Data Science Applications in IoT for Electric Vehicles: Leveraging Artificial Intelligence and Machine Learning

The integration of Internet of Things (IoT) technology in Electric Vehicles (EVs) has opened new avenues for optimizing vehicle performance, enhancing user experience, and improving operational efficiency. This paper explores the application of Artificial Intelligence (AI) and Machine Learning (ML) in IoT-enabled EVs, focusing on key interface areas where data-driven insights can be leveraged. By analyzing current IoT architectures, this research identifies potential areas for AI and ML intervention, such as predictive battery management, autonomous driving algorithms, predictive maintenance, and energy consumption optimization. The proposed framework demonstrates how machine learning models can be utilized to predict battery life and charging patterns, improve autonomous driving decisions, and optimize energy efficiency based on real-time data. The results indicate significant improvements in both vehicle performance and user satisfaction through the integration of AI and ML technologies. This paper provides a comprehensive overview of the challenges and limitations associated with implementing these advanced technologies in EVs, while also highlighting the potential for future research in this rapidly evolving field.