• NEHA
• AVINASH
• HARSHAN M J
• AMRUTHA P
• PRIYADARSHINI V

This project proposes a smart railway gate control system integrated with emergency vehicle detection using IoT and deep learning technologies. An ultrasonic sensor positioned 200 meters away detects an approaching train, while a camera at the railway gate employs a YOLO-based object detection model to identify ambulances or other emergency vehicles. Depending on four real-time scenarios, the system automatically controls the servo motor, LEDs, buzzer, and LCD display to manage gate operation and ensure safety. The proposed system allows priority passage for emergency vehicles without compromising train movement. By combining sensor data with AI-driven decision-making, it minimizes human error, reduces accidents at unmanned railway crossings, and enhances response time for emergency services, contributing to the development of intelligent transportation and smart city infrastructure.

- IoT (Internet of Things), DL (Deep Learning), YOLO (You Only Look Once), EV Detection (Emergency Vehicle Detection).

"Emergency vehicle priority system in railway crossing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 12, page no.a85-a93, December-2025, Available :http://www.jetir.org/papers/JETIR2512011.pdf

"Emergency vehicle priority system in railway crossing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 12, page no. ppa85-a93, December-2025, Available at : http://www.jetir.org/papers/JETIR2512011.pdf