate Interoperability in the
U.S. Capital Facilities Industry, Gaithersburg, Maryland, USA: US Department of
Commerce.
Available at: http://www.bfrl.nist.gov/oae/publications/gcrs/04867.pdf
[Accessed January 12, 2009].
O'Donnell, J., 2009. Specification of Optimum Holistic Building Environmental and Energy
Performance Information to Support Informed Decision Making. Doctorate. University
College Cork, Ireland.
Piette, M.A., Kinney, S.K. & Haves, P., 2001. Analysis of an information monitoring and
diagnostic system to improve building operations. Energy and Buildings, 33 (8), 783-791.
Raftery, P. et al., 2010. Energy Monitoring Systems: value, issues and recommendations based
on five case studies. In CLIMA 2010. CLIMA 2010 Conference.
Simpson, P.G., 2008. BIM revolution - ICT waves in the AEC industry. Available at:
http://www.bimproducts.net/download/BIM-1-36_19-06.pdf [Accessed November 1,
2009].
Watson, J.R., Watson, G.R. & Krogulecki, M., 2009. Post Construction BIM Implementations
and Facility Asset Management. Journal of Building Information Modeling, (Spring 2009).
Available
at:
http://www.buildingsmart.com/files/u1/jbim_spring09.pdf
[Accessed
November 1, 2009].
Appendix A
This appendix shows the complete set of diagrams for the performance scenario that focuses
on heating system in the Environmental Research Institute (ERI) building as described in
section 4.1 (Scenario 1). The diagrams are followed by a complete list of sensors and formulae
required to underpin the three scenarios developed within the project. 88 of these sensors are
wireless and have been deployed as part of the WSN within the BuildWise technology platform.
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Scenario 1 – Heating in 4 reference zones
Performance
Aspect
Building
Function
Performance
Object
Z_G05:
Immunology Lab
Z_1.23: Open
Plan Office Space
Qualitative
Performance
Objective
Quantitative
Performance
Metric
Sensor/Meter
Formula
Monitor Themal
Comfort
PMV
Formula (see
spreadsheet)
Monitor Lighting
levels
Lux Level at
Working plane
Lux
Sensor
Monitor Relative
Humidity
Air Relative
Humidity
Air Relative
Humidity
Sensor
Monitor
Temperature
Air Temperature
Air
Temperature
Sensor
Monitor Window
Door Opening
Opening Signal
Window/Door
Opening
Sensor
Monitor Zone
Occupancy
CO2 Level
CO2
Sensor
Motion
PIR
Sensor
Monitor Themal
Comfort
PMV
Formula (see
spreadsheet)
Monitor Lighting
levels
Lux Level at
Working plane
Lux
Sensor
Monitor Relative
Humidity
Air Relative
Humidity
Air Relative
Humidity
Sensor
Monitor
Temperature
Air Temperature
Air
Temperature
Sensor
Monitor Window
Door Opening
Opening Signal
Window/Door
Opening
Sensor
Monitor Zone
Occupancy
CO2 Level
CO2
Sensor
Motion
PIR
Sensor
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Scenario 1 – Heating in 4 reference zones
Performance
Aspect
Building
Function
Performance
Object
Z_1.28:Seminar
Room
Z_1.28:Seminar
Room_b
Qualitative
Performance
Objective
Quantitative
Performance
Metric
Sensor/Meter
Formula
Monitor Themal
Comfort
PMV
Formula (see
spreadsheet)
Monitor Lighting
levels
Lux Level at
Working plane
Lux
Sensor
Monitor Relative
Humidity
Air Relative
Humidity
Air Relative
Humidity
Sensor
Monitor
Temperature
Air Temperature
Air
Temperature
Sensor
Monitor Window
Door Opening
Opening Signal
Window/Door
Opening
Sensor
Monitor Zone
Occupancy
CO2 Level
CO2
Sensor
Motion
PIR
Sensor
Monitor Themal
Comfort
PMV
Formula (see
spreadsheet)
Monitor Lighting
levels
Lux Level at
Working plane
Lux
Sensor
Monitor Relative
Humidity
Air Relative
Humidity
Air Relative
