Towards the smart citizen:
the IRMA service project
Gianmario Motta, Daniele Sacco, Linlin You
DIII (Dpt of Electric, Electronic, Biomedical and
Computer Engineering)
University of Pavia
September 19, 2013
- 1-
Towards the smart citizen: the IRMA project
Introduction
An ideal
profile
IRMA
Trip Planner
City Feed
Conclusion
- 2-
A foreword
 Most people live in cities:
nowadays 3.6 billion and
in 2050 68% of world
population.
 Cities consume 80% of
worldwide energy
production and generate
67% of energy-related
greenhouse gases.
 64% of travelled
kilometers are urban and
the travel within urban
areas is expected to
triple by 2050
Transport shall be smart,
green and integrated (H2020 EU Framework Programme for
Research and Innovation)
- 3-
Smart mobility
User System
Transport
System
Smart city
Vehicle
System
Traffic
Management
System
 A smart city shall provide smart
mobility
– Green mobility: green vehicles, public
or shared transports.
– Integrated mobility: the citizen can
travel across a seamless transport
system.
 A smart mobility has to integrate
multiple physical transport
systems
– Transport systems
– Traffic management systems
– Vehicle systems.
 A smart citizen needs to integrate
mobility information from
multiple sources and therefore
requires
– a (smart) user system to manage
his/her mobility
- 4-
Smart mobility: some projects
 European projects
– Instant Mobility
User System
Transport
System
• intends to manage mobility for different stakeholders,
based on future internet infrastructure (FI-WARE).
• enables travellers to view real-time traffic status and public
transport availability and optimize their routes according to
current personal preferences and constraints.
• supports local authorities, public transport operators and
professional drivers to optimize traffic and promote car
sharing and pooling.
• logistic is enhanced and optimized for fleet management.
– TRIPZOOM
Smart city
Vehicle
System
Traffic
Management
System
• implements a new approach to urban mobility by sharing
personal mobility patterns via social networks.
• E.g. citizens can optimize their mobility needs using
recommendation and personalized traffic services from the
city authority.
 Other projects
– Future Urban Mobility
• developed by MIT and National Research Foundation of
Singapore.
• uses mobile devices to provide high quality information on
the status of the transportation network and
• aims to guarantee the promise that urban citizens demand,
such as energy consumption.
• Currently, only a framework has been developed.
- 5-
Smart Mobility: present and future
System
Transport
Present
Cars dominate
Car (and buses) orientation




Future
Public transports (underground etc.)
Shared transports (bikes etc.)
Private green transports
Public & shared mobility
Traffic Management
Vehicle (Vehicle
Management Systems)
User
Mainly cars

Probably not a priority
Navigators
Google maps
Itinerary planner



Integrate open data, crowd data etc.
Plan and monitor personal mobility
Buy mobility
- 6-
Towards the smart citizen: the IRMA project
Introduction
An ideal
profile
IRMA
Trip Planner
City Feed
Conclusion
- 7-
Our architecture
exemplifies the
service convergence
into a value
proposition
Integrated Personal Mobility User System: Layers
Custom
Application
Application services for the smart citizen
(value proposition)
Storage &
Process
Big Data technologies
Transformation
& Loading
Extraction
Sources
Custom application software (e.g. agent)
General
Transit Feed
Spec (GTFS)
or API
API /
Crawling
API
Open Data
(Transport)
Miscellaneou
s Open Data
& Websites
Crowd Open
Data
- 8-
Open data as source
 Open data initiatives require
that government data are
freely available
 Transport open data initiatives
 Open data include public
transport
 In Europe
– «The term open data has been
coined a few years after the
Directive 2003/98/EC of the
European Parliament and the
Council of 17 November 2003 on
the re-use of public sector
information (PSI), which sets out
the rules and practices for
accessing public sector
information resources for further
exploitation»
- 9-
Open Transport Data
Open Transport data
AGENDA
Introduction
Geospatial
data
Timetables
Fare cost
Traffic data
Accident data
Road network
metadata
State of Art
Historical
data
Bus stops
Real-time
Vehicle
Speed
limitation
Reports
Tram lines
Archived
Bike
Addresses
…
Pedestrian
…
IRMA
Open Data
Conclusion
Future Work
○
Routes
Locations
The General Transit Feed Specification (GTFS) defines a common format for public
transportation schedules and associated geographic information. It allows:
•public transit agencies to publish their transit data
•developers to write applications that consume that data in an interoperable way
- 10-
GTFS format
AGENDA
A GTFS feed is composed of a series of text files collected in a ZIP file. Each file
models a particular aspect of transit information.
