A Smart Emergency Ambulance Hiring System for Real-Time Medical Response

Abstract

In rapidly expanding cities and remote rural areas, delays in emergency medical response are a prevalent issue with the potential to result in death. Traditional ambulance dispatch strategies rely on manual calls, unclear location information, and uncoordinated communication between emergency responders, resulting in inefficient distribution and sluggish services. This study suggests a Smart Emergency Ambulance Hiring System (EAHS) that employs real-time location tracking, mobile-user interfaces, cloud computing, and intelligent dispatching algorithms to transform emergency service ordering and delivery. The system involves a mobile application for users to request ambulances, with GPS capability for location tracking, and connected to a cloud backend that allocates the nearest available ambulance through geofencing and smart routing. Ambulance drivers carry a special application that provides navigational guidance and status updates, while administrators may monitor operations via a centralized dashboard. The prototype was deployed in a simulated city scenario and demonstrated 40% shorter response times versus conventional methods, with high user satisfaction ratings and reduced ambulances' idle times. The findings show that such smart systems can significantly improve the efficiency and responsiveness of emergency medical services. Key challenges such as network connectivity, data privacy, and digital literacy are addressed, as well as emerging areas such as AI-based demand forecasting and multilingual interfaces. This article presents a model for integrating digital technologies into EMS operations, especially in regions with systemic healthcare delivery problems. The scalability and modular design allows for adaptation across various geographies and health infrastructures, ultimately resulting in improved public health outcomes.