Sensor Identification and Fault Detection in IoT Systems - Chakraborty, Tusher; Nambi, Akshay; Sharma, Rahul; Chandra, Ranveer; Manohar, Swami; Kapetanovic, Zerina (ACM SenSys (Demo), 2018)
The proliferation of Internet of Things (IoT) devices has led to the deployment of various types of sensors in the homes, offices, buildings, lawns, cities, and even in agricultural farms. Due to the diverse nature of IoT deployments and the likelihood of sensor failures in-the-wild, a key challenge in the design of IoT systems is ensuring the integrity, accuracy, and fidelity of sensor data. We present a system based on the Fall-curve primitive – a sensor's voltage response when the power is turned off – to characterize the sensor. A sensor's Fall-curve constitutes a unique signature using which it is possible to identify the sensor and also detect whether it is operating correctly or not. In this demo, we show Fall-curve in action to accurately detect and identify the sensors connected to an IoT device. Furthermore, we also show that Fall-curves can reliably detect various transient and permanent sensor faults in an IoT device.