Featuring Machine Learning in Municipal Solid Waste Management
Bhupinder Singh, Christian Kaunert, Rishabha Malviya
Abstract
Due to the expansion of urban areas and the steady growth of the global population, the management of municipal solid waste has become increasingly complex in recent times. Inadequate handling of waste poses risks to the environment, public health, and exacerbates greenhouse gas emissions. There are various approaches such as the principle of reduce, reuse, recycle, and recover have been introduced to tackle these challenges. However, effectively implementing these strategies remains intricate and challenging. Machine learning stands out as a promising technology with the potential to revolutionize municipal solid waste management. ML can play a pivotal role in streamlining waste sorting and segregation processes, thereby enhancing the efficiency and cost-effectiveness of waste management operations. This chapter explores the machine learning enables route optimization, waste categorization, and prediction of waste characteristics, aiming to enhance efficiency, reduce costs, and minimize environmental impact solid waste management.