Vehicle systems are difficult for both Hardware implementation and Software implementation, so it is safeguarding is a difficult task. In vehicle trade, the maintenance process being utilized that effect in a fall of vehicle lifetime and also loss of capital. Predictive maintenance is needed to conquer these problems. The fault diagnosis system is proposed using PIC Microcontroller with efficient manner. The several parts in the vehicle such as vehicle engine, Gearbox, Power train unit, Airbag, Engine Control Units (ECUs), Chassis, ABS are establishing to apply the microcontroller. This article aims to clarify and review the ML frontiers involved in modern vehicle condition monitoring systems. The microcontroller operation helps to information about the individual health of the vehicle and gives/saves on the Internet of Things (IoT). Then, the web page receives the data and information will apply to the fault code diagnosis system. The fault diagnosis system helps to find the faults in the vehicle, such as the faults are precisely identified and establish the proper establishment of fault information in the fault diagnosis system. This work is combined effect of IoT data with machine learning to reduce the vehicle demages or fault condition monitoring. The performance analysis of the proposed system attains better performance than the other existing approaches.


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    Titel :

    Machine Learning and Vehicle Fault Diagnosis System with IoT Enabled Data


    Beteiligte:


    Erscheinungsdatum :

    21.12.2023


    Format / Umfang :

    517882 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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