Waste management is a process of collecting, transporting, disposing, and monitoring waste materials generated by human activities. It is an essential part of maintaining public health, hygiene, and environmental sustainability. Waste management systems can be designed to handle different types of waste, such as household waste, industrial waste, hazardous waste, and medical waste. The increasing amount of waste has become a major issue for the development of sustainable communities. Machine learning can help solve this problem by allowing scientists to analyze and reduce waste. This chapter aims to provide a comprehensive overview of the various aspects of waste management using machine learning. The chapter covers the various aspects of waste disposal, generation, transportation, and collection. It also explores machine learning's potential in this area, such as data analysis and prediction. It additionally compiles case studies about how machine learning has been utilized in this field.
Top1. Introduction
Waste management is an important environmental issue that needs to be addressed urgently (Song, 2021; Singh and Chhabra et al., 2023; Pardini and Rodrigues et al., 2019). The increasing population and urbanization have led to an increase in waste generation, which, if not managed properly, can severely impact the environment (Sami and Amin et al., 2020; Yadav and Rohilla, et al., 2023; Barik and Naz et al., 2022). Traditional waste management techniques, such as landfill and incineration, have failed to provide sustainable solutions (Xia and Jiang et al., 2022; Dubey and Singh et al. 2020; Gupta and Shree et al., 2019). Since it can pollute the environment and result in the depletion of natural resources (Khan and Kumar et al., 2021; Bakhshi and Ahmed, 2018). There is a need for modern solutions that can help reduce waste generation and improve waste management (Kannangara and Dua et al., 2018; Zaman, 2022; Chen, 2022).
Machine learning is a field of artificial intelligence that has shown great potential in solving complex problems (Joshi and Bharti et al., 2022; Kaushik and Gahletia et al., 2022; Velis and Wilson et al., 2023). It involves the use of algorithms that can analyze large amounts of data, learn from it, and make predictions. Machine learning can be used to predict waste generation, sort waste, and identify the best method for waste disposal (Yadav and Kumar et al., 2023; Desai and Dalvi et al., 2018; Graus and Niemietz et al., 2018). In this paper, we discuss the importance of waste management and how machine learning can be used to reduce waste.
Waste management systems are crucial for maintaining a sustainable environment and promoting public health. With the help of technology and data-driven approaches, waste management systems can become more effective, efficient, and sustainable. Waste management is the systematic process of collecting, transporting, processing, recycling, and disposing of waste materials in a safe, efficient, and environmentally responsible manner. It encompasses a wide range of activities aimed at minimizing the negative impacts of waste on human health, the environment, and society as a whole.
In modern societies, waste management has become a critical issue due to the ever-increasing volume and complexity of waste generated from various sources such as households, businesses, industries, and construction activities. Effective waste management is essential for preserving natural resources, reducing pollution, mitigating public health risks, and promoting sustainable development. In modern societies, waste management has become a critical issue due to the ever-increasing volume and complexity of waste generated from various sources such as households, businesses, industries, and construction activities (Kahhat and Kim et al., 2008).
Effective waste management is essential for preserving natural resources, reducing pollution, mitigating public health risks, and promoting sustainable development (Seadon, 2010). The goals of waste management include: Minimization, Resource Recovery, Environmental Protection, Public Health and Safety and Compliance and Regulation. Minimizing the generation of waste at the source through prevention, reduction, and reuse strategies to conserve resources and reduce environmental impact. Maximizing the recovery of valuable materials from waste through recycling, composting, and energy recovery to conserve resources and reduce the need for raw materials. Protecting public health and safety through waste management that prevents disease spread, reduces exposure to hazardous substances, and ensures waste materials are handled and disposed of safely.