Objective: The train collision avoidance system (TCAS) is a synergic approach for intervention of train in danger zone using Internet of things. Methods: The proposed system surveillance the signal condition and observe the disobedience of the track signal. A sensor is placed beneath the track, which senses the pressure, temperature, altitude of the track. The presence of train is observed by heavy pressure, change in temperature, and altitude on the track. Eventually, the system notifies the intervention of train being in danger zone using Internet of things by ThingSpeak IoT platform. An alarm is given to the train side that blow through Beaglebone black using Wi-fi module and if locomotive pilot does not respond, then the train stops by controlling braking system. Findings: Track signal plays a paramount role in cognizance of train’s direction. The disobedience of signal results in collision, derailment, and conflict. It is mainly occurred due to human error or rigid climate conditions like fog, rain and affects thousands of lives. TCAS-IoT prevails the problem of overshooting the track signal and acknowledging the locomotive pilot about intervention of train in danger zone. Conclusion/Improvement: The proposed TCAS-IoT can avoid train collision and capable of taking action before collision or derailment of trains. It is a unique way to synthesize the intervention of train in danger zone and can save lot of precious lives. © Springer Nature Singapore Pte Ltd. 2018.