Artificial Intelligence-Powered Optimisation of Food-Energy-Water Resource Allocation in Nigerian Internally Displaced Persons' Camps

• Ezekiel O. DARAMOLA

  Author

• Omolola A. OGBOLUMANI

  Author

The rising number of internally displaced persons (IDPs) in Nigeria, caused by insurgency, armed conflict, and climate-related disasters, has exposed serious weaknesses in how food, water, and energy are managed in IDP camps. Conventional manual distribution methods are slow, fragmented, and prone to shortages, over-allocation, and avoidable waste. This study addresses the problem by developing an Artificial Intelligence (AI)-enabled mobile decision-support system for resource allocation in Nigerian internally displaced persons camps. The mobile application provides a simple conversational interface that allows camp administrators to enter routine operational data on populations, stocks, water supply, and energy availability. The AI component processes these data to validate entries, estimate short-term needs, and recommend allocation plans that respect the interdependencies between food, energy, and water. The prototype was implemented with Flutter, Firebase, and the Gemini application programming interface (API), and evaluated against a manual planning baseline under four representative camp scenarios. The evaluation covered response time, usability, feasibility, transparency, explainability, auditability, and allocation outcomes. The results show that the AI-assisted approach produces structured allocation plans faster and with fewer avoidable stockouts than manual planning, while keeping human decision-makers in control of every recommendation. The work offers a practical foundation for operationalising the Food–Energy–Water (FEW) nexus at camp level in Nigerian internally displaced persons operations.

• 71_Daramola and Ogbolumani (2026)

Copyright (c) 2026 Ezekiel O. DARAMOLA, Omolola A. OGBOLUMANI (Author)

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.