Abstract

Optimization of ambulance scheduling is a crucial factor in improving emergency responses to preserve lives. The present study introduces a novel methodology for ambulance scheduling, which incorporates the Internet of Things (IoT) to enhance resource utilization and reduce response times in emergency medical services. We have devised a dual-level program model consisting of two sub-models. The first sub-model is designed to allocate ambulances to different districts based on geographic and traffic data. The second sub-model is responsible for determining the order of visit priorities within each district, aiming to minimize the overall time required to respond to a case. Substantial enhancements in responsiveness and resource utilization were observed in comparison to traditional approaches. The present system, which is enabled by the IoT, exhibits real-time adaptability in crisis management. We present results that demonstrate the revolutionary capacity of IoT applications in Emergency Medical Services (EMS) and offer practical insights for healthcare organization managers.