MEDIDRONE: Optimizing Emergency Medical Deliveries Using Autonomous Drones

In Rio Arriba County, New Mexico, some rural communities are located far from hospitals and medical facilities. During emergencies, delivering essential medical supplies can be difficult because of long travel distances, limited road access, and challenging terrain. I want to investigate how autonomous delivery drones can help transport medical supplies faster and more efficiently to remote communities.

For my project, I plan to develop a computer simulation called MEDIDRONE that models emergency medical deliveries across Rio Arriba County. The simulation will include hospitals, rural communities, delivery locations, terrain, weather conditions, drone battery capacity, and package weight. I will use Python to create and compare different delivery strategies, including shortest-distance routes, energy-efficient routes, and routes that prioritize urgent medical deliveries.

My main research question is: How can autonomous drone delivery systems be optimized to reduce emergency medical supply delivery times while maintaining safety and battery efficiency in Rio Arriba County?

I plan to use high-performance computing to run thousands of simulated emergency scenarios involving different weather conditions, delivery distances, and medical supply demands. I will analyze the results by measuring delivery time, battery consumption, successful deliveries, and emergency response efficiency.

My goal is to identify the most effective drone delivery strategies and determine whether optimized autonomous drones could improve access to emergency medical supplies in remote communities. Through this project, I hope to demonstrate how computer science and supercomputing can help solve real-world healthcare transportation challenges in rural New Mexico.