Wireless Sensor Network Based Train to Train Imparting System

Trains are well known as a reliable, affordable, and speedy means of transportation in metropolitan cities in India and around the globe. Though convenient and ever popular, train accidents in India are often blamed on human mistake. With the speed of trains high and the latency in human intervention, it is always a major task to prevent such crashes. This study suggests a proactive method of minimizing railway accidents by using Radio Frequency Identification (RFID) technology. The main goal of the suggested system is to forecast possible train collisions and notify the central control room or train drivers prior to an accident. There are few mechanisms in place to avoid train crashes at present, and thus the use of an advanced Anti-Collision Device (ACD) system is essential. The suggested train collision avoidance system combines RFID technology, Zigbee communication, machine learning, and artificial intelligence (AI) to improve railway safety. Every locomotive has an automated monitoring system, and the railway network is segmented into two-kilometer sections, each having a unique track number. RFID tags placed on the trains are scanned by onboard RFID scanners, and this information is processed by an AI system to check for the existence of other trains on the same path. When there is a possible collision, the system sends alarms to train controllers through Zigbee, and an automatic braking system is activated to halt the crash. This advanced system offers real-time collision detection and avoidance, vastly enhancing railway safety and minimizing the possibility of train collisions.