On-board Image Processing in Wireless Multimedia Sensor Networks: a Parking Space Monitoring Solution for Intelligent Transportation Systems

Wireless Sensor Network (WSN) has been adopted during the years for a large set of applications, such as environmental monitoring, industrial automation, process control, and, more recently, for video surveillance and multimedia streaming applications. Surveillance applications – like traffic monitoring, vehicle parking control, and intrusion detection – involve monitoring of the environment in order to detect and interpret the activities of relevant objects and their behavior. These applications demand real-time images from the scene in order to collect relevant information. Wireless Multimedia Sensor Network (WMSN) provides a low-cost and flexible solution for distributed video surveillance based on low-power autonomous smart camera nodes. Image processing in the WMSNs scenario is very challenging due the necessity to store and process huge amount of visual data on energy and resource constrained sensor nodes. To deal with this problem, many researchers have mainly proposed distributed in-network processing and low-complexity computer vision techniques to be executed on-board. In this chapter we focus on the development of on-board image processing techniques for detecting the occupancy status of parking spaces. The developed techniques are presented as an effective solution for vehicle parking lot monitoring applications in the domain of Intelligent Transportation Systems (ITS). Performance results show as the developed image processing techniques are able to reach 99.92% sensitivity and 95.59% specificity in detecting the parking spaces occupancy status. Moreover, in the chapter a full implementation of the developed algorithms in embedded devices is presented and their overall performance evaluated in terms of execution time and memory occupancy.