AI-Driven Waste Management in Innovating Space Exploration

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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.

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