Optimizing Disaster Relief: AI and Drone Technology in the Maghreb Region

Maghreb countries including Morocco, Algeria, Tunisia, and Libya have been hit by natural disasters in the past decade such as earthquakes, floods, and forest fires. Additionally, illegal immigration from North Africa to Europe is a significant issue, as each year many immigrants lose their lives in the Mediterranean and the desert due to the delayed detection of people in danger. Artificial Intelligence assists disaster rescue efforts by employing disaster-focused drones. This includes victim detection through thermal or visual imagery in collapsed buildings, fires, or floods, gas leakage detection, fire detection, and landslide search and rescue planning in challenging environments. The purpose of the research is to introduce framework combines Reinforcement Learning (RL) algorithm with Blockchain for AI-powered drones to enhance humanitarian duty’s response times and general efficiency, which would eventually strengthen the region’s crisis management systems. Moreover, blockchain can be utilized for novel use cases, as having centralized control for drone swarms in distrusting environments constitutes a single point of failure. While the use of RL to improve drone capabilities for disaster relief missions in Maghreb nations is investigated in this work. Drones may learn from past missions and adapt to different crisis conditions more effectively thanks to RL’s adaptive learning capabilities.