Fault diagnosis system for low-cost air pollution sensors - Marathe, Sumukh; Nambi, Akshay, Nishant Shrivastava; Manohar, Swami; Sutaria, Ronak (ACM SenSys demo, 2020)
Fine-grained air pollution monitoring is a fundamental step towards curbing pollution levels. This is sought to be achieved by the large-scale deployment of low-cost sensors at high spatio-temporal resolution. Due to the nature of these deployments, in-the-wild and in harsh environments, sensors are prone to failures and hence ensuring data reliability is challenging. Furthermore, detecting a fault by analyzing the sensor data using existing data-centric approaches is non-trivial. This demonstration presents a sensor fault diagnosis system that employs the current signature of the sensor to address data reliability issues. The current signature captures the electrical characteristics of the hardware components enabling accurate detection and isolation of faults in low-cost pollution sensors.