Event-based data authenticity analytics for IoT and blockchain-enabled ESG disclosure

Abstract

Environment, social, and governance (ESG) disclosure has raised significant interest in academia and industry for sustainable development and investing. However, the data authenticity of the ESG disclosure is still a serious matter of concern. This study proposes a novel solution to solve the above problem. First, an ESG information disclosure system (IBESG) enabled by IoT and blockchain is originally designed. The IBESG integrates IoT and blockchain technologies to facilitate the collection and transmission of data during ESG disclosure, and to ensures the data authenticity, consistency, and transparency. Second, the authors design a Local and Global Authenticity Verification Flow (LGA) consisting of edge computing and cloud computing to sufficiently verify the authenticity through the data flow. In addition, data authenticity analytics algorithms are developed in this study, which contains event-based spatial–temporal analytics and authenticity index computation. Finally, an experimental simulation is carried out to illustrate the implementation of the IBESG and the performance of the verification solution, and the sensitivity analysis of the above solution is conducted. Moreover, the relevant suggestions on deployment are given according to the findings during the experiment, and future work on improving the algorithm and conducting experiments in field manufacturing factories is illustrated. This study is expected to help academia and industry apply the solution in similar scenarios and inspire new ideas.