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Data Driven Approach to Modelling the Resource Footprints of Live Data Streams in Digital Twins
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 two new campus buildings to improve efficiency and demand flexibility.
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.
Partners
ARUP Group Limited
Dates
27.09.2021 - 26.09.2025
Funding
EPSRC and Arup
Contact
William Markiewicz
Research Team
Duncan Wilson, Cliff Elwell (UCL Energy Institute), William Markiewicz