Blockchain and Digital Asset Transactions-Based Carbon Emissions Trading Scheme for Industrial Internet of Things

Carbon emissions trading has become an increasingly hot topic nowadays, due to the fact that how to reduce carbon emissions has been a common effort of different countries. However, traditional methods are plagued by issues, such as inadequate privacy protection mechanisms and the challenge of representing data assets in a comprehensive form using blockchain data models. In this article, we propose carbon emissions trading scheme (CETS), a secure carbon emissions trading system using blockchain combined with digital assets transactions. The proposed CETS scheme enhances the performance of models for carbon emissions trading by prioritizing the efficiency, privacy, and traceability of carbon emissions trading. Simultaneously, it improves the consistency of digital asset trading throughout the chain. First, we propose a dual-blockchain-based method for storing and tracing carbon emission data, which ensures the privacy of the data. Next, we propose algorithms for transaction of digital assets in carbon emission trading scheme, which include digital asset uniqueness algorithm, serializable mechanism, and cross-chain algorithm of digital assets. Finally, we propose an automated machine learning pipeline approach based on the carbon trading price forecasting model construction method, which can provide efficient, automatic price forecasting model construction and training. The experimental results prove that our proposed carbon emission trading system can provide an efficient and stable carbon emission trading solution.