1.1 Background of the Study
Humanitarian crises, particularly in conflict-affected regions like Borno State, require efficient resource distribution to address the needs of Internally Displaced Persons (IDPs). Traditional resource distribution systems often face challenges such as misallocation, delays, and inadequate tracking. Artificial Intelligence (AI) has emerged as a transformative tool for optimizing resource allocation, enhancing supply chain management, and ensuring equitable distribution.
AI systems use predictive analytics, real-time monitoring, and optimization algorithms to analyze data on population needs, resource availability, and logistics. For IDP camps in Borno State, these capabilities are critical in addressing food insecurity, healthcare needs, and shelter allocation (Ahmed & Yusuf, 2025). This study explores the role of AI in improving the efficiency and effectiveness of resource distribution during humanitarian crises in Borno State.
1.2 Statement of the Problem
Resource distribution in IDP camps often suffers from inefficiencies, including delays, duplication, and inequitable allocation. Despite the potential of AI in addressing these issues, its adoption in humanitarian logistics remains limited, primarily due to technical, financial, and organizational barriers.
1.3 Objectives of the Study
1.4 Research Questions
1.5 Research Hypothesis
1.6 Significance of the Study
The findings of this study provide valuable insights for humanitarian organizations and policymakers on leveraging AI to optimize resource distribution and improve crisis response.
1.7 Scope and Limitations of the Study
This study focuses on IDP camps in Borno State and the use of AI in resource distribution. Limitations include access to proprietary logistics data and variability in humanitarian crisis contexts.
1.8 Operational Definition of Terms
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