… Review articles, wastewater treatment, and others unrelated to MSWM were not included in
this paper. A total of 137 articles were selected. Meanwhile, we expanded the literature data …

… the reality is, there is a lot of waste. So, we are proposing an automated waste classification
problem utilizing Machine Learning and Deep Learning algorithms. The goal of this task is to …

… waste management by predicting the probability of the waste level in trash bins. By using
machine learning … In this paper, we consider algorithms, based on heuristic models or graph …

… and its modification as well as conventional machines learning algorithms. The use of … Smart
Waste Management both in research and practical domains. The Smart Waste Management …

… We recommend using the introductory machine learning algorithm here, which can greatly
change simple techniques and success levels. The machine import algorithm combines new …

… waste management system with machine learning algorithm to collect and predict the waste
accurately. … This section introduces the intelligent waste management system that contains …

… The machine learning induction algorithm that we propose to use here is capable of
changing the conventional methods and efficiency rates, to a better output (Fig. 6). …

… the disposal of garbage and to forecast the air pollutant … algorithm (k-NN) and logistic reg)
and a non-traditional (long short term memory (LSTM) network-based deep learning) algorithm …

… that these algorithms can be used to reduce the environmental, … impacts of waste by designing
a smart waste management … , and environmental benefits of using ML algorithms in waste …

… By integrating ML in waste estimation, we aim to improve the efficiency and sustainability of
… environmental impact. This research contributes to advancing waste management practices …