Expert system prototype of food aid distribution

Area of Science:

• Information Science
• Artificial Intelligence
• Disaster Management

Background:

• International food aid distribution faces challenges in efficient monitoring and evaluation.
• Existing processes lack adaptive feedback mechanisms for timely intervention.
• Disaster relief organizations require improved tools for managing food aid operations.

Purpose of the Study:

• To develop a prototype expert system for monitoring and evaluating food aid distribution.
• To enhance the efficiency of international food relief organizations' operations.
• To create an adaptive feedback system for various stages of food aid delivery.

Main Methods:

• Data collection on monitoring and evaluation processes from international food-aid organizations.
• Development of a rule-based expert system prototype using CLIPS (C) software.
• Implementation of facts and heuristic rules for adaptive feedback within the Food Aid Monitor system.
• Validation of the prototype by expert panels assessing completeness, relevancy, consistency, correctness, precision, and usability.

Main Results:

• A functional prototype system, Food Aid Monitor, was successfully developed.
• The system utilizes artificial intelligence to provide adaptive feedback on food aid processes.
• Expert panel validation confirmed the prototype's quality attributes and potential utility.
• The system demonstrated potential for positive impact on food aid monitoring and evaluation.

Conclusions:

• The Food Aid Monitor expert system shows promise for improving food aid distribution efficiency.
• AI-driven adaptive feedback can significantly aid in monitoring and evaluation stages.
• The validated prototype offers a valuable tool for international disaster relief organizations.