Benchmarking Environmental Building Data for Enhanced Performance and Improved Insights

Project ID: 2531ad1477

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Research Theme: Energy and Decarbonisation

UCL Lead department: Bartlett School of Environment, Energy and Resources (BSEER)

Department Website

Lead Supervisor: Sam Stamp

Project Summary:

Are you excited by the potential of big data to transform building efficiency and environmental quality? Join us in a pioneering research project aimed at harnessing smart building data to create healthier, more sustainable, and resilient indoor spaces. This PhD studentship offers a unique opportunity to develop your skills in data analysis, big data management, and environmental benchmarking, making a real impact on how buildings are designed, managed, and optimized. Project Overview Smart building technologies now generate enormous quantities of environmental data—including metrics on energy use, indoor air quality, temperature, humidity, and occupancy. This data has untapped potential to enhance sustainability and operational efficiency in buildings, yet translating raw data into actionable insights remains a key challenge. This research will tackle this complexity by integrating and analyzing diverse data sources, defining performance metrics, and creating benchmarks that can identify poorly performing spaces in need of intervention, as well as highlight resilient, energy-efficient spaces that can serve as models.

Using University College London (UCL) buildings as a case study, this project aims to build a comprehensive benchmarking framework that leverages thousands of data points from a diverse range of UCL spaces, including academic, office, and residential buildings. This PhD project will not only advance traditional energy benchmarking but will expand it into the domain of indoor environmental quality (IEQ), allowing for real-time, room-level, and time-series data analysis that can dynamically assess resilience as well as average performance