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@article{199347,
        author = {Chidananda R and Dr. Madhavi Mallam and Nisarga N and Kushi S and Pavan Gowda D.P},
        title = {Techno Dam: Advanced Automation of Water Infrastructure using IOT and Deep Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {11715-11722},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=199347},
        abstract = {An integrated dam automation and safety monitoring system is proposed, one that eliminates the drawbacks of conventional, manual operation. This article introduces the Techno Dam system, a holistic solution that utilizes a suite of Internet of Things (IoT) technologies and deep learning to offer holistic, real-time information and automated control. For structural integrity, a deep learning model based on the YOLOv5 algorithm is used to automatically identify and classify cracks and leaks from high- resolution images, which surpasses limitations of complex visual backgrounds. Meanwhile, an ESP32 microcontroller gathers real-time information from a series of sensors for water level, water quality (pH and turbidity), and rainfall. This sensor input powers an autonomous dam gate control system that allows proactive flood prevention and maximum resource utilization. In addition, the system has an emergency alert function that sends SMS or email notifications to responsible people when it detects critical conditions using data obtained through a Telegram application. By minimizing dependence on human intervention and facilitating data-driven decision- making, the Techno Dam system greatly increases the safety, efficiency, and resilience of water