Car failure detection is a complicated process and requires high level of expertise. Any attempt of developing an expert system dealing with car failure detection has to overcome various difficulties. It is expected that the proposed design would ensure that car owners have proper assistance in times of crisis and save them from the clutches of exploitative roadside mechanics. For this purpose a rule- base artificial intelligence (AI) (knowledge base creation) was utilized to obtain theoretical and practical expert system parameters, using interview method with structured questions as data collection method and then a conceptual expert system was designed using object oriented analysis and design methodology (OOADM). The expert system functioning is based on the database of car faults, symptoms and their correction, which make up its knowledge base. The new system was developed using Python and MatLab. After testing of the system, it was seen to be capable of solving problems up to 70% level of accuracy which will increase as more symptoms/ faults are introduced into its knowledge based data-base.
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