Humidity
Sensor
Monitor
Temperature
Air Temperature
Air
Temperature
Sensor
Monitor Window
Door Opening
Opening Signal
Window/Door
Opening
Sensor
Monitor Zone
Occupancy
CO2 Level
CO2
Sensor
Motion
PIR
Sensor
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Performance
Aspect
Thermal
Loads
Performance
Object
Qualitative
Performance
Objective
Quantitative
Performance
Metric
Sensor/Meter
Formula
Site
Monitor
Temperature
Outdoor Air
Temperature
Air
Temperature
Sensor
Z_G05:
Immunology Lab
Monitor Lighting
Lighting
Electricity
Electricity
Meter
Monitor Plug
Loads
Plug Loads
Electricity
Electricity
Meter
Monitor Zone
Occupancy
Occupancy
Thermal Load
Formula (see
spreadsheet)
Monitor Lighting
Lighting
Electricity
Electricity
Meter
Monitor Plug
Loads
Plug Loads
Electricity
Electricity
Meter
Monitor Zone
Occupancy
Occupancy
Thermal Load
Formula (see
spreadsheet)
Monitor Lighting
Lighting
Electricity
Electricity
Meter
Monitor Plug
Loads
Plug Loads
Electricity
Electricity
Meter
Monitor Zone
Occupancy
Occupancy
Thermal Load
Formula (see
spreadsheet)
Monitor Lighting
Lighting
Electricity
Electricity
Meter
Monitor Plug
Loads
Plug Loads
Electricity
Electricity
Meter
Monitor Zone
Occupancy
Occupancy
Thermal Load
Formula (see
spreadsheet)
Z_1.23: Open
Plan Office Space
Z_1.28:Seminar
Room
Z_1.28:Seminar
Room_b
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Scenario 1 – Heating in 4 reference zones
Performance
Aspect
System
Performance
Performance
Object
UFH Manifold 0.02
UFH Manifold 0.02
Loop 1 (Z_G05)
UFH Manifold 0.02
Loop 2 (Z_G05)
UFH Manifold 1.03
UFH Manifold 1.03
Loop 10 (Z_1.23)
UFH Manifold 1.03
Loop 11 (Z_1.23)
UFH Manifold 1.03
Loop 12 (Z_1.23)
UFH Manifold 1.03
Loop 13 (Z_1.23)
Qualitative
Performance
Objective
Quantitative
Performance
Metric
Sensor/Meter
Formula
Monitor
Temperature
Supply Water
Temperature
Water
Temperature
Sensor
Monitor
Temperature
Return Water
Temperature
Water
Temperature
Sensor
Monitor
Operation
Valve Signal
Control
BMS
Datapoint
Monitor
Temperature
Return Water
Temperature
Water
Temperature
Sensor
Monitor
Operation
Valve Signal
Control
BMS
Datapoint
Monitor
Temperature
Return Water
Temperature
Water
Temperature
Sensor
Monitor
Temperature
Supply Water
Temperature
Water
Temperature
Sensor
Monitor
Temperature
Return Water
Temperature
Water
Temperature
Sensor
Monitor
Operation
Valve Signal
Control
BMS
Datapoint
Monitor
Temperature
Return Water
Temperature
Water
Temperature
Sensor
Monitor
Operation
Valve Signal
Control
BMS
Datapoint
Monitor
Temperature
Return Water
Temperature
Water
Temperature
Sensor
Monitor
Operation
Valve Signal
Control
BMS
Datapoint
Monitor
Temperature
Return Water
Temperature
Water
Temperature
Sensor
Monitor
Operation
Valve Signal
Control
BMS
Datapoint
Monitor
Temperature
Return Water
Temperature
Water
Temperature
Sensor
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Performance
Aspect
System
Performance
Performance
Object
UFH Manifold 1.01
UFH Manifold 1.01
Loop 1 (Z_1.28)
UFH Manifold 1.01
Loop 2 (Z_1.28)
UFH Manifold 1.01
Loop 3 (Z_1.28)
UFH Manifold 1.01
Loop 4 (Z_1.28)
UFH Manifold 1.01
Loop 5 (Z_1.28_b)
UFH Manifold 1.01
Loop 6 (Z_1.28_b)
UFH Manifold 1.01
Loop 7 (Z_1.28_b)
Qualitative
Performance
Objective
Quantitative
Performance
Metric
Sensor/Meter
Formula
Monitor
Temperature
Supply Water
Temperature
Water
Temperature
Sensor
Monitor
Temperature
Return Water
Temperature
Water
Temperature
Sensor
Monitor
Operation
Valve Signal
Control
BMS
Datapoint
Monitor
Temperature
Return Water
Temperature
Water
Temperature
Sensor
Monitor
Operation
