Electric trains are made up of various safety-sensitive systems, these systems are safety-sensitive in that a simple loophole can compromise the trainâ€™s safety and may lead to catastrophic incidents and accidents. These systems are usually maintained regularly at set schedules and frequencies to keep the train in good working conditions. This type of maintenance is called preventive maintenance. However, cases may occur where a system abnormality may occur or be altered before the pre-set preventive maintenance. This may or may not cause an immediate effect but can be a root cause of a major system failure and hence leading to equipment damage and accidents. What is currently being done in case of such a scenario is that the driver who may or may not technically upright make a call to the technical department to report any abnormality on the train. This method is time-consuming and it would require a detailed explanation to correctly diagnose the real cause of the problem.rnTherefore this research investigates the effect of the Internet of Things (IoT) to improve the systemâ€™s traction safety through real-time conditions monitoring over the LTE-R network and internet communication channel, meaning it advocates for predictive rather than preventive maintenance. Upon simulation of the IoT system, this research indicates an improvement in the time parameters of the average duration it would take for the technical team to get the information about a certain fault. The improvement was found out to be 97.4%, from approximately 1.5 hours to 0.02 hours. The other parameters of meantime to repair (MTTR) and meantime before failure (MTBF) are not affected by this idea of including IoT technology. This was achieved by constantly monitoring the system vital parameters in real-time and sending an instant e-mail and SMS notification in case of any fault or abnormality the system detects from the big data generated from the sensor nodes.