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Full Description
Harnessing Automation and Machine Learning for Resource Recovery and Value Creation: From Waste to Value provides a comprehensive understanding of how automation and machine learning technologies can be used to convert waste into valuable resources. This book gives insight in the opportunities offered by automation and machine learning technologies in waste management and how they can help address the challenges associated with waste management and to discuss the benefits and potential of automation technologies. It examines the potential of machine learning algorithms in analyzing waste management data, identifying patterns, predicting future waste generation, and optimizing waste management processes. Moreover, this book showcases case studies from different industries and regions, highlighting the revolutionary applications of automation and machine learning in waste management. This book is an indispensable resource for researchers, waste management professionals, and policymakers interested in learning more about how automation and machine learning can contribute to waste management and the creation of a sustainable future.
Contents
1. Introduction to innovative Technologies for Waste-to-Energy Conversion using automation and machine learning
2. Basics of Machine learning
3. Basics of Automation
4. Waste classification into plastics, industrial, domestic, and agriculture waste
5. Plastics recycling and the automation role in the recycling process
6. Artificial intelligence for reutilizing the Plastics
7. Handling Metals waste to Salvage with Automation
8. Machine learning: A better means for Metal waste to reprocess
9. Automation in the recycling of Industrial waste
10. Machine learning in Industrial Waste to value added
11. Waste to Value Added: Role of automation in Organic waste
12. Impact of Artificial Intelligence for the recycling of Organic waste
13. Future of Agriculture: Automated vertical farming
14. Agriculture: The Next Machine-Learning Frontier
15. Recycling robots to tackle electrical waste
16. Machine learning for sustainable development in electronics
17. Automated Sorting of Recyclable Domestic waste
18. Machine learning for recycling domestic waste
19. Future aspects of Machine learning/automation for the waste management