A Novel Architecture for Predictive Maintenance and Realtime Monitoring of Electric Vehicle

The rapid expansion of the electric vehicle sector presents a transformative opportunity for sustainable transportation, offering reduced emissions and increased energy efficiency. This paper introduces an innovative architecture leveraging the Internet of Things to enhance the maintenance and real-time monitoring of electric vehicles. The proposed system collects data from various sensors within the EV, including battery health, motor performance, and operational metrics. Machine learning models process this data in real-time, predicting maintenance needs before they become critical issues. Cloud integration enables remote monitoring and data accessibility, fostering a collaborative ecosystem. This architecture promises to elevate the reliability, efficiency, and sustainability of the EV industry, harnessing digitization and data-driven insights for cleaner, smarter, and more reliable transportation.