AAAR 37th Annual Conference October 14 - October 18, 2019 Oregon Convention Center Portland, Oregon, USA
Abstract View
A Physical-property Based Method to Characterize Low-cost Sensor
MEILU HE, Nueraili Kuerbanjiang, Suresh Dhaniyala, Clarkson University
Abstract Number: 685 Working Group: Air Quality Sensors: Low-cost != Low Complexity
Abstract Low-cost sensors, based on optical sensing of particles, have become very popular for air pollutant monitoring in indoor and outdoor environments. While we have a good understanding of the general physics underpinning these sensors, we lack a direct understanding of their specific response characteristics as a function of particle type, size, concentration, etc. Most applications currently rely on machine learning models built with field data at a certain location and time period. But outside the calibration region and time period, significant errors could be resulted. Here, we study a popular low-cost sensor – Plantower PMS5003 – to determine the detection characteristics of its different channels as a function of particle properties. The sensor signals were obtained for a range of test particle properties and the measurements were compared to research-grade instruments, and the signals were then analyzed to obtain the sensor channel transfer functions. The sensor transfer function allows us to understand the particle size- and composition-dependence of the signal in the different channels and helps in improving the accuracy of measurements made with these sensors. We will present our experimental approach, analytical techniques, and the obtained sensor transfer functions in our presentation.