Towards Detection of Faulty Traffic Sensors in Real-Time

Detecting traffic events using the sensor network infrastructure is an important service in urban environments that enables the authorities to handle traffic incidents. However, irregular measurements in such settings can derive either from faulty sensors or from unpredictable events. In this paper, we propose an efficient solution to resolve in real-time the source of such irregular readings by examining the correlation and the consistency among neighbor sensors and exploiting the wisdom of the crowd. Our experimental evaluation illustrates the efficiency and practicality of our approach.