DigiGuide: A DT-based Occupant Guiding System for Optimizing Comfort and Energy Consumption

Abstract

Balancing occupant comfort while minimizing energy consumption is not trivial. Traditional methods rely on environmental control guided by occupant feedback but often fall short in addressing individual preferences effectively. This paper presents DigiGuide, an innovative system that leverages Digital Twin (DT) methodologies combined with multi-objective optimization algorithms to guide occupants to spaces that best meet their multi-variant comfort needs. DigiGuide forecasts future indoor environmental conditions and occupant states in real-time by relying on the DT of the physical environment. It then leverages a genetic algorithm to simultaneously optimize occupant movement guidance to balance comfort needs with energy efficiency. DigiGuide is validated using two realistic largescale scenarios: a co-working open space and an airport in Paris, France. Results demonstrate that DigiGuide achieves an average of 18.2% lower discomfort with 8.6% lower energy consumption compared to baseline approaches.