Internet of Things technologies can improve the operational efficiency of buildings, creating "digital twins". This project assesses the whole lifecycle cost of data capture, analysis and storage to deliver sustainable digital twins for decarbonisation and demand management. Intelligent Buildings have been in operation for decades however it is only in recent years that data from these systems is starting to surface beyond building management systems. The ubiquity of the Internet of Things is changing how we sense and interact with our environment and has led to the emergence of the Digital Twin - a virtual model of a real-life operational entity. Driven by information, these models allow us to monitor operations to head off issues before they arise, or optimise operations based on ever changing human-environment interaction. This research will explore the hidden value of "data as a material" in 2 new campus buildings to improve efficiency and demand flexibility.
At a global level, urgent action is required to decrease the carbon intensity of our buildings and to support a transition to a net zero carbon operation. As the potential volume of data grows exponentially it is essential that we strategically look at the whole life cost of this information to ensure the digital footprint cost is optimised compared to the benefit accrued.
This PhD aims to develop a new method to quantify the social, economic and environmental benefits of capturing, analysing and storing information generated in a digital twin based on analysis of demand management and post occupancy evaluation. Analysis will be conducted on the digital footprint of two new campus buildings at UCL East (opening 2022 and 2023) which have the capacity to generate about 30 million data points per day. The research will explore the buildings in the context of operational factors such as improving facilities and the role of a Living Lab environment supporting research and teaching.