Title: Intelligent Sorting Systems for Humanitarian Data: Leveraging AI for Efficient Emergency Response"
Authors: Heba I.A. Alqedra. And Sany S, Abu-Naser
Volume: 9
Issue: 6
Pages: 29-40
Publication Date: 2025/06/28
Abstract:
The protracted conflict in Gaza has significantly intensified humanitarian crises, posing severe challenges to relief operations due to resource scarcity, logistical obstacles, and the complexities imposed by the blockade. This study proposes the development of an intelligent sorting system utilizing advanced artificial intelligence (AI) methodologies to prioritize, classify, and manage critical humanitarian data efficiently in real-time. Designed to meet the specific demands of crisis response, this AI-driven system organizes and categorizes essential data streams-including urgent aid requests, resource allocation data, and public health information-while addressing logistical and infrastructural barriers typical of conflict zones. Leveraging machine learning algorithms, the system identifies and ranks high priority needs dynamically, supporting accurate resource distribution and prompt emergency interventions. Findings from this study indicate improvements in response times and overall resource management efficiency, highlighting the transformative potential of AI in humanitarian data handling. Furthermore, the study presents a scalable framework adaptable to other crisis-affected regions worldwide, enhancing the management of complex data demands under extreme conditions. The system's scalability underscores its relevance as an innovative tool for advancing humanitarian logistics and emergency response in volatile, high-risk environments."