AI Based Predictive Maintenance for Vehicles
Dr.Jamuna R1, Abhishek V G2 , Ajay Kartheek S3, Jayasaththy G4 , Kalaivani T5
1 Professor, Electronics and Communication Engineering, Sri Shakthi Institute of Engineering and Technology, India
E-mail: rjamunaece@siet.ac.in
2 Electronics and Communication Engineering, Sri Shakthi Institute of Engineering and Technology, India
E-mail: abhishekvg21ece@srishakthi.ac.in
3 Electronics and Communication Engineering, Sri Shakthi Institute of Engineering and Technology, India
E-mail: ajaykartheeks21ece@srishakthi.ac.in
4 Electronics and Communication Engineering, Sri Shakthi Institute of Engineering and Technology, India
E-mail: jayasaththyg21ece@srishakthi.ac.in
5 Electronics and Communication Engineering, Sri Shakthi Institute of Engineering and Technology, India E-mail: kalaivanit21ece@srishakthi.ac.in
Abstract
Predictive maintenance is a critical aspect of ensuring the longevity and optimal performance of vehicles. This paper presents a novel approach for vehicle health monitoring through the integration of Artificial Intelligence techniques and the Internet of Things (IoT) for predictive maintenance. The system utilizes a (RPI) platform combined with an OBD2 interface, using an ELM327 Bluetooth device to retrieve real-time vehicle data. The AI model processes these data inputs to predict potential vehicle failures and recommend maintenance actions, reducing downtime and improving overall efficiency. By leveraging machine learning algorithms, the system analyzes various vehicle parameters such as engine performance, fuel efficiency, and emission levels to generate actionable insights. This intelligent system enables early detection of faults, thus lowering repair costs, enhancing safety, and improving vehicle reliability. The proposed system is a cost-effective and scalable solution for vehicle maintenance, making it a valuable tool for both individual vehicle owners and fleet management operations.
Keywords: RPI Raspberry Pi, OBD2-Onboard Diagnosis Device
