A Robust Parking Detection Algorithm Against Electric Railway Magnetic Field Interference

Abstract

Wireless magnetic sensor networks (WMSNs) offer an effective and efficient low-cost alternative for real-time parking space monitoring. Current algorithms used for parking space detection based on the WMSNs have been well studied but not without eliminating the geomagnetic field interference. Electric railway systems, such as subways and light rail systems, produce magnetic field radiation that interferes with the geomagnetic field. The electric railway magnetic field interference has increased and is prominent in urban settings; therefore, it is imperative to filter out the interference in order to increase the detection accuracy. This paper proposes an algorithm for parking space detection, which can effectively eliminate the geomagnetic background interference. We solve the parking detection problem through signal filtering technology. Based on mathematical morphology, we designed two filters for extracting morphological structures from interfered magnetic signals. The experimental results verify that the proposed algorithm is more accurate than the existing algorithms.