An IoT based rail track condition monitoring and derailment prevention system

This paper proposes a new method for monitoring the irregularities in railway tracks by updating the status of the tracks in the cloud. The IoT based Railway Track Monitoring System (IoT-RMS) is proposed for monitoring the health of the railway track. The system identifies any abnormality in the tracks at an early stage. These abnormalities are rectified before they develop for smoother transportation. The micro electro mechanical system (MEMS) accelerometers are placed in the axle box for measuring the signal. It becomes hard to identify the exact location of abnormalities when the global positioning system (GPS) falters due to signalling issues. In this paper, a new hybrid method is proposed for locating irregularities on a track; even in the absence of a GPS signal. Pre-processing of the GPS signal is carried out effectively because the sensors used in IoT-RMS are capable of functioning in a high noise environment. The IoT-RMS updates the location of the abnormality in the cloud and shares it with other trains that will be passing through that location. As a result, the drivers of trains respond accordingly and avoid derailment. An experimental setup has been developed for a study of the performances for four different abnormal cases, and the result shows the effectiveness of the proposed system.