Key points are not available for this paper at this time.
Abstract The increasing industrialization and urbanization have amplified pollution, leading to the release of contaminants harmful to ecosystems and human health. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. This review explored the integration of Internet-of-Things and blockchain technologies in environmental pollution monitoring and data management by examining 108 articles. The study highlighted the drawbacks of traditional monitoring methods, including high costs, time consumption, and limited scalability, prompting the adoption of Internet-of-Things-based solutions. In addition, by integrating blockchain technology, the frameworks ensure data authenticity, transparency, and traceability. A comparative analysis of existing Internet-of-Things-blockchain models shows that, while they improve real-time data monitoring and offer enhanced security, challenges such as high computational complexity and inadequate sensor coverage persist. The identified key issues include the need for more scalable, low-cost sensor systems and lightweight frameworks to handle diverse environmental data; the importance of selecting appropriate blockchain networks and consensus algorithms to balance security, scalability, and efficiency; and addressing lax-cryptic trustworthiness in the process, amongst other issues. Future directions solicit the convergence of Artificial Intelligence, Internet-of-Things, and blockchain technologies for more efficient and cost-effective pollution monitoring, to ensure real-time data security, authenticity, and environmental sustainability.
Ajakwe et al. (Wed,) studied this question.