Human Digital Twins for Exposure-Aware Behavioural Interventions in Learning Environments

Project ID: 2531bd1607

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Research Area(s): Engineering
Healthcare technologies
Data-driven systems / digital twins

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

Project Summary:

We spend more than ninety percent of our lives indoors, yet our understanding of how everyday environmental exposures—light, air quality, temperature, and noise—affect our behaviour, mood, and wellbeing remains limited. Traditional monitoring approaches rely on static sensors and isolated datasets, overlooking the dynamic and interactive nature of human experience within buildings. This PhD project will pioneer the use of Human Digital Twins (HDTs)—data-driven personal models that integrate environmental, physiological, behavioural, and contextual information—to better understand and improve how people experience and adapt to their surroundings. By linking multimodal sensor data with real-world behaviours, the research will move beyond passive observation toward adaptive, exposure-aware interventions that promote healthier and more comfortable learning environments. The project addresses four critical gaps:

Methodological: Integrate multimodal sensing, exposure mechanisms, and just-in-time adaptive interventions (JITAIs) into a unified HDT framework.
Contextual: Extend HDTs into higher-education learning spaces, where exposures and behaviours are collective, dynamic, and constrained by building systems.
Applied: Evaluate both the predictive accuracy of HDTs and their real-world effectiveness in changing behaviour, reducing exposure, and improving comfort and wellbeing.
Societal: Develop open-source tools and data protocols that inform healthier, more responsive educational and occupational environments. This interdisciplinary research sits at the intersection of building science, health, behavioural data analytics, and environmental design, offering opportunities for collaboration across engineering, architecture, and human health disciplines. The outcomes will contribute to new methods for understanding and optimising the indoor environment’s impact on human performance and wellbeing.