A Computer-Aided Modeling and Measurement System for Environmental Thermal Comfort Sensing

Predicted mean vote (PMV) is a well-known thermal comfort index with four environmental variables (air temperature, relative humidity, air velocity, and average radiation temperature) and two human factors (metabolic rate and clothing thermal resistance). This paper presents a novel computer-aided thermal comfort measurement system with PMV, which combined the advanced sensors with the virtual instrument technology. The system software is developed using the LabVIEW platform. The measured data can be transmitted to the server-computer in a data center and displayed on a web page through the Internet. The impact of the measurement error of each environmental variable on PMV is analyzed via MATLAB. The system tests were conducted under the certain environmental conditions and Monte Carlo method is deployed to analyze the PMV measurement uncertainty. The experimental results show the feasibility and effectiveness of the proposed system, and confirm that the measurement uncertainty of PMV is not a constant, and varies with the environment changes.