Automated Track Monitoring System using Object detection and Ultrasonic Sensor for Railway safety

An automated track monitoring system intended to improve railroad safety is presented in this project. The device uses a GPS module and an ultrasonic sensor to track conditions and identify deviations in real-time. It detects deviations beyond predefined criteria, obtains GPS coordinates, and measures distances to surrounding objects. When deviations occur, the system notifies the operator and sends GPS locations for immediate assistance, aiming to reduce risks and enhance train safety. Additionally, the system includes an object detection and alert mechanism using computer vision. This component employs a pre-trained deep learning model via OpenCV to identify objects on or near the tracks in real-time. If an object remains in the detection zone for over a predefined duration , an email alert is triggered. This ensures prompt reporting of potential hazards, further enhancing railway safety.