Valve Signal
Control
BMS
Datapoint
Monitor
Temperature
Return Water
Temperature
Water
Temperature
Sensor
Monitor
Operation
Valve Signal
Control
BMS
Datapoint
Monitor
Temperature
Return Water
Temperature
Water
Temperature
Sensor
Monitor
Operation
Valve Signal
Control
BMS
Datapoint
Monitor
Temperature
Return Water
Temperature
Water
Temperature
Sensor
Monitor
Operation
Valve Signal
Control
BMS
Datapoint
Monitor
Temperature
Return Water
Temperature
Water
Temperature
Sensor
Monitor
Operation
Valve Signal
Control
BMS
Datapoint
Monitor
Temperature
Return Water
Temperature
Water
Temperature
Sensor
Monitor
Operation
Valve Signal
Control
BMS
Datapoint
Monitor
Temperature
Return Water
Temperature
Water
Temperature
Sensor
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Performance
Aspect
System
Performance
Performance
Object
Qualitative
Performance
Objective
Quantitative
Performance
Metric
Sensor/Meter
Formula
Building
Monitor Operation
Cost
Cost of
Operation
Formula (see
spreadsheet)
Bolier
Monitor Operation
Cost
Cost of
Operation
Formula (see
spreadsheet)
Heat Pump
Monitor Operation
Cost
Cost of
Operation
Formula (see
spreadsheet)
Monitor Heat
Pump Output
Heat Output
Water circuit
heat
meter
Monitor Efficiency
COP
Formula (see
spreadsheet)
Scenario 1 – Heating in 4 reference zones
Performance
Aspect
Performance
Object
Qualitative
Performance
Objective
Quantitative
Performance
Metric
Legislation
Building
Monitor
Operational BER
EUI
Formula (see
spreadsheet)
Monitor CO2
emissions
CO2 Emissions
Formula (see
spreadsheet)
Sensor/Meter
Formula
Scenario 1 – Heating in 4 reference zones
Performance
Aspect
Energy
Consumption
Performance
Object
Qualitative
Performance
Objective
Quantitative
Performance
Metric
Z_1.28:Seminar
Room_b
Monitor Lighting
Lighting
Electricity
Electricity
Meter
Monitor Plug
Loads
Plug Loads
Electricity
Electricity
Meter
Monitor Energy
Consumption
Heating Energy
Consumption
Formula (see
spreadsheet)
Sensor/Meter
Formula
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Performance
Aspect
Energy
Consumption
Performance
Object
Qualitative
Performance
Objective
Building
Monitor Energy
Consumption
Total Energy
Consumption
Formula (see
spreadsheet)
Bolier
Monitor Energy
Consumption
Gas
Consumption
Gas
Meter
Heat Pump
Monitor Energy
Consumption
Electricity
Consumption
Electricity
Meter
UFH Manifold 0.02
Monitor Energy
Consumption
Heating Energy
Consumption
Formula (see
spreadsheet)
UFH Manifold 1.01
Monitor Energy
Consumption
Heating Energy
Consumption
Formula (see
spreadsheet)
UFH Manifold 1.03
Monitor Energy
Consumption
Heating Energy
Consumption
Formula (see
spreadsheet)
Z_G05:
Immunology Lab
Monitor Lighting
Lighting
Electricity
Electricity
Meter
Monitor Plug
Loads
Plug Loads
Electricity
Electricity
Meter
Monitor Energy
Consumption
Heating Energy
Consumption
Formula (see
spreadsheet)
Monitor Lighting
Lighting
Electricity
Electricity
Meter
Monitor Plug
Loads
Plug Loads
Electricity
Electricity
Meter
Monitor Energy
Consumption
Heating Energy
Consumption
Formula (see
spreadsheet)
Monitor Lighting
Lighting
Electricity
Electricity
Meter
Monitor Plug
Loads
Plug Loads
Electricity
Electricity
Meter
Monitor Energy
Consumption
Heating Energy
Consumption
Formula (see
spreadsheet)
Z_1.23: Open
Plan Office Space
Z_1.28:Seminar
Room
Quantitative
Performance
Metric
Sensor/Meter
Formula
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Appendix B
This appendix contains the slides and the minutes of the last BuildWise workshop that was held
at UCC in September 2010 with the interested companies.