Introduction
State of Art
IRMA
Open Data
Conclusion
Future Work
○
- 11-
Implementation on Torino
AGENDA
Gruppo Torinese Trasporti provides GTFS data
Introduction
Travel monitoring and control needs also GTFS-RT data (real-time)
State of Art
IRMA
Open Data
Conclusion
Future Work
○
- 12-
OpenTripPlanner
AGENDA
Introduction
State of Art
IRMA
Open Data
a. All components of the OpenTripPlanner are open. All of its
software is open source, it is built on an open architecture.
b. It was specifically designed to be modular for easy
customization, including the use of other datasets.
c. Developers have full access to source code
d. It uses three open datasets to generate an intelligent
routable graph( GTFS, NED e OSM)
Conclusion
Future Work
○
- 13-
- 14-
- 15-
- 16-
Integrated Personal Mobility User System:
Stakeholders
Feedback
End User
Booking /
Boarding transactions
Virtual tickets
Transpo
rt
Provider
s
Consent
Planned mobility
Actual mobility
Information on
Personal Mobility
(Big Data
Technologies)
Financial
Provider
s
Municipality
Service
Provider
s
Troubl
e
tickets
Progress
- 17-
Towards the smart citizen: the IRMA project
Introduction
An ideal
profile
IRMA
Trip Planner
City Feed
Conclusion
- 18-
Integrated Personal Mobility User System : IRMA
- 19-
IRMA: Overall vision
Transport
providers
On Board Display
Smart TV
APP
Local
Government
INDIVIDUAL
MOBILITY
FORECASTER
INDIVIDUAL
MOBILITY
ANALYZER
Smartphone
TRIP
PLANNER
Big Data (Synthesis of diverse data)
Open Data
(timetables)
Crowd data
(User and device
feeds)
Miscellaneous Data
(e.g. Websites)
- 20-
Towards the smart citizen: the IRMA project
Introduction
An ideal
profile
IRMA
Trip Planner
City Feed
Conclusion
- 21-
IRMA: Trip Planner
- 22-
IRMA: Trip Planner on Android
- 23-
IRMA: Mobility Analyzer
- 24-
IRMA: Mobility Analyzer
Tweet density in Torino
- 25-
Towards the smart citizen: the IRMA project
Introduction
An ideal
profile
IRMA
Trip Planner
City Feed
Conclusion
- 26-
IRMA: City Feed
- 27-
IRMA: City Feed
- 28-
Towards the smart citizen: the IRMA project
Introduction
An ideal
profile
IRMA
Trip Planner
City Feed
Conclusion
- 29-
Conclusions
 IRMA is an universal application multi-language and multi-location
 IRMA proves that a sophisticated cloud application based on big data concepts
– can be designed and developed by an University
– by integrating together Open Sources modules thus
• Reusing software (web services)
• Lowering costs (no sw license)
 Smart User Mobility (Trip planner + Mobility Analyzer) has a high potential impact on
transports.
– Occasional users (e.g. tourists) become able to use the public network of a city
– The system supports personal mobility END TO END of
• Users
• Municipalities (forecasting, monitoring and analyzing mobility flows)
– In the future scenario:
• Users buy an itinerary, not a ticket, regardless the transports they use.
