… to boost environmental performance through waste recovery. There are two phases in a
typical waste management system. First phase is the collection of waste from houses for …

… In order to handle MSW responsibly, it is essential to design a waste management system
that allows for both material recycling and energy production from non-recyclable MSW, while …

… waste management domains like municipal solid waste management, smart bin management,
domestic waste … of different machine learning algorithms in the waste recycling process. …

… waste. In addition to enhancing our knowledge of the production of odor from domestic
waste, we also explore the application of machine learning to odor pollution in our study. …

… Due to the superiority of machine learning (ML) data processing, it is widely used in research
of solid waste (SW). This study analyzed the research and developmental progress of the …

… with chemical analysis improves waste pyrolysis, carbon … intelligence in waste management
systems for smart cities. … machine learning-based methods in waste management to …

… Different combinations of keywords were used in the initial search, mostly including ‘waste
management’, ‘machine learning’, ‘deep learning’, ‘artificial intelligence’ and ‘artificial neural …

… impact aiding food waste management. … Machine Learning (ML) algorithms were used to
predict deviations in production, reducing uncertainties related to the amount of waste produced…

… steps of waste management is the separation of the waste into … To simplify the process, we
propose an intelligent waste … Network model which is a machine learning tool and serves as …

… The Smart Bin is the process of predicting the waste filling percentage and detecting the
nasty smell and level of filling the machine learning is the part where the prediction takes place. …