Design and Implementation of an Expert System for Diagnosing Automobile

ABSTRACT The Expert System for Diagnosing Automobile Faults is designed to assist vehicle owners and mechanics in identifying potential issues based on symptoms observed in automobiles. This system leverages knowledge-based techniques to analyze inputted symptoms and provide accurate diagnoses along with suggested solutions. The system is developed as a web-based application to ensure accessibility, allowing users to interact through a user-friendly interface on both web and local servers. The project focuses on addressing the limitations of traditional manual diagnostic methods, which often rely heavily on human expertise and can lead to inconsistent or inaccurate results. By implementing a robust knowledge database, the expert system offers quick, consistent, and reliable diagnoses. The system incorporates features such as user registration, symptom input, automated diagnosis, and administrative management of diagnostic rules. In developing the system, a two-level database design approach was utilized: The Information Level Design to gather and structure user requirements, and the Physical Level Design to translate these requirements into a working database model. Testing procedures, including unit testing and interface testing, were conducted to ensure the system functions accurately and meets user expectations. The results show that this expert system significantly improves the efficiency, accuracy, and accessibility of automobile fault diagnosis, providing a valuable tool for both experienced and novice users. The system's scalability and ease of use make it a promising solution for modern vehicle maintenance and troubleshooting.