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@article{187999,
        author = {S Ranganathan and Dr. N. Vinoth Kumar and E. Muthuramalingam},
        title = {Water Distribution System, Leak Detection, Sensors, Wireless Sensor Networks, Signal Processing.},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {7},
        pages = {848-865},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=187999},
        abstract = {Urban water systems are facing increasing pressure to reduce non-revenue water losses, making efficient leak detection a global priority. This review offers a comprehensive examination of sensor technologies and data analytics methods, with a particular focus on their integration within intelligent IoT-enabled monitoring frameworks. The evolution of sensors has been traced from early acoustic tools to modern smart meters, fiber optics, and hybrid multi-sensor solutions, highlighting trade-offs in accuracy, cost, scalability, and deployment feasibility. Parallel advances in data analytics were reviewed, spanning statistical and signal-processing approaches to machine learning, deep learning, and hybrid AI models, demonstrating significant improvements in detection accuracy and robustness. By synthesizing these two dimensions, this study introduces a practical selection framework for aligning sensor choices with the analytical requirements and operational contexts. Comparative analyses and tabular summaries provide actionable insights for utilities, while research gaps, including small leak detection, field validation, cost–scalability challenges, and cybersecurity, are explicitly outlined. The review concludes that integrated sensor–analytics solutions, supported by IoT and digital twin technologies, represent the most promising direction for optimizing leak detection in urban water systems, bridging academic advances with practical implementation.},
        keywords = {Water Distribution System, Leak Detection, Sensors, Wireless Sensor Networks, Signal Processing.},
        month = {December},
        }