IoT based rail track health monitoring and information system

This paper describes an Internet of things (IoT) based track monitoring system for increasing the comfort of rail track transportation. Usually, rail tracks are inspected only at midnight and also the inspection is carried out only once in a month or lesser. Unfortunately, any emergency issues not detected within the stipulated time leads to train derailment and other safety concerns. Hence in-service vehicle has been introduced to increase the safety of train transportation. In this paper, track irregularities are detected using bogie and car body acceleration measurements and these measurements is further optimized using particle swarm optimization algorithm (PSO). The proposed system is compared with the conventional track geometry measurement system. The monitoring and control information can be sent through IoT. Simulation results are performed for two different speed scenarios and it shows that the proposed system produces better results than the traditional track geometry measurement system and the effectiveness of the proposed method.