AI-IoT Solution for Railway Train Collision Prevention on Identical Tracks and Animal Detection

It is an IoT-based system that detects and prevents animal incidents Utilizing cutting-edge sensors and continuous monitoring on railway tracks to minimize the risk of train accidents involving animals has been a notable issue. The proposed system integrates various sensors such as LIDAR, infrared (IR), ultrasonic, and vibration sensors with an ESP32 microcontroller to detect animals and obstacles on the tracks. The system constantly observes the track and transmits the data to a mobile application (Blynk) and a web interface for real-time monitoring. The LIDAR sensor measures the distance to objects on the track, while the IR sensor detects the heat signature of the animals. The ultrasonic sensor detects obstacles in close range, and the vibration sensor detects vibrations due to trains, disturbances, etc. When an anomaly, such as an animal, is detected, the system immediately alerts the operator via the Blynk app and provides a notification on the web interface. The ESP32 CAM captures an image of the detected object for visual confirmation. The ESP32 microcontroller facilitates real-time processing and decision making, while the Blynk app provides an intuitive interface for notifications and sensor data visualization. The Web interface allows operators to monitor multiple track sections, access live sensor data, and remotely manage the system. It will save the animals on the tracks and improve railway safety by providing efficient real-time warnings and allowing immediate intervention. Using low-cost IoT components, the system provides a scalable and practical solution to reduce animal-related incidents, contributing to safer and more efficient rail transport.