• MS V PREETHA
• A GOWTHAM
• R ASHWIN BAALAJI
• K GOKULAKRISHNAN

The "Emergency Vehicles Detection while arrival of ambulance and fire engine using machine learning" uses machine learning to quickly detect ambulances and fire engines during an emergency. It uses visual signals from strategically positioned cameras to identify emergency vehicles based on distinguishing characteristics such as flashing lights and sirens. This automatic detection procedure reduces reaction times for emergency personnel, allowing them to get at the situation more swiftly and effectively. The system's user-friendly interface sends real-time updates to emergency responders and other drivers, therefore improving road safety. By limiting human error and improving route planning, technology decreases delays and increases emergency service performance. This novel technique is consistent with existing emergency response strategies that emphasize integrating technology to improve results. Finally, the system contributes to establishing safer communities by permitting faster and timely emergency response times.

Emergency vehicles,detection system,machine learning, response time, user-friendly interface,safety,technology,route planning,effectiveness,community safety.

"EMERGENCY VEHICLES DETECTION WHILE ARRIVAL OF AMBULANCE AND FIRE ENGINE USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 3, page no.f535-f541, March-2024, Available :http://www.jetir.org/papers/JETIR2403564.pdf

"EMERGENCY VEHICLES DETECTION WHILE ARRIVAL OF AMBULANCE AND FIRE ENGINE USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 3, page no. ppf535-f541, March-2024, Available at : http://www.jetir.org/papers/JETIR2403564.pdf