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Existing frameworks often rely on energy-intensive consensus mechanisms (e.g., Proof of Work) or centralized architectures, limiting their applicability to large-scale, sustainable smart cities. To bridge these gaps, we propose a novel IoT blockchain framework that uniquely combines hybrid consensus mechanisms (Proof of Stake + Practical Byzantine Fault Tolerance), K-means clustering for demand-response optimization, and lightweight IoT protocols (MQTT\/CoAP) to ensure energy efficiency, scalability, and user-centric design. Our approach leverages real-world datasets (UK-DALE, PECAN Street) to train predictive models, cluster energy consumption patterns, and automate decentralized energy trading via blockchain smart contracts. Simulations demonstrate a 15% reduction in energy costs for high-consumption clusters, 80% lower energy use (50 kWh\/tx vs. 500 kWh\/tx for PoW), and near-linear scalability for 500+ IoT devices. A secure dashboard with AI-driven recommendations (e.g., peak-load alerts) further enhances stakeholder engagement. By addressing technical limitations of previous works, such as computational bottlenecks, lack of user interfaces, and poor interoperability, our framework provides actionable insights for policymakers to advance sustainable urban energy systems. These results position the proposed architecture as a transformative solution for scalable, eco-friendly smart cities.<\/jats:p>","DOI":"10.1007\/s10586-025-05677-3","type":"journal-article","created":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T18:07:13Z","timestamp":1760033233000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Integrating IoT and blockchain for smart urban energy management: enhancing sustainability through real-time monitoring and optimization"],"prefix":"10.1007","volume":"28","author":[{"given":"Mohammed","family":"Elhajj","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali El","family":"Attar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ahmad","family":"Mikati","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,10,9]]},"reference":[{"issue":"34","key":"5677_CR1","doi-asserted-by":"publisher","first-page":"8945","DOI":"10.1073\/pnas.1606035114","volume":"114","author":"B G\u00fcneralp","year":"2017","unstructured":"G\u00fcneralp, B., Zhou, Y., \u00dcrge-Vorsatz, D., Gupta, M., Yu, S., Patel, P.L., Fragkias, M., Li, X., Seto, K.C.: Global scenarios of urban density and its impacts on building energy use through 2050. 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