AI-Driven Ambulance Dispatching and Routing for Resilient Emergency Medical Services
Supervisor Name
Ahmed Alsalibi
Supervisor Email
asalibi@israa.edu.ps
University
Israa University - Gazaq
Research field
Artificial Intelligence
Bio
AI researcher, academic leader, and digital education specialist with more than 10 years of experience in higher education, research, and institutional digital transformation. Currently serving as Dean of the Faculty of Engineering and Information Technology at Al-Israa University – Gaza, where I lead initiatives related to online learning, academic development, and technology-enhanced education. My academic and research background combines Computer Science, Artificial Intelligence, IoT systems, healthcare technologies, and intelligent decision-support systems. I have published research in peer-reviewed international journals and contributed to interdisciplinary work involving AI-driven healthcare applications, smart systems, and digital technologies.
Description
This project is inspired by the severe challenges faced by Emergency Medical Services (EMS) during the war in Gaza, where ambulance shortages, damaged and inaccessible roads, disrupted communications, and reduced healthcare capacity frequently delayed or prevented emergency response. These conditions highlighted the need for better methods to manage extremely limited emergency resources and motivated the development of this research idea. The project investigates how Artificial Intelligence (AI), optimization, and simulation techniques can support ambulance dispatching and routing in environments where resources and infrastructure are limited or disrupted. The proposed framework will consider emergency demand, ambulance availability, road-network conditions, travel time, and healthcare-facility accessibility when assigning and routing ambulances. Under supervision, the undergraduate student will conduct a focused literature review, prepare or generate suitable EMS and road-network datasets, implement baseline ambulance-dispatching and routing methods, and evaluate selected AI- or optimization-based approaches. The student will also construct simulation scenarios reflecting conditions observed in Gaza, such as reduced ambulance fleets, road closures, inaccessible areas, changing emergency demand, and partial availability of healthcare facilities. The proposed methods will be evaluated using indicators such as ambulance response time, geographic coverage, vehicle utilization, and the percentage of emergency cases reached within an acceptable time. The project will also explore how improvements such as reopening roads, restoring healthcare facilities, or increasing ambulance availability could affect EMS performance. Expected outputs include a structured dataset, a simulation or prototype system, comparative experimental results, and a final technical report. If the results are sufficiently strong, the project may also contribute to a conference or journal publication.