Machine Learning for Sustainable Energy Solutions

Comprehensive insights into integrating modern engineering techniques with machine learning and renewable energy to create a more sustainable worldThrough an interdisciplinary approach, Machine Learning for Sustainable Energy Solutions provides comprehensive insights into integrating modern engineering techniques such as machine learning (ML), artificial intelligence (AI), nanotechnology, digital twins, and the Internet of Things (IoT) with renewable energy. Each chapter is based on modern research and enhanced by experimental or simulated data. The book offers a thorough review of several energy storage techniques, helping readers fully grasp the larger background in which chemical, thermal, electrical, mechanical, and machine learning technologies may be used to evaluate, categorize, and maximize different storage systems. The book also reviews the confluence of the Internet of Things (IoT) and machine learning for real-time digestive parameter control and monitoring, along with the cooperative importance

science, and machine learning. The book also helps decision-makers in various fields by providing them the required knowledge to make informed choices on sustainable practices and policies. [Publisher's Text]

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