• Municipalities simulate alternative transport modes and pollution /energy
impact
 City Feed enables cooperation of citizens and municipalities, and overcomes
bureaucratic walls
- 30-
The IRMA team
The almost complete SEL team
IBM visit
Presentation to Malpensa
SEL = Service Engineering Lab, DIII, University of Pavia
- 31-
Acknowledegments
– Overall Design / PM
•Gianmario Motta (AP)
•Linlin You (PhD st)
•Daniele Sacco (Phd st)
•Thiago Barroero (PhD,
Pavia)
– PASS (forerunner of
IRMA)
•Giovanni Miceli (Pavia)
•Yuwei Yin (Tongji )
– IRMA State of art survey
•Belloni (Pavia)
– IRMA Trip Planner
•Li Renlong (HIT)
•Xu Ran (Tongji)
•Zhao Hongda (HIT)
– IRMA Big Data / Mobility
Analyzer
•Nicola Bertolazzo (Pavia)
•Chen Chen (Tongji)
•Han Yingwei (Tongji)
– IRMA City Feed
•Chonghe Ruan (UESTC)
•Lu Zhang (UESTC)
•He Yong (Tongji )
- 32-
Former Steps
2011/12
•PASS Exercise
September - December, 2012 : IRMA r0
•FP7 Proposal (selected not funded)
March – July, 2013: IRMA r1
•IRMA R1 design and development
•Pavia & Malpensa pilots talks
•HIT lab & Weihai pilot talks
•SAP talks
Best Application Paper
SOLI 2013
- 33-
Next steps
Sept -Dec 2013 :
IRMA Pilot
• Pavia follow-up team
• Pavia spin-off launch
Sept-Dec 2013 : International
cooperation
• HIT cooperation on Weihai lab launch
• Tongji cooperation on Big Data
Winter-Spring 2014
• Horizon 2020
- 34-
BACK UP
- 35-
IRMA
IRMA Big Data Introduction
-Mobility Analyzer
- 36-
IRMA
IRMA
INTEGRATED REAL-TIME
MOBILITY ASSISTANT
- 37-
IRMA Scope
On Board Display
APP
Smart TV
Municipalities
Smartphone
Transport
providers
MOBILITY
FORECASTER
MOBILITY
ANALYZER
MOBILITY
ASSISTANT
COMMUNICATIONS SERVICES (MIDDLEWARE)
Open Data
(timetables)
Crowdsourcing
data (feeds)
Big Data
(Unstructured
data)
- 38-
Mobility Analyzer: Big Data
Data Profile
Volume:
- E.g. Milano might be about 10
M per day
What can it provide
City Conditions
Variety:
- Geo-based data, sentiment
data, open data, trip data
Volatility:
- Refleshes every second
Dashboard
Reports
Smarter city
DaaS
Other：Mobility Assistant data
Various City Data
Social network
How to use it
Transportation System
CITY Feed
Other
- 39-
IRMA
BIG DATA Solutions
MOBILITY ANALYZER
SOLUTION
- 40-
Our Solution: From Data to Visualization
Key performance indicators
Real-time position of vehicles
and people
Scheduled position
of vehicles (according to timetables)
Streets and routes
Municipality Map
Data Retrieval
GTFS Files
Data Processing and Transformation
Data Integration
Data Presentation
Json Files
Mobility Analyzer
web-app
EC2 sever
Raw source tables
- 41-
IRMA
IRMA BIG DATA
FUTURE SCENARIO
- 53-
Future Scenario
 Data storage (Transactional DB and Data Warehouse)
Two Areas
Current Solution:
ETL powered by Pentaho
Transactional DB
Data Storage
No-SQL DB
Data Warehouse
Relational DB
Relational and object-oriented DB
Data Analysis
Future Scenario
(SAP HANA Solution)
In-memory DB
Columnar DB
Data Load Architecture Scenarios
- Near real-time reputation (scheduled)
- Real-time reputation
- Periodic Load (ETL)
- 54-
Future Scenario
 Big Data (Analysis part)
Distributed file system
Store Data
Mapreduce：Data Analysis
Two Areas
Data Storage
Data Analysis
Current Solution
In Cloud
Analysis Result
From Raw Data
to Analysis result
Cloud Computing Solution
Deploy Hadoop in Cloud
Run Mapreduce in Cloud
Reduce
(Agents)
Map
(Agents)
……
Raw Data
(Social Data)
Future Scenario:
SAP Solution
-
Real-time analysis
SAP Cloud (SAP Cloud Service)
