Leveraging blockchain and AI for sustainable recycling and traceability in the vehicle industry

The increasing use of electric vehicles (EVs) has highlighted the need for sustainable recycling and traceability of essential raw materials. 

Osaka Metropolitan University researchers introduced a blockchain and AI-integrated framework designed with the possibility to optimize vehicle components lifecycle management with recycling and tracing throughout the supply chain. The system uses Decentralized Identifiers (DIDs) for secure identification of components, enabling transparent tracking from production to recycling. Hyperledger Fabric ensures immutable data and choring across stakeholders. Hyperledger Caliper is used for benchmarking the system, assessing metrics such as transaction speed, latency, and scalability. AI models, including regression and clustering algorithms, are utilized to optimize recycling processes, predict component lifespans, and enhance resource recovery in the system. A tokenized reward mechanism incentivizes eco-friendly practices among stakeholders. The system also shows its environmental benefits, including energy savings from improved recycling performance. 

The proposed framework effectively supports the circular economy by enhancing resource recovery processes. While its design has the potential to reduce environmental impact, this benefit depends on the reusable, modular system design.

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