• Aafreen Marzuqa.A
• Shameem Fathima.M.J
• Sonya.A

Railway accidents involving humans and animals on tracks often result in fatalities due to the high speeds of approaching trains, necessitating an advanced safety mechanism that integrates multiple technologies for real-time obstacle detection and alerting authorities. The lack of an efficient and timely detection system increases the risk of collisions, making it crucial to develop a proactive solution to identify and mitigate potential hazards. Utilizing cameras, PIR sensors, and a Raspberry Pi-based processing unit, the system accurately identifies obstructions. The processing unit handles data and coordinates responses, while communication protocols like MQTT and HTTP ensure efficient data transmission. YOLOv8, a deep learning algorithm, enables precise object detection. An LCD display is used to show whether an object is detected on the track or not, providing instant on-site status updates. Detected objects or movements trigger immediate alerts, which are relayed to nearby railway control centres and railway police stations, significantly enhancing response time and enabling proactive measures to mitigate potential hazards. The system leverages GPS and live camera surveillance to facilitate seamless communication between railway control centres and law enforcement, addressing one of the most persistent challenges in railway safety. By integrating advanced technologies, this solution not only reduces accidents but also ensures a safer railway environment for both humans and animals, representing a significant advancement in railway safety.

Railway accidents, Obstacle detection, Safety mechanism, YOLOv8 Classification Model, PIR Sensor Monitoring, Raspberry Pi Automation, GPS -enabled Alert System.

"Enhancing Railway Safety using YOLOv8 for obstacle detection and accident prevention", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 4, page no.m157-m164, April-2025, Available :http://www.jetir.org/papers/JETIR2504C20.pdf

"Enhancing Railway Safety using YOLOv8 for obstacle detection and accident prevention", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 4, page no. ppm157-m164, April-2025, Available at : http://www.jetir.org/papers/JETIR2504C20.pdf