The project focuses on modelling of the energy consumed by buildings and their outdoor environment at the neighbourhood scale to evaluate strategies that can mitigate urban heat islands and climate change.
This project focuses on the development of novel strategies for increasing the autonomy of space habitats; primarily: 1) root cause analysis of faults, and 2) uncertainty quantification in digital twins.
The project aims to develop enabling methods for practical deployment of reinforcement learning for building control.
The primary goal of this project is to design, implement, and evaluate a human-in-the-loop sensing and control system for energy efficiency of HVAC and lighting systems based on a novel depth-imaging occupancy sensor.
The primary goal of this project is to design, implement, and evaluate a human-in-the-loop sensing and control system for energy efficiency of HVAC and lighting systems based on a novel depth-imaging occupancy sensor.
This project targets the development of a metadata inference framework to provide operational information, i.e., the metadata associated with sensors and actuators.
This project seeks to develop technologies for the creation of operating systems for buildings, including ontologies and schemas for hardware abstraction, middleware platforms and the tooling around these.
Through this project, we seek to develop an integrated framework for predicting extreme temperature risks in urban areas.