Federated Blockchain–IoT Framework for Transparent and Intelligent Carbon-Credit Management in the Automotive Sector

Abstract

Massive growth of the Chinese carbon-credit market has been characterized by endemic data obscurity, certification latency, and fraud, specifically in the Passenger Cars Corporate Average Fuel Consumption and New Energy Vehicle Credit Regulation (PCFN) scheme in the automotive industry. Its present centralized management system is not transparent and has information asymmetries and is very prone to manipulation results in erroneous carbon-credit determination, inefficient dealings, and the deteriorating stakeholder confidence. This paper offers a federated blockchain-IoT information infrastructure to deal with these severe inadequacies, namely, the provision of end-to-end transparency, tamper-resistance, and autonomous functionality in managing carbon-credit. The framework uses radio frequency identification (RFID) to capture real-time emission data, delegated proof-of-stake (DPoS) consensus to provide scalable verification and uses smart contracts to provide a decentralized credit assessment and trading. Besides, an AI-based predictive analytics control is incorporated to dynamically predict credit prices and identify anomalies on distributed nodes. Experimental comparison with national automotive carbon datasets reveals that the 72.6% latency of credit verification is reduced, the 38.2% transparency of audit is increased, and the 93.5% accuracy of fraud detection is achieved rather significantly in comparison to the traditional centralized model. The suggested framework will offer a platform on which the cross-sector carbon-credit markets of China can be scaled and verified to speed up the process of the country achieving its carbon neutrality targets of 3060.