Designing Social Resource Networks for Intelligent Waste Matchmaking and Cross-Industry Circular Resource Exchange Using AI

Author

Hassan Abubakar

Abstract

 Growing resource consumption, industrial waste generation, and environmental pressures have intensified the transition from linear production systems toward circular economies that preserve material value through reuse, recovery, and cross-sector collaboration. Despite this transition, potentially valuable waste streams frequently remain underutilized because resource information is fragmented, industrial actors operate within disconnected networks, and conventional exchange platforms inadequately identify compatibility between heterogeneous waste outputs and production requirements. This study proposes a Social Resource Network (SRN) framework that integrates socio-technical networking principles with artificial intelligence to enable intelligent waste matchmaking and cross-industry circular resource exchange. The framework structures information on material composition, quality, quantity, location, availability, processing requirements, and organizational demand while applying machine learning, semantic analysis, and recommendation mechanisms to identify viable resource matches. Multi-criteria assessment incorporates technical compatibility, economic feasibility, environmental value, geographical proximity, regulatory compliance, and participant trust. Continuous feedback from completed and rejected exchanges further supports adaptive matchmaking and network learning. The proposed framework transforms fragmented waste information into actionable resource intelligence, enabling industrial symbiosis, reducing disposal dependence, improving secondary-resource utilization, and strengthening scalable, data-driven circular resource ecosystems across traditionally disconnected industrial sectors.

Keywords

Social Resource Networks; Intelligent Waste Matchmaking; Artificial Intelligence; Industrial Symbiosis; Circular Resource Exchange; Circular Economy

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References

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