CQUniversity
Browse

File(s) not publicly available

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

journal contribution
posted on 2023-03-13, 22:37 authored by Lynda AndeobuLynda Andeobu, Santoso WibowoSantoso Wibowo, Srimannarayana GrandhiSrimannarayana Grandhi
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 increasing emphasis on resource recovery (reusing, recycling and extracting energy from waste) using more advanced approaches such as artificial intelligence (AI) in Australia. AI is a powerful technology that is increasingly gaining popularity and application in various fields. The adoption of AI techniques offers alternative innovative approaches to solid waste management (SWM). Although there are previous studies on AI technologies and SWM, no study has assessed the adoption of AI applications in solving the diverse SWM problems for achieving sustainable waste management in Australia. Moreover, there are inconsistencies and a lack of awareness on how AI technologies function in relation to their application to SWM. This study examines the application of AI technologies in various areas of SWM (generation, sorting, collection, vehicle routing, treatment, disposal and waste management planning) to enhance sustainable waste management practices in Australia. To achieve the aims of this study, prior studies from 2005-2021 from various databases are collected and analyzed. The study focuses on the adoption of AI applications on SWM, compares the performance of AI applications, explores the benefits and challenges, and provides best practice recommendations on how resource efficiency can be optimized to improve economic, environmental and social outcomes. This study found that AI-based models have better prediction abilities when compared to other models used in forecasting solid waste generation and recycling. Findings show that waste generation in Australia has been steadily increasing and requires upgraded and improved recovery infrastructure and the appropriate adoption of AI technologies to enhance sustainable SWM. Australia’s adoption of AI recycling technologies would benefit from a national approach that seeks consistency across jurisdictions, while catering for regional differences. This study will benefit researchers, governments, policy-makers, municipalities and other waste management organizations to increase current recycling rates, eliminate the need for manual labor, reduce costs, maximize efficiency, and transform the way we approach the management of solid waste.

History

Volume

834

Start Page

1

End Page

17

Number of Pages

17

eISSN

1879-1026

ISSN

0048-9697

Publisher

Elsevier

Language

en

Peer Reviewed

  • Yes

Open Access

  • No

Acceptance Date

2022-04-15

Author Research Institute

  • Centre for Intelligent Systems

Era Eligible

  • Yes

Medium

Print-Electronic

Journal

Science of the Total Environment

Article Number

155389