• Rohit Adaram Wagadi

The emergency vehicle priority (EVP) system is a time necessity to reduce the transit time of emergency vehicles in cities. These cities are important economic centres and are therefore among the most densely populated cities in the world. Due to many such problems, ambulances cannot reach patients and hospitals on time. This white paper proposes a system that can help accurately identify ambulances and establish a makeshift hard shoulder on the route they should take. This system relies on a neural network-based siren classifier to detect ambulances using speech processing. The overall accuracy of the siren classifier was 97.2%. When an ambulance is detected, this information is relayed to a network of Internet of Things (iot) devices that activate visual indicators of the ambulance's route. Traffic on these roads may begin to form a temporary breakdown lane when the visual indicator is activated. A network of iot devices consists of host and station/node devices in a chain-like connection where all devices communicate over a local wifi network. The host gets information about the ambulance from neural networks and a mobile app. The host then sends this information up the chain to other node devices. It is hoped that our proposed system will reduce ambulance travel time, enabling more rapid treatment of accident victims, heart attack patients, etc.

"How AI Helps in Emergency Service?", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 12, page no.e281-e286, December-2022, Available :http://www.jetir.org/papers/JETIR2212439.pdf

"How AI Helps in Emergency Service?", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 12, page no. ppe281-e286, December-2022, Available at : http://www.jetir.org/papers/JETIR2212439.pdf