Characterizing and Calibrating Low-Cost Wearable Ozone Sensors in Dynamic Environments

The increased interest in utilizing wearable technologies for ubiquitous monitoring of human physiological, behavioral, and environmental parameters has come to force, including the rise of cost-effective, low-power gas sensors that enable personalized air quality monitoring in daily life. Despite the advances in system design of wearable gas sensor nodes, the characteristics of these sensors under real-world conditions have not been comprehensively examined, specifically the influences of environmental dynamics on sensor calibration and sensitivity. In this paper, we propose ozone sensor calibration algorithms that exploit dynamic relative humidity (RH) and temperature sensor measurements to enhance the quality of ozone measurement. The contributions of this study are 1) characterization of the influences of RH and temperature dynamics on low-cost metal oxide ozone sensors, and 2) calibration algorithms with considerations of sensor characteristics. Experimental results demonstrate the efficacy of the proposed methods in characterizing and calibrating the low-cost wearable ozone sensors.