Glasgow Caledonian University
SEBE PhD Research Project Portfolio
Project Reference Number
SEBE_NCS_HL_1
School/Institute/Research Group
School of Engineering and Built Environment - Networks and
Communications Research Group
http://www.gcu.ac.uk/isetr/researchareasandthemes/interactiveandcommunicationsengineering/
Research Discipline
Project Title

Building Energy management, Wireless sensors, advanced machine
learning, Random Neural Networks
Smart Building Energy management for Large Non-domestic Buildings Using
HVAC (Heating Ventilation and Air Conditioning) Control
Research Project Summary
Energy Management Systems and Building Control Systems are becoming a
very important area of growth in the 21st century Green Economy. It requires
many optimized specialties and techniques that span over a wide area of
engineering: Network protocols and standards, embedded systems, and
Building Standards.
Central controllers have been mostly based on
thermodynamic calculations for the large buildings, these are complex and
require a lot of computing power, and are not suitable for real-time
calculations.
The aims of the project are to:
1. Develop an advanced central controller for management of energy and
building control systems in large non-domestic buildings based on Random
Neural networks. This project is an advancement of the previous successful Phd
Studentship (Advanced Sensor Architecture (Protocols and Embedded Systems)
for Development of Energy Management Systems and Building Control
Systems) which culminated in a patent and several research papers (for local
controllers). Large non-domestic buildings require both local and central
controllers; our focus will be central controllers in this project.
2. Rigorously test and critically analyze the central controller in the test labs of
the School as well as under field conditions, including remote monitoring (BNE:
RICH center, and CEBE) of buildings with HVAC.
3. Optimize the control systems using advanced techniques (i.e. random neural
networks) to develop machine learning central controller. This will generate a
system that learns from the environment and what humans prefer as ideal
settings for the building, and generate control commands in real-time. The
main objective is energy efficiency and human comfort. This type of controller
will be very important for reducing carbon footprint, and generate partnerships
with industry.
Supervisory Team
Staff Contact



Dr. Hadi Larijani (DoS)
Dr. Ali Ahmadinia
Prof. Rohinton Emmanuel
Dr. Hadi Larijani (Senior Lecturer)
Tel: 01413313190
Email: H.Larijani@gcu.ac.uk