The vehicle classification based on neural networks in intelligent transport systems

This article is aimed to new methods of measurement, transfer and processing of data from complex system of FibreBragg Grating (FBG) sensors. State of the art technologies and algorithms for vehicle recognition and categorisation in university campus are used. Content of the Article is divided into two parts. The first part is devoted to fibre optic FBG sensors and their basic properties. The second part ofarticle is dedicated to visual data processing by neural networks for visual vehicle categorisation as visual confirmation of data from the fibre Bragg grating sensor arrays. Experimental results show that using AlexNet neural network can be achieved an accuracy for categorization of vehicles of 87.1%. Research is done under the grant project dealing with coexistence of photonic sensor systems and photonic networks within the Internet of Things.