IoT Based Rail Track Joints Monitoring System Using Cloud Computing Technology

This paper describes a real time track monitoring system that access and monitor the rail track joints based on Internet of things (IoT). The health state of the track joint is inspected once a month manually and also the inspection is carried out during midnight. The critical situations must be detected and solved with in a specific time otherwise it leads to heavy loss. In this paper, two accelerometers are mounted in the vertical and lateral direction of the axle-box and two different cases has been considered for simulation. The measured signal which is received from the accelerometer has been optimized using honey bee optimization (HBO) technique and the result is compared with conventional track geometry measurement system. The measured values are updated simultaneously in the cloud. The server manages this situation and sends the information to the control room. Simulation has been performed for two different speed of the train and it shows that the performance of the proposed method is better than for the track measurement system. To summate, the proposed system has been used to monitor and update the track parameters continuously and the same was tested using Raspberry Pi.