AI Rule-Based Expert System: Diagnosis and Treatment of Bean Diseases

Author(s)	Mr. Dayahan Angas Bugao, Dr. Hidear Talirongan
Country	Philippines
Abstract	This study introduces an AI rule-based expert system designed to help diagnose and treat common bean diseases. Built with SWI-Prolog, the system uses if-then rules to analyze symptoms provided by users, identify the most likely disease, and recommend suitable treatments. Its structure combines a knowledge base, inference engine, and rule set that cover major diseases such as Fusarium Wilt, Charcoal Rot, Leaf Spot, Mung Bean Yellow Mosaic, and Cercospora Leaf Spot. Tests and expert reviews confirmed that the system is accurate, consistent, and reliable, making it a practical decision-support tool for farmers and agricultural workers. By automating diagnosis, it reduces dependence on human experts, enables quicker disease management, and helps farmers prevent crop losses. The study also shows how SWI-Prolog supports clear and logical reasoning in agricultural applications. Future enhancements include expanding the knowledge base, improving the user interface, and linking the system with mobile or database platforms for wider access.
Keywords	Expert System, Decision Support System, Rule-Based System, Bean Disease, SWI-Prolog
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 16, Issue 3, July-September 2025
Published On	2025-08-28
DOI	https://doi.org/10.71097/IJSAT.v16.i3.7933
Short DOI	https://doi.org/g9z5nm

About IJSAT Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us	Message on WhatsApp	+91-9687-182-185	editor@ijsat.org

International Journal on Science and Technology