The Application of Artificial Intelligence in the Effective Battery Life Cycle in the Closed Circular Economy Model—A Perspective

Abstract

Global pollution of the environment is one of the most challenging environmental problems. Electronic-based population and anthropogenic activity are the main reasons for dramatically increasing the scale of waste generation, particularly battery waste. Improper battery waste disposal causes harmful environmental effects. Due to the release of heavy metals, battery waste affects ecosystems and health. We are faced with the challenge of effective battery waste management, especially recycling, to prevent the depletion of natural resources and maintain ecological balance. Artificial Intelligence (AI) is practically present in all areas of our lives. It enables the reduction of the costs associated with various types of research, increases automation, and accelerates productivity. This paper reviews the representative research progress of effective Artificial Intelligence-based battery waste management in the context of sustainable development, in particular, the analysis of current trends, algorithm accuracy, and data availability. Finally, the future lines of research and development directions of human-oriented Artificial Intelligence applications both in the battery production process and in battery waste management are discussed.

Keywords

• battery waste
• waste management
• artificial intelligence
• machine learning
• genetic programming
• end-of-life