Research Trends in Organic and Inorganic Waste Sorting Technology: A Bibliometric Analysis

This research presents major trends in organic and inorganic waste sorting technology over the past 20 years (2003-2023). To do so, we employed bibliometric analysis and VOSviewer and Biblioshiny software. The data used in this study included 810 documents from the Scopus database. This study also used literature analysis of 11 documents discussing the use of AI in organic and inorganic waste sorting technology. The results showed that leading journals covering the topics ‘Waste Management and Resources’, ‘Conservation’, and ‘Recycling’, had the highest publication volume and total citations. Journals in China also had high volume and citations. The literature analysis of the articles further showed that integrating AI into waste-sorting technology can improve organic and inorganic waste-sorting efficiency and effectiveness, and also contribute to sustainable environmental planning. Future research opportunities include enhancing AI accuracy in waste sorting, developing renewable waste-to-energy technologies, and promoting interdisciplinary collaboration to advance sustainable waste management solutions.

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Publication Details

Journal
Environment and Natural Resources Journal
Published
2025-03-25
DOI
https://doi.org/10.32526/ennrj/23/20240277
Citations
1
Primary Topic
Agriculture, Soil, Plant Science
Type
article
Field-Weighted Citation Impact
3.03
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article

Research Trends in Organic and Inorganic Waste Sorting Technology: A Bibliometric Analysis

Mahliza Nasution, M. Rudi Irwansyah, Hermansyah Hermansyah, Rospita Gultom
1 citations
Environment and Natural Resources Journal
Agriculture, Soil, Plant Science
3.03
article

Research Trends in Organic and Inorganic Waste Sorting Technology: A Bibliometric Analysis

Mahliza Nasution, M. Rudi Irwansyah, Hermansyah Hermansyah, Rospita Gultom
article en
1 citations

Abstract

This research presents major trends in organic and inorganic waste sorting technology over the past 20 years (2003-2023). To do so, we employed bibliometric analysis and VOSviewer and Biblioshiny software. The data used in this study included 810 documents from the Scopus database. This study also used literature analysis of 11 documents discussing the use of AI in organic and inorganic waste sorting technology. The results showed that leading journals covering the topics ‘Waste Management and Resources’, ‘Conservation’, and ‘Recycling’, had the highest publication volume and total citations. Journals in China also had high volume and citations. The literature analysis of the articles further showed that integrating AI into waste-sorting technology can improve organic and inorganic waste-sorting efficiency and effectiveness, and also contribute to sustainable environmental planning. Future research opportunities include enhancing AI accuracy in waste sorting, developing renewable waste-to-energy technologies, and promoting interdisciplinary collaboration to advance sustainable waste management solutions.

Environment and Natural Resources JournalVol. 23(3)
Medan Area University (ID)
Openalex Percentile: Top 12%
Agriculture, Soil, Plant Science
3.03
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