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Waste Management

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Municipal solid waste management for low-carbon transition: A systematic review of artificial neural network applications for trend prediction.

Environmental pollution (Barking, Essex : 1987)
Improper municipal solid waste (MSW) management contributes to greenhouse gas emissions, necessitating emissions reduction strategies such as waste reduction, recycling, and composting to move towards a more sustainable, low-carbon future. Machine le...

Machine-learning intervention progress in the field of organic waste composting: Simulation, prediction, optimization, and challenges.

Waste management (New York, N.Y.)
Aerobic composting stands as a widely-adopted method for treating organic solid waste (OSW), simultaneously producing organic fertilizers and soil amendments. This biologically-driven biochemical reaction process, however, presents challenges due to ...

Sensor-based characterization of construction and demolition waste at high occupancy densities using synthetic training data and deep learning.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
Sensor-based monitoring of construction and demolition waste (CDW) streams plays an important role in recycling (RC). Extracted knowledge about the composition of a material stream helps identifying RC paths, optimizing processing plants and form the...

Waste management and artificial intelligence: Is it happening already?

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA

Multi-modal deep learning networks for RGB-D pavement waste detection and recognition.

Waste management (New York, N.Y.)
To create a clean living environment, governments around the world have hired a large number of workers to clean up waste on pavements, which is inefficient for waste management. To better alleviate this problem, relevant scholars have proposed sever...

Intelligent and sustainable waste classification model based on multi-objective beluga whale optimization and deep learning.

Environmental science and pollution research international
Resource recycling is considered necessary for sustainable development, especially in smart cities where increased urbanization and the variety of waste generated require the development of automated waste management models. The development of smart ...

Multi-objective location-routing optimization based on machine learning for green municipal waste management.

Waste management (New York, N.Y.)
Most of the existing municipal waste management (MWM) systems focus on the optimization of the waste disposal center locations and waste collection paths, which can be modeled based on the location-routing problem (LRP). This study models a green MWM...

Effective waste management in service industry: Fuzzy-based modelling approach for strategic decision-making.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
Hospitals need to identify issues of greater importance on waste management because the implementation of many different strategies may lead to an unconscious increase in costs. Accordingly, the purpose of this study is to define the most effective w...

Classification of e-waste using machine learning-assisted laser-induced breakdown spectroscopy.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
Waste management and the economy are intertwined in various ways. Adopting sustainable waste management techniques can contribute to economic growth and resource conservation. Artificial intelligence (AI)-based classification is very crucial for rapi...

Agro-industrial waste management employing benefits of artificial intelligence.

Environmental science and pollution research international
By 2050, the world's population is predicted to reach over 9 billion, which requires 70% increased production in agriculture and food industries to meet demand. This presents a significant challenge for the agri-food sector in all aspects. Agro-indus...