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AI-Driven Waste Management in Innovating Space Exploration

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  • David Bamidele Olawade

    (Department of Allied and Public Health, School of Health, Sport and Bioscience, University of East London, London E16 2RD, UK
    Department of Research and Innovation, Medway NHS Foundation Trust, Gillingham ME7 5NY, UK
    Department of Public Health, York St John University, London E14 2BA, UK)

  • Ojima Zechariah Wada

    (Division of Sustainable Development, College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Education City, Doha 34110, Qatar
    Global Eco-Oasis Sustainable Initiative, Ibadan 220212, Nigeria)

  • Tunbosun Theophilus Popoola

    (Department of Chemistry, Faculty of Science, University of Ibadan, Ibadan 200005, Nigeria)

  • Eghosasere Egbon

    (Department of Tissue Engineering and Regenerative Medicine, Faculty of Life Science Engineering, FH Technikum, 1200 Vienna, Austria)

  • James O. Ijiwade

    (Department of Chemistry, Faculty of Science, University of Ibadan, Ibadan 200005, Nigeria)

  • B. I. Oladapo

    (Sustainable Development, De Montfort University, Leicester LE1 9BH, UK
    School of Science and Engineering, Afe Babalola University, Ado-Ekiti 360102, Nigeria)

Abstract

This research evaluates advanced waste management technologies suitable for long-duration space missions, particularly focusing on artificial intelligence (AI)-driven sorting systems, biotechnological bioreactors, and thermal processing methods, such as plasma gasification. It quantitatively assesses the waste generated per crew member. It analyses energy efficiency, integration capabilities with existing life-support systems, and practical implementation constraints based on experimental ground and ISS data. Challenges are addressed, including energy demands, microbial risks, and integration complexities. The research also discusses methodological approaches, explicitly outlining selection criteria and comparative frameworks used. Key findings indicate that plasma arc technologies significantly reduce waste volume, although high energy consumption remains challenging. Enhanced recycling efficiencies of water and oxygen are also discussed. Future research directions and actionable policy recommendations are outlined to foster sustainable and autonomous waste management solutions for space exploration.

Suggested Citation

  • David Bamidele Olawade & Ojima Zechariah Wada & Tunbosun Theophilus Popoola & Eghosasere Egbon & James O. Ijiwade & B. I. Oladapo, 2025. "AI-Driven Waste Management in Innovating Space Exploration," Sustainability, MDPI, vol. 17(9), pages 1-19, May.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:9:p:4088-:d:1647584
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    References listed on IDEAS

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    1. Tong Li & Li Yu & Yibo Ma & Tong Duan & Wenzhen Huang & Yan Zhou & Depeng Jin & Yong Li & Tao Jiang, 2023. "Carbon emissions of 5G mobile networks in China," Nature Sustainability, Nature, vol. 6(12), pages 1620-1631, December.
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