A Hybrid Optimal Approach for Efficient Remote Monitoring and Avoidance of Train Collisions

Abstract

Almost all categories of people would travel in trains, loads of material were to be transported, and various industry-related loads were carried for their business-oriented purposes including government goods to distribute to the state-wise needy of the people. This scenario requires the safety of train travel. In recent scenarios the world and India, have been experiencing train accidents that have led to the loss of many innocent people, as well as loss to specific organizations, and governments. There may be many ways to avoid accidents, but an effective and accurate system is needed. The significant approaches used are Positive Train Control (PTC), Collision Avoidance Systems (CAS), Automated Train Operation (ATO), and Advanced Signaling Systems along with traditional approaches. These scenarios demand a novel approach with maximum accuracy by overcoming the difficulties such as identifying potential equipment failures, and enhanced communication systems for seamless coordination of trains and control centers. The key benefits are comparison against existing methods, proactive risk assessment, and predictive maintenance to enhance safety standards, optimize operations, and ensure sustainability. In this, IoT devices like sensors, with network support are key functionalities in avoiding of train accidents.