Intelligent Agents to Improve Thermal Satisfaction by Controlling Personal Comfort Systems Under Different Levels of Automation

Abstract

Heating, ventilation, and air conditioning (HVAC) systems account for 43% of building energy consumption, yet only 38% of commercial building occupants are satisfied with the thermal environment. The primary reasons for low occupant satisfaction are that HVAC operations do not integrate occupant comfort requirements nor control the thermal environment at the individual level. Personal comfort systems (PCSs) enable local control of the thermal environment around each occupant. However, full manual control of PCS can be inefficient, and fully automated PCS reduces an occupant’s perceived control over the environment, which can then lead to lower satisfaction. A better solution might lie somewhere between fully manual and fully automated environmental control. In this article, we describe the development and implementation of an Internet-of-Things (IoT)-based intelligent agent that learns individual occupant comfort requirements and controls the thermal environment using PCS (i.e., a local fan and a heater). We tested different levels of automation where control is shared between an intelligent agent and the end user. Our results show that PCS use improves occupant satisfaction and including some level of automation can improve occupant satisfaction further than what is possible with manually operated PCS. Among the levels of automation investigated, inquisitive automation, where the user approves/declines the control actions of the intelligent agent before execution, led to highest occupant satisfaction with the thermal environment.