A Rule-Based Expert System for Automobile Fault Diagnosis

Authors

  • Ibrahim Said Ahmad Department of Information Technology, Faculty of Computer Science and Information Technology, Bayero University Kano, Nigeria.
  • Saleem Abubakar Department of Information Technology, Faculty of Computer Science and Information Technology, Bayero University Kano, Nigeria.
  • Farouk Lawan Gambo Department of Computer Science, Faculty of Science, Federal University Dutse, Dutse, Jigawa, Nigeria
  • Murja Sani Gadanya Department of Information Technology, Faculty of Computer Science and Information Technology, Bayero University Kano, Nigeria

Abstract

Diagnosis of car fault is a complicated process which demands a high level of knowledge and skills. For this reason, automobile users require skilled automobile technicians for diagnosing a fault detected in their automobile and for maintenance. However, some faults are minor and will not require the services skilled mechanics. Expert systems are widely used in such fields as medical and trading for providing advice from a knowledge base database. However, fewer studies have used expert systems for automobile fault diagnosis that can be used by automobile users. The aim of this research is to develop an expert system for automobile fault diagnosis for automobile users. The knowledge base was acquired through interview and observation. The system was evaluated, and the results show that expert system can be used for automobile fault diagnosis by automobile users. This will enable automobile users to able to identify the fault in their automobile, fix it if it is a minor fault or take it to the necessary technician where necessary.

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Published

2021-07-16

How to Cite

Said Ahmad, I. ., Abubakar, S., Farouk Lawan Gambo, & Gadanya, M. S. . (2021). A Rule-Based Expert System for Automobile Fault Diagnosis. International Journal on Perceptive and Cognitive Computing, 7(1), 20–25. Retrieved from https://journals.iium.edu.my/kict/index.php/IJPCC/article/view/204

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