Machine learning (ML) has evolved into one of the most acclaimed technologies, with applications ranging from inventive to scientific. There is not much debate that ML is one of the big revolutions that society is witnessing, and it will undoubtedly revolutionize the way operation take place. Indeed, it is starting to play an essential part in the plastic recycling process. This chapter will review some exceptional cases that employ ML to enhance the collection, sorting, and processing of plastic garbage. This chapter explores residential solid plastic management profiling such as high-performance recycling machines, plastic waste collection, innovative plastic waste sorting processes, effective recycling processes, optimized plastic waste processing, and a way of smart plastic waste management. It is expected that this study will contribute to a more approachable amount of research on this subject and serve as a useful guide for all stakeholders in raising awareness of the potential benefits of applying machine learning in smart plastic management. Additionally, it describes the benefits of applying machine learning approaches that articulate solutions to specific problems and proposes some potential avenues for future research.

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Smart Intelligence in Residential Solid Plastic Management Profiling: Machine Learning Approaches

  • Abdul Gaffar Sheik

摘要

Machine learning (ML) has evolved into one of the most acclaimed technologies, with applications ranging from inventive to scientific. There is not much debate that ML is one of the big revolutions that society is witnessing, and it will undoubtedly revolutionize the way operation take place. Indeed, it is starting to play an essential part in the plastic recycling process. This chapter will review some exceptional cases that employ ML to enhance the collection, sorting, and processing of plastic garbage. This chapter explores residential solid plastic management profiling such as high-performance recycling machines, plastic waste collection, innovative plastic waste sorting processes, effective recycling processes, optimized plastic waste processing, and a way of smart plastic waste management. It is expected that this study will contribute to a more approachable amount of research on this subject and serve as a useful guide for all stakeholders in raising awareness of the potential benefits of applying machine learning in smart plastic management. Additionally, it describes the benefits of applying machine learning approaches that articulate solutions to specific problems and proposes some potential avenues for future research.