Systematic Review of Standardized Blockchain IoT AI for Smart City Air Quality Monitoring

Traditional air quality monitoring (AQM) systems in densely populated smart cities face significant challenges regarding data integrity, spatial coverage, and real-time reporting. This systematic literature review evaluates international efforts integrating blockchain, artificial intelligence (AI), and the Internet of Things (IoT) to enhance AQM capabilities, focusing on their alignment with international standards. The study utilizes a comprehensive PRISMA-guided methodology, analyzing peer-reviewed literature published between 2015 and 2025 from major databases including IEEE Xplore, Scopus, ScienceDirect, and SpringerLink. Findings indicate significant progress in real-time pollution sensing, decentralized data security, and predictive environmental modeling through the integration of these technologies. Key challenges persist in ensuring the explainability of AI-generated predictions, achieving full adherence to lifecycle standards (ISO/IEC 30141, ISO/TC 307, ISO/IEC 23053), and aligning with institutional governance frameworks. This assessment highlights the critical need for next-generation AQM systems that are transparent, policy-aligned, standards-compliant, and capable of supporting robust institutional and citizen decision-making within global environmental governance.