Measuring mean radiant temperature for indoor comfort assessment using low-resolution optical sensors

Abstract

Measuring and controlling human thermal perception-related parameters within the built environment is crucial for ensuring occupant comfort, productivity, well-being, and reduced energy consumption. The human body is sensitive to both convective and radiative thermal effects. Mean radiant temperature represents the comprehensive radiant thermal impact individuals perceive in their surroundings. However, no feasible, robust, and ergonomic methods exist for real-time mean radiant temperature measurements in the built environment. In this paper, we introduce a method for measuring longwave mean radiant temperature utilizing low-resolution infrared temperature sensors. The approach utilizes projective transformations to derive surface temperature distributions from raw infrared thermal data. Our technique is tested in four diverse real-world environments, encompassing different heating methods and room configurations, resulting in a maximum error of ±0.5 °C. The results demonstrate the method’s repeatability and robustness across diverse room sizes, layouts, and scenarios, suggesting its potential integration into room thermostats to improve human comfort while optimizing building energy utilization. We anticipate that this method will revolutionize sensing in the built environment by eliminating the requirement for costly hardware. This study introduces a method for real-time mean radiant temperature measurement, a key parameter representing the thermal comfort perceived by individuals. This method achieves ±0.5 °C accuracy in diverse environments, showing potential for integration into energy-efficient building systems.

Topics & Concepts