A Smart Rail Guard IoT Based Railway Track Obstacle Detection and Alert System Using Deep Learning Techniques and Computer Vision

Most accidents on the railway be it from obstructions such as fallen trees, stray vehicles, or wandering animals severely compromise safety. These issues need immediate attention, which is why our project “Smart Rail Prevent: IoT-Based Railway Track Obstacle Discovery Along with Alert System Using Deep Learning Strategies and Computer Vision” combines the best features of cloud computing, automated AI, and IoT technology to provide an effective barrier identification, solution, and alert system in real-time. Utilizing advanced computer vision and Convolutional Neural Networks (CNN) allows our system to stream and analyse live footage of the railway lines in order to systematically identify and classify any obstructions present. The visual data is supplemented by ultrasonic and infrared sensors when visibility is low. An ESP32 module locally processes the data captured while GPS integration provides exact location information on the obstructions. Obstructions are categorized based on information received, and transmitted to the relevant railway authorities using multiple IoT communication channels: GSM, LoRa, and Wi-Fi. In addition, cloud user dashboards on ThingSpeak enable users real-time monitoring of detection data, including historical data, as well as full and easy customization.