Artificial intelligence applications for sustainable solid waste management practices in Australia: A systematic review

L Andeobu, S Wibowo, S Grandhi - Science of The Total Environment, 2022 - Elsevier
Solid waste generation and its impact on human health and the environment have long
been a matter of concern for governments across the world. In recent years, there has been …

Artificial intelligence applications in solid waste management: A systematic research review

M Abdallah, MA Talib, S Feroz, Q Nasir, H Abdalla… - Waste Management, 2020 - Elsevier
The waste management processes typically involve numerous technical, climatic,
environmental, demographic, socio-economic, and legislative parameters. Such complex …

Toward smarter management and recovery of municipal solid waste: A critical review on deep learning approaches

K Lin, Y Zhao, JH Kuo, H Deng, F Cui, Z Zhang… - Journal of Cleaner …, 2022 - Elsevier
Increasing generation of municipal solid waste, heterogeneity of waste composition, and
complex processes of waste management and recovery have limited the performance of …

Tackling environmental challenges in pollution controls using artificial intelligence: A review

Z Ye, J Yang, N Zhong, X Tu, J Jia, J Wang - Science of the Total …, 2020 - Elsevier
This review presents the developments in artificial intelligence technologies for
environmental pollution controls. A number of AI approaches, which start with the reliable …

Estimating construction waste generation in the Greater Bay Area, China using machine learning

W Lu, J Lou, C Webster, F Xue, Z Bao, B Chi - Waste management, 2021 - Elsevier
Reliable construction waste generation data is a prerequisite for any evidence-based waste
management effort, but such data remains scarce in many develo** economies owing to …

Forecasting municipal solid waste generation using artificial intelligence modelling approaches

M Abbasi, A El Hanandeh - Waste management, 2016 - Elsevier
Municipal solid waste (MSW) management is a major concern to local governments to
protect human health, the environment and to preserve natural resources. The design and …

A hybrid machine-learning model for predicting the waste generation rate of building demolition projects

GW Cha, HJ Moon, YC Kim - Journal of Cleaner Production, 2022 - Elsevier
Abstract Information on waste generation rate (WGR) is useful for waste management.
Recently, several studies have been conducted to predict WGR using artificial intelligence …

Water quality assessment using NSFWQI, OIP and multivariate techniques of Ganga River system, Uttarakhand, India

G Matta, A Nayak, A Kumar, P Kumar - Applied Water Science, 2020 - Springer
Ganga River water is very much stressed with the rapidly increasing population, climate
change and water pollution that increase domestic, agricultural and industrial needs. This …

Landfill area estimation based on solid waste collection prediction using ANN model and final waste disposal options

MM Hoque, MTU Rahman - Journal of Cleaner Production, 2020 - Elsevier
Public health of inhabitants has been affected by the increase of unsound waste
management in the cities of develo** countries. Solid waste management has received …

Forecasting municipal solid waste quantity using artificial neural network and supported vector machine techniques: A case study of Johannesburg, South Africa

OO Ayeleru, LI Fajimi, BO Oboirien… - Journal of Cleaner …, 2021 - Elsevier
Detailed prediction of the amounts of municipal solid waste (MSW) is very crucial for
planning and management of MSW in a sustainable manner. Forecasting of MSW quantity is …