Our project aims to solve the problem causing derailments and prevents subsequent accidents. The two major causes of derailments, i.e, the misjudgment of speed-weight and the faulty tracks.

Our proposed solution consists of two main features :

• Controlling speed according to the dynamic weight (The historical data of speed vs. weight is fed into the artificial neural network connected to the server and areal time comparison of actual and predicted speed is displayed on the app.)
• Detection of the faulty tracks (Voltage is passed through the tracks, sectionally. It is then compared with the initial value and in case of inequality, the fault is detected and the data is sent back to raspberry pi.)

A monitoring app keeps a track of the train activities and subsequent reschedules. Authorities can see the live status, track the faults in the map and check the reschedules.