Collaborative Sensing-Based Parking Tracking System With Wireless Magnetic Sensor Network

Abstract

Wireless magnetic sensor networks provide a low-cost technology for the outdoor real-time parking tracking system. However, the magnetic sensor is susceptible to the interference caused by vehicles parked in adjacent spaces. Most existing detection systems are solely based on local sampled data from the sensor node and they are prone to high false and missed detection rates in the case of a low signal-to-noise ratio. This paper proposes a collaborative sensing parking tracking system by fusing the signals of the adjacent sensors to eliminate the interference. Sensor nodes convert magnetic signals into signatures represented by peak values, and then the base station computes the spatial relationships between adjacent signatures to identify parking event or interference. An experiment system includes sixty sensor nodes that were deployed in bay parking spaces. Experiment results verified that the proposed system has better detection accuracy than existing systems.