Revolutionizing Battery Management: A Secure AI-Powered Optimization Framework

This research focuses on tackling the environmental issues caused by e-waste, especially batteries, using Machine Learning-based Battery Management Systems (BMS). It highlights advancements in battery materials, such as solid-state electrolytes, to extend battery life and reduce environmental impact. Machine learning techniques, including regression models and clustering, optimize battery health and sustainability by analyzing critical performance parameters like temperature and charge/discharge rates. The study also underscores the importance of secure and robust AI/ML methods to prevent potential vulnerabilities. Ultimately, the goal is to create a sustainable future by maximizing the benefits of electronic devices while minimizing battery waste, requiring collaboration across scientific, policy, and public sectors.