SAP In-memory technology (SAP HANA)
SAP BD Technology (Columnar DB)
Parallel processing (SAP HANA)
- 55-
User systems in Smart Cities: some projects
Profile
Mobility User
Stakeholders
FP7
Instant Mobility
Projects
Singapore
FP7
Future Urban
TripZoom
Mobility
Partial
Pavia
IRMA
Municipality
Transport Provider
Transport
Management Systems
(Open Data)
Data Sources
Traffic Management
Systems (Open Data)
To be
developed
Vehicles
Social networks and
crowd data
Mobility analysis
Services
Mobility forecasting
Partial
To be
developed
Real-time assistant
- 56-
Smart City Framework Programs levels
 No overall master plans but FPs
 Italian Government issues cofunded FPs
EU :
H2020
Italy: MIUR FP
Italy regions: MIUR-like FPs
Italy Municipalities: City Planning
- 57-
Europe’s Horizon 2020
 Objectives
– societal challenges by helping to
bridge the gap between research
and the market by helping
innovative enterprise to develop
their technological
breakthroughs into viable
products with real commercial
potential.
Italy
 Funding
– Total budget = 86B €
– Budget for smart, green and
integrated transport = 6,802B €
Italy regions
 Target
– Industrial consortia in
collaboration with universities
and research centers
EU
Italy Municipalities
 Time Horizon
– Running 2014 to 2020
- 58-
Italy’s MIUR FP
 Objectives
– Contribute to smart communities in
cities in order to solve emerging
social challenges by new
technologies, applications or models.
 Budget
– Project threshold = 12M €
– Project ceiling = 22M €
– Total = 655M €
EU
Italy
 Eligible participants
– Industrial corporations (50% funded)
– Universities and research centers
(80% funded )
Italy regions
 Timing
– Projects chosen in 2013 springtime
– Projects to be finished by December
30, 2015
Italy Municipalities
- 59-
Italy’s MIUR FP: winning cities
 Turin: 183M € on smart grids,
sustainable buildings
environment monitoring
EU
 Milan: 170M € on smart
logistics and water resources
control
Italy
 Napoli: 19M € on bike-sharing
 Bologna: 113M € on a system
that aggregates public
transport information on
smartphone
 Genova: 160M € : Security,
Transport, Sea logistics,
Remote patient monitoring
Italy regions
Italy Municipalities
- 60-
Italy’s MIUR FP :
Wide Sensible Cities case study
Project
manager
Fondazione
Politecnico
Industry
partner
Finmeccanic
a/Selex
Research
partner
User partner
Politecnico
di Milano
Malpensa
municipality
Università di
Pavia
SEA (Airport
mngt)
Treasury
police and
air police
ENAV (Flight
authority)
- 61-
Italy’s MIUR FP :
Wide Sensible Cities case study
Traffic
management
Police support
Security
Integrated
mobility
Smart grid
Traffic
coordination
system
Auto-detectore
(plate analysis)
Security control
room
Trip planner
Intelligent
lights
Access control
(ECO-pass)
Patrol support
system
E-BLUE (remote
escort on
smartphone)
Ticketing
Intelligent
traffic lights
Parking
manager
Grid control
system
Bike-sharing
Miscellaneous
PAVIA
- 62-
PAVIA solutions
Project
Concept
Target
PASS
IRMA
• 7th Framework Programme
• Horizon 2020 Programme
• App to manage user’s trip
• Open data (Web services)
• On premises
• User’s trip + municipality
• Open data (GTFS) + Crowd
data + Big data
• Cloud service
• Development of a pilot
• FP7 proposal
• DIII: application
• Politecnico: technology
• Terminated (2012)
• Complete demo: IRMA (trip) +
City Feed (municipality)
• Pilot city talks
• Pavia municipality
• Malpensa municipalities
• Other
• Cooperation with MNCs on
technology
- 63-