Journal of E-Technology Ricardo Rodríguez Jorge 17 2 2026 https://doi.org/10.6025/jet/2026/17/2/80-96 https://www.dline.info/jet/fulltext/v17n2/jetv17n2_3.pdf Smart IoT technologies have emerged as transformative innovations for advancing sustainability through real-time monitoring and control of environmental systems. This structured review examines the application of IoT across urban infrastructure, water resource management, and smart buildings. The study highlights how integrated sensors, communication networks, and data analytics enhance operational efficiency in energy, waste, and water sectors. Specifically, it explores IoT-based water monitoring systems, detailing architectures for leak detection, quality assessment, and consumption management. A four-layer conceptual architecture comprising sensing, communication, data processing, and application layers is proposed to structure these systems. Despite significant advancements, the review identifies critical challenges hindering widespread deployment, including data security, scalability, interoperability, and high implementation costs. Comparative analyses of existing literature reveal gaps in multi-sensor integration and energy efficiency. The paper concludes that while IoT-driven systems offer immense potential for sustainable resource management and smart city development, realizing this potential requires overcoming technical fragmentation. Future research must focus on developing scalable, secure, and interoperable ecosystems through cross-sector collaboration. This synthesis provides a roadmap for advancing IoT-driven environmental monitoring to support sustainable urban governance. Additionally, the review emphasizes incorporating emerging technologies like artificial intelligence and blockchain to enhance system performance. By addressing current limitations in sensor integration and data management, stakeholders can optimize resource utilization. Ultimately, this paper underscores the critical role of IoT in achieving sustainable urban development through intelligent, data-driven environmental monitoring solutions.