Diagnosis of the Car Brake System with Fuzzy-Bayesian Expert

Abstract

Brakes are essential for vehicle safety, acting as the primary protection on the road. A malfunction can cause accidents, highlighting the importance of regular checks for issues like unusual noises, abnormal movements, slow response, and warning lights. Often, drivers may not link these symptoms to brake problems, delaying necessary checks. However, identifying these issues as brake-related allows for immediate action. This paper proposes a Fuzzy-Bayesian expert system to aid drivers in maintaining car brakes. This system combines fuzzy logic and Bayesian reasoning to manage uncertainty and make informed decisions. It utilizes UPAFuzzySystems for fuzzy rule description and Twilio for SMS integration, enabling drivers to access brake system information via mobile. Our Python-based tool aims to revolutionize brake system diagnostics and maintenance, ensuring enhanced safety through timely and effective decision-making.