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Energy Efficient Lighting workshop 16/09/2010 – minutes and actions
Attendees
Breakout groups listings (ref below)
+
Anthony Kelly, Powervation
Menouer Boubekeur, Donal Brown, Paul Stack, UCC
Michael Grufferty, Katherine Barry, Tyndall
Apologies/absence
Sean Noone, SELC
Kevin Donnelly, EI
Tony Power, Niall Harrington, FHP
Additions to circulation list (delegates were sent on their behalf)
Gary Duffy, Excelsys
Paul Sheridan, Lita Lighting
Cian O’ Mathuna, Tyndall
Pierce Martin, Wow Energy
Jim Lawler, EI
Dirk Pesch, CIT
Actions
• Brendan O’ Flynn & Nicolas Cordero to pass on their notes from breakout groups to Mike – DONE
(thanks).
• Mike to circulate soft copy of the presentation material – ATTACHED.
• (If Sirus would like to create 1 slide outlining their activities and interests it would be most welcome).
• John Doyle to circulate the building retrofit test-bed draft document that the WISEN group had
previously created. (e.g. Is there an opportunity to drive forward a proposal for industry led large scale
deployment of sensors incorporating EEL?)
• Mike Hayes to organize conference call with WISEN chair and industry experts to discuss test bed
reliability and standardization opportunities
• Paul McCloskey to provide market information to breakout group 1 to help understand market niches
better
• Mike Hayes to organize follow-up session with breakout group 1 to pull together an outline proposal.
• Mike Hayes to talk to Sean Noone off-line about breakout group 1.
• Participants to let the overall group know if they are interested in follow up meetings of this nature
(Mike Hayes will be happy to facilitate).
• If anyone wants to join any of the breakout group follow-on actions please let me know.
Breakout group sessions
Breakout group 1 - Drivers/ICs.
Attendees: Excelsys (Dermot Flynn), Ikon Semi (Conor McAuliffe), Lita (Paul Hacket), UCC (Brian
Cahill), Tyndall (Mike Hayes), EI (Paul McCloskey)
The key to success here will be for SMEs to cluster together and ‘punch above their weight’, using
collaborative technical knowhow, benchmarking and marketing intelligence (EI will help provide good
quality segmented market searches) to find market niches that are too small for the large SMEs to play in
but large enough that a few SMEs can operate in and all get a sufficient ROI.
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Applications
The group plans to start by bringing together technical experts to write an application niche driven
performance spec.
For optimized control algorithms the group needs to understand the applications (life levels, reliability,
lumens, accessibility, efficient savings, ease of retrofit, compatibility with systems, regulatory
conformance, etc.)
User needs need to be defined, e.g. ‘soft area’, user perceptions, minimum safety requirements, indoor
Vs outdoor conditions, control level settings, accessibility and expectations.
One possible significant area for exploration is solar powered street lighting/lamps for developing
countries.
The indoor lighting retrofit market is another key niche area, would be important that devices work with
existing dimmers, switches, etc.
Specification
We need to map out future topologies, e.g. implications of high step down ratios.
Need to optimize for the target voltage and load but also be aware that future specifications will focus
more on performance (efficiency) over a wide range of conditions (e.g. EPA 2.0 standard uses arithmetic
average over a range of conditions)
Light quality may be more important than just designing with a given margin & allowing for degradation.
Sensing technology could be used to optimize lumens operation Vs real-time conditions (Vs operating at
higher levels to compensate for performance deterioration with life).
Sensing technology could be used for ‘health monitoring’, indicating when lights are not operating
effectively/reliably (& which ones), optimizing and minimizing maintenance.
This is a very fast moving market so resources should also be deployed to keep an ongoing eye on the
market in parallel with any developments, team must be open to changes in product spec based on new
technologies & products as they come on to the market (e.g. next generation ballasts, plasma
technology).
Next steps
The group will work off-line on developing a multi-stand research proposal loosely defined as follows:• Application driven product specifications (Lita)
• IC design. e.g. FPGA (Tyndall & Ikon)
• Topologies (Excelsys & Ikon)
• LEDs & alternatives + optics (Tyndall)
• Thermals, magnetics modeling (Tyndall & Excelsys)
• DFM (Excelsys and Lita use SCMs) (sub-contract manufacturers)
I suspect SELC will also be very interested, will talk to Sean Noone off-line to determine SELC potential
roles to be determined in the above.
Deliverables:- 2 x outlines specs, 1 for indoor 1 for outdoor + IC samples
Breakout group 2 - sensors, actuation.
Attendees: Wirelite (Michael Phelan), Benetel (John Doyle), Rockbrook (Paul Byrne) , EI (Mike
Dolan, Andrew Connell), Sirus (Frank Caul & James Byrne), Tyndall (Brendan O’ Flynn, Padraifg
Curran), Joe O’ Callaghan (IERC consultant), CIT (Alan McGibney), UCC (Karsten Menzl), NUIG
(Marcus Keane).
A number of opportunities presented themselves
New Products
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There is an opportunity in the development of localization technologies based on next generation
802.15.4 UWB radios
This will benefit industry developing the technology and users further up the value chain who could
integrate these technologies in to building management systems they are developing and installing
There is a lack of standardization of wireless protocols. This creates significant barriers for potential
adopters of this technology, how to ensure compatibility with all the protocols out there. We also need to
get a handle on how to enable actuation in accordance with the various wired and wireless protocols out
there.
There is a general mistrust of wireless sensor network (WSN) technology for many applications. It is Ok
for basis sensing but for actuation and control or applications where it is critical the info is transmitted
immediately many users are wary of it. We need address this perception of reliable networking capability
through the development of industry driven test beds where the reliability of such systems can be proven
in the field and issues such as scale up, security, data reliability. Latency etc addressed and be shown
not to be an issue to customers
Once these issues are addressed there would be significant building management retro fit opportunities
for metering (secondary metering) actuation and control
Breakout group 3 - integration of EEL solutions for displays and refrigeration.
Attendees: Nualight (Vincent Guenebaut), Rockbrook (Brian Franzoni), WowEnergy (Brigid
Curtin), Tyndall (Peter O’ Brien and Nicolas Cordero)
The group talked mostly about integration at system level (e.g. in a retail application a system would
include the light fixtures, the driver(s) -one per fridge or one per isle ...- and the controls).
There was nobody from retrofitting (e.g. Lita) or from drivers so the group did not talk about integration at
fixture level.
One important conclusion of the discussion is the fact that as the big fixture players (Philips, Osram, ...)
get into the fixture market, the small players cannot compete. So the opportunities for SMEs are in the
system integration. Instead of just selling Tesco the fixtures, you have to offer the whole solution: the
whole system, with control, driver and fixtures, customized for their application.
From the control point of view, two big issues are (i) the mistrust of wireless networks and (ii) the lack of
single protocols.
So if users have two or three systems (general lighting, security lighting -with batteries, etc.), they have to
put two or three wires going to each appliance/fixture. Not too bad for greenfield sites, but a waste for
brownfields.
The control and intelligence are very much application dependent. The participants have very good
examples. In retail, control and intelligence are of very little use (if the lights in an isle or a fridge are
dimmed or turned off customers won't go there!!!). On the other side, in a conference centre, it is enough
to know the times when the talk(s) are on to have a very effective control system. Feedback on the
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operation of the light (e.g. is it broken?) and on security lighting (e.g. self-testing) is essential to take full
advantage of the control system.
Energy efficiency may not be the key driver for some applications, it may be taken as given that some
kind of energy efficient lighting solution is being used and price and performance become the key drivers
(e.g. lumens, reliability, consistency of colouration).
It is premature to expect any solid actions form this break-out group until further work is done in the other
2 areas but this was stated before the breakout sessions started and the information form the session is
useful.
However these conclusions should help on deciding were to go: How to improve confidence on wireless
networks? How do you standardize/unify protocols? Design of application-specific control/intelligence?
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