Paper Info
Title
Sensor Identification and Fault Detection in IoT Systems.
Abstract
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.
Year
DOI
Venue
2018
10.1145/3274783.3275190
SenSys '18: The 16th ACM Conference on Embedded Networked Sensor Systems Shenzhen China November, 2018
Keywords
Field
DocType
IoT system,Fault detection,Sensor identification,Reliability
Voltage response,Fidelity,Software deployment,Fault detection and isolation,Computer science,Internet of Things,Real-time computing
Conference
ISBN
Citations 
PageRank 
978-1-4503-5952-8
0
0.34
References 
Authors
4
6
Name
Order
Citations
PageRank
Tusher Chakraborty186.03
Akshay Uttama Nambi262.21
Ranveer Chandra34089268.00
Rahul Sharma4426.45
rahul anand sharma5183.49
Zerina Kapetanovic6664.93