Start date: 03/2022 Duration: 15 months

USL has been awarded funding for a collaborative research project of ‘A novel framework for occupant comfort and building energy management to accelerate decarbonisation’. This is an international multi-university cross-disciplinary collaboration between USL Imperial College London (ICL) and LIFT Nanyang Technological University (NTU).

This project is developing a novel framework to evaluate the thermal comfort, awareness, and attitude of occupants toward smart applications (e.g., motion sensor light and solar panel) in buildings, in order to reduce operational carbon emissions as part of global efforts for decarbonisation. The project is starting with buildings at both Imperial and NTU campuses and developing a methodology that can be extended to residential and commercial estates in UK and Singapore.

Research teams and people
A major theme of the research in the two groups at ICL and NTU for the past decade has been the development of smart IoT systems and people behaviour modelling based on a range of conventional and new data sources and techniques.

• USL
  At the ICL team, the research is focused on modelling activity-travel behaviour and demand, with extensions to address demand-side behaviour in buildings. This stream of work has developed new methodologies, e.g., activity-based approaches to investigate the behaviour of occupants in buildings. The application of these methods requires advanced statistical/machine learning models, accurate and timely energy data sources and appropriate occupant survey data.
  Dr Aruna Sivakumar | Dr Fangce Guo | Han Wang
• LIFT
  At the NTU team, a wireless smart IoT framework has been developed to enable rapid condition assessment of civil infrastructure. The system has been recognized by NSF in the USA for commercialization, and it has also been installed on over 10 railroad bridges in the USA and Ain Dubai Ferris Wheel in the UAE.
  Dr Yuguang Fu | Dr Swapnil Dubey

The collaboration will extend the scope of the existing smart sensing platform developed by the NTU team with the occupant behaviour models developed by the ICL team to address the challenges in building energy management. The building sector as one of the largest energy consumers contributes approximate 40% of the total energy use in the world. More specifically, a large proportion of the energy consumed in buildings is used to improve the indoor comfort of occupants. Hence, this project aims to develop an integrated framework to evaluate the thermal comfort and attitude of occupants toward smart applications in buildings to address energy optimisation issues in building management.

Workshops and webinars

Dates	Activities	Main speakers and  team members	Topics
10th Jun 2022	Webinar at ICL	Dr Jacek Pawlak	Modelling the demand side response (DSR) to energy price signals using the MDCEV approach
1st July 2022	Webinar at NTU	Dr Swapnil Dubey	Overview of Smart and Sustainable Building Technology (SSBT) programme at ERI@N
7th Oct 2022	Webinar at ICL	Dr Huiqiao Hou	Understanding building and urban environment interactions: an integrated framework for building occupancy modelling
16th Dec 2022	Workshop at NTU	Dr Aruna Sivakumar	Understanding building and urban environment interactions: an integrated framework for building occupancy modelling (Updated)
		Yu Ziying, Tan Yun Liang	RoomSensor development for indoor environment monitoring
		Dr Pradeep Shakya	Intelligent Building Automation and Analytics using Model Prediction Control (MPC)
		Dr Fangce Guo	Sustainable AI in Intelligent Transport Systems
		Dr Wei Shen	Wireless data infrastructure for infrastructure sensing
		Han Wang	Exaggerated potential for improvement in demand-side management with EV? Testing with observed and simulated consumer activities
10th Feb 2023	Webinar at NTU	Dr Giridharan K	SinBerBEST Technology Transfer Initiatives
16th June 2023	Virtual workshop at ICL	⁠Han Wang	Thermal comfort modelling in shared offices based on environmental sensors and social influence surveys
			Modelling Activity Rescheduling in Demand Side Management with Surveys and Mixed Logit Models
		Ku Chia ⁠Tzu Pei, Yu Ziying, Tan Yun Liang, Hao Jie, Lim Ju Yen, Junru	Smart Sensing for Building Management System by RoomSense (Updated)

 Dates are subject to change