The Role of Artificial Intelligence in Resource Distribution During Humanitarian Crises: A Case Study of IDP Camps in Borno State
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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
- To analyze the use of AI tools in resource distribution during humanitarian crises in IDP camps in Borno State.
- To evaluate the impact of AI on the efficiency and equity of resource distribution.
- To identify barriers to the adoption of AI in humanitarian logistics.
1.4 Research Questions
- How are AI tools used in resource distribution during humanitarian crises in Borno State?
- What is the impact of AI on the efficiency and equity of resource distribution?
- What challenges hinder the adoption of AI in humanitarian logistics?
1.5 Research Hypothesis
- AI significantly improves the efficiency of resource distribution in IDP camps.
- AI enhances the equity of resource allocation during humanitarian crises.
- Limited funding and technical expertise are barriers to AI adoption in humanitarian logistics.
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
- Humanitarian Crises: Situations requiring urgent assistance due to conflict or natural disasters.
- Internally Displaced Persons (IDPs): Individuals displaced within their own country due to crises.
- Resource Distribution: The allocation and delivery of essential goods and services.
- Predictive Analytics: AI tools used to forecast needs and optimize resource allocation.
- Supply Chain Management: The coordination of logistics to deliver resources efficiently.
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