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Centre for Digital Built Britain completed its five-year mission and closed its doors at the end of September 2022

This website remains as a legacy of the achievements of our five-year foundational journey towards a digital built Britain
 

Research background

Xiang Xie is a research associate working in the Asset Management group in Institute for Manufacturing. Xiang’s research mainly focuses on the application of building level and campus level Digital Twin to support better-informed decision-making. Particularly, he is interested in establishing a digital-twin enabled building energy quantification and performance assessment framework in Operations and Maintenance management.

CDBB projects involved with

West Cambridge Digital Twin Facility

Research ambitions for CDBB

My research in CDBB will focus on demonstrating the role Digital Twin plays in delivering public benefits, unlocking the value from data and providing determinable insights for construction sector, during the operation and  maintenance management. In particular, I am working on developing a fault diagnosis/prognosis system that exploits machine learning capabilities to detect anomalies of energy assets, and facilitates understanding of their interaction with indoor built environment. Meanwhile, I would also actively explore an appropriate energy quantification and assessment framework to ascertain the efficiency of energy use in buildings and lay the foundation for decision-making to enhance energy efficiency.
 

Biography

Xiang got his PhD degree in the Zhejiang University in September, 2018. For his PhD, he focused on providing an accurate assessment, awareness and identification for anomalies in water distribution systems using data-driven monitoring techniques. Specifically, with the help of affordable sensing and communication equipment, system-wide smart metering is implemented to collect heterogeneous data from different sources and operational information is mined to intelligentize the urban water supply infrastructure.

Publications

Key publications: 
Research Associate

Affiliations

Classifications: