Health-Aware Digital Twins for Building Control under Climate Extremes: An Exposure-State Control Framework

Seyed Reza Samaei; James Riffat

doi:10.65582/rrs.2026.011

Authors

Seyed Reza Samaei World Society of Sustainable Energy Technologies, Nottingham, United Kingdom https://orcid.org/0000-0003-1627-1991
James Riffat World Society of Sustainable Energy Technologies, Nottingham, United Kingdom https://orcid.org/0000-0003-0374-4526

DOI:

https://doi.org/10.65582/rrs.2026.011

Keywords:

Health-Aware Digital Twin, Exposure-State Control, Cumulative Health Exposure, Indoor Air Quality, Energy–IAQ Co-Optimization, Climate Extremes, Building Control Systems

Abstract

Climate extremes expose a fundamental limitation in current building control strategies: compliance with instantaneous thermal and air quality thresholds does not guarantee protection against cumulative health risk. Existing digital twin and predictive control approaches largely treat indoor environmental variables as memoryless signals, neglecting the time-integrated nature of human exposure. This study addresses this gap by introducing an exposure-state control framework that explicitly models cumulative thermal and air quality exposure as dynamic system states with temporal memory. A health-aware digital twin is developed by integrating a physics-based building model with residual learning and predictive control over an augmented state space. The framework is evaluated using a structured stress-test suite, including prolonged heatwaves, compound heat–pollution events, ventilation constraints, sensor drift, and equipment degradation. Across 30 Monte Carlo simulations, the proposed approach reduces cumulative thermal exposure by 35–55% and particulate exposure by 30–50% relative to compliance-based and MPC controllers, while limiting energy penalties to below 12%. The results reveal a structural disconnect between regulatory compliance and long-term health protection and demonstrate that exposure-state modeling enables anticipatory and risk-aware control under sustained stress conditions.

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