Vehicle Identification using Discrete Spectrums in Wireless Sensor Networks

We studied the possibility of using wireless sensor networks for vehicle identification in a large open field. This is exciting research in that it not only presents a challenge but has practicality. The challenge here is to develop algorithms and/or protocols for sensor nodes to execute a given task. Since each sensor node has limited computation and communication capabilities, these limitations prohibit the use of algorithms and/or protocols developed for conventional computers and networks. Each sensor is dispensable and easily deployable, it can do meaningful work when it is collaborated as a networked cluster; therefore it is very practical in application. Our goal is to identify vehicles in real time using acoustic signal sensors and wireless networks. Our contribution in this paper is three fold. First, we developed a simple vehicle sound identification algorithm enough to be implemented for capacity limited sensor nodes. Second, we proposed architecture and protocols of wireless sensor networks for vehicle identification using this developed sound classification algorithm. Third, we proposed a cooperation model among sensors to expedite the classification process. Our preliminary results show the proposed architecture and protocols are promising.