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Using Artificial Intelligence to Tackle Food Waste and Enhance the Circular Economy: Maximising Resource Efficiency and Minimising Environmental Impact: A Review

Author

Listed:
  • Helen Onyeaka

    (School of Chemical Engineering, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK)

  • Phemelo Tamasiga

    (Public Policy in Africa Initiative, Yaounde, Cameroon)

  • Uju Mary Nwauzoma

    (Faculty of Environmental Science, University of Nigeria, Enugu Campus 410001, Nigeria)

  • Taghi Miri

    (School of Chemical Engineering, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK)

  • Uche Chioma Juliet

    (Department of Urban and Regional Planning, University of Nigeria, Enugu Campus 410001, Nigeria)

  • Ogueri Nwaiwu

    (School of Chemical Engineering, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK)

  • Adenike A. Akinsemolu

    (Institute of Advanced Studies, University of Birmingham, Birmingham B15 2TT, UK)

Abstract

Food waste is a global issue with significant economic, social, and environmental impacts. Addressing this problem requires a multifaceted approach; one promising avenue is using artificial intelligence (AI) technologies. This article explores the potential for AI to tackle food waste and enhance the circular economy and discusses the current state of food waste and the circular economy, highlighting specific ways that AI can be used to monitor and optimise food production and supply chains, redistribute excess food to those in need, and support circular economy initiatives. As a result, we can maximise resource efficiency and minimise environmental impact with these applications, ultimately creating a more sustainable and equitable food system.

Suggested Citation

  • Helen Onyeaka & Phemelo Tamasiga & Uju Mary Nwauzoma & Taghi Miri & Uche Chioma Juliet & Ogueri Nwaiwu & Adenike A. Akinsemolu, 2023. "Using Artificial Intelligence to Tackle Food Waste and Enhance the Circular Economy: Maximising Resource Efficiency and Minimising Environmental Impact: A Review," Sustainability, MDPI, vol. 15(13), pages 1-20, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10482-:d:1186016
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    2. Daniel Nijloveanu & Victor Tița & Nicolae Bold & Doru Anastasiu Popescu & Dragoș Smedescu & Cosmina Smedescu & Gina Fîntîneru, 2024. "The Development of a Prediction Model Related to Food Loss and Waste in Consumer Segments of Agrifood Chain Using Machine Learning Methods," Agriculture, MDPI, vol. 14(10), pages 1-27, October.
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