Streamlining occupant-centric HVAC operations through multi-modal infrared array sensing technology

Abstract

This study systematically evaluates a novel occupant-centric heating, ventilation, and air-conditioning (HVAC) control strategy that integrates multi-modal infrared (IR)-based sensing technology. The proposed system dynamically adjusts HVAC setpoints based on real-time occupant information, including presence, count and operative temperature. Unlike previous studies, which explored IR array sensors primarily for recognizing occupants in small-sized private spaces, this study integrates IR sensing into occupant-centric controls for systematic assessment. To accurately and promptly recognize occupant-related parameters, the proposed system incorporated multiple heat transfer mechanisms and advanced counting-based control strategies aimed at heating energy use without compromising adaptive comfort. A simulation model was developed to replicate an open office space (100 m²) in Michigan, validated with field measurements, and assessed using 2023 local weather data. Results showed that the multi-modal sensing technology achieved 95 % accuracy in detecting occupant presence and effectively calculated operative temperatures from background thermal data. The proposed OCC yielded a 33.7 % reduction in heating energy consumption, with a payback period of 8.1 years when using a 110° vision angle IR array sensor. However, while the multi-modal OCC outperformed baseline and presence-based two-position control strategies in energy savings, it exhibited the most pronounced negative impact on thermal comfort, with a 13.6 % adaptive comfort penalized percentage during the heating season. This finding highlights the inherent trade-off between energy efficiency and occupant comfort. The contribution of this study is the development and validation of a comprehensive control framework that leverages multi-modal sensing to enhance the intelligence, adaptability, and energy performance of occupant-centric HVAC systems.