The global push for green technologies and digital transformation has intensified the demand for critical raw materials, prompting the European Union to enact the Critical Raw Materials Act (CRMA) to ensure ethical, transparent, and resilient mineral supply chains. As the world advances toward the 6G and IoT era, characterized by ultra-low latency, ubiquitous connectivity, and intelligent edge computing, there is an urgent need to empower all levels of the supply chain, especially artisanal small-scale mining (ASM), which remains largely disconnected from such innovations. To address this gap, we propose the Raw Material Radar (RMR) framework, centered on a smart barrel that integrates IoT sensing, edge AI processing, and blockchain-based record-keeping. This low-power device enables real-time detection of shipment anomalies such as tampering or unauthorized access, even in offline and resource-limited environments. Our fully functional prototype achieves high performance (94% F1-score, 98% recall), with minimal resource usage (8.45KB RAM, 407KB flash) and fast inference (5.25 ms), making it well-suited for deployment at the network edge. By enabling verifiable, autonomous custody tracking, the RMR solution exemplifies how edge AI can enhance supply chain transparency and regulatory compliance—critical components for ethical sourcing in the 6G-driven IoT landscape.

Toward Compliance and Transparency in Raw Material Sourcing With Blockchain and Edge AI

Abderrahim Khiari;Anas Osman;Massimo Vecchio
;
Mattia Antonini;Miguel Pincheira
2025-01-01

Abstract

The global push for green technologies and digital transformation has intensified the demand for critical raw materials, prompting the European Union to enact the Critical Raw Materials Act (CRMA) to ensure ethical, transparent, and resilient mineral supply chains. As the world advances toward the 6G and IoT era, characterized by ultra-low latency, ubiquitous connectivity, and intelligent edge computing, there is an urgent need to empower all levels of the supply chain, especially artisanal small-scale mining (ASM), which remains largely disconnected from such innovations. To address this gap, we propose the Raw Material Radar (RMR) framework, centered on a smart barrel that integrates IoT sensing, edge AI processing, and blockchain-based record-keeping. This low-power device enables real-time detection of shipment anomalies such as tampering or unauthorized access, even in offline and resource-limited environments. Our fully functional prototype achieves high performance (94% F1-score, 98% recall), with minimal resource usage (8.45KB RAM, 407KB flash) and fast inference (5.25 ms), making it well-suited for deployment at the network edge. By enabling verifiable, autonomous custody tracking, the RMR solution exemplifies how edge AI can enhance supply chain transparency and regulatory compliance—critical components for ethical sourcing in the 6G-driven IoT landscape.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/360828
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