IoT-Controlled Railway Gate System With ML Object Detection Approach

Abstract

The growing demand of internet of things (IoT) has rendered advancement in the practical fields towards society. In spite of recent advancements and cost effective IoT solutions for smart railway infrastructure, presently, most of the railway gates in India are opened and closed manually. This is a time-consuming process. It is an error-prone system and raises the accident probability. This chapter evaluates and demonstrates the applicability of IoT to resolve the problem of unmanned automatic railway crossing. The aim is to propose a prototype that will control with the help of microcontroller board, IoT sensor integration, and integrating it to machine learning-based image analysis to detect the intermediate real time obstacle (obstacle on the track). This kind of IoT system will also invite potential attacks, and traditional security countermeasures can be inefficient in dynamic IoT environments. So open challenges related to IoT security threats and emerging security mechanisms for security of the proposed smart railway crossing system are also elaborated.