A Comprehensive Approach to WSN-Based ITS Applications: A Survey

In order to perform sensing tasks, most current Intelligent Transportation Systems (ITS) rely on expensive sensors, which offer only limited functionality. A more recent trend consists of using Wireless Sensor Networks (WSN) for such purpose, which reduces the required investment and enables the development of new collaborative and intelligent applications that further contribute to improve both driving safety and traffic efficiency. This paper surveys the application of WSNs to such ITS scenarios, tackling the main issues that may arise when developing these systems. The paper is divided into sections which address different matters including vehicle detection and classification as well as the selection of appropriate communication protocols, network architecture, topology and some important design parameters. In addition, in line with the multiplicity of different technologies that take part in ITS, it does not consider WSNs just as stand-alone systems, but also as key components of heterogeneous systems cooperating along with other technologies employed in vehicular scenarios

Distance based decision fusion in a distributed wireless sensor network

Abstract. Target classification fusion problem in a distributed, wireless sensor network is investigated. We propose a distance-based decision fusion scheme exploiting the relationship between sensor to target distance, signal to noise ratio and classification rate, which requires less communication while achieving higher region classification rate when compared to conventional majority-vote based fusion schemes. Several different methods are tested, and very encouraging simulation results using real world experimental data samples are also observed.