Vehicle detection and classification is an important and demanding application of WSN. The idea of utilizing small, almost invisible sensor nodes, equipped with a variety of passive and active sensors, for intrusion detection, force protection and border surveillance, though not new, remains fascinating. This project presents vehicle classification using acoustic signal and its FPGA implementation. For feature extraction TESPAR coding used to produce simple and fixed size matrices which are used for classification purpose. Classification is accomplished by using ANN. It is implemented on FPGA.
TRIVEDI, ANIKET U.
"HARDWARE IMPLEMENTATION OF NEURAL NETWORK FOR VEHICLE CLASSIFICATION USING FPGA,"
International Journal of Electronics Signals and Systems: Vol. 2
, Article 13.
Available at: https://www.interscience.in/ijess/vol2/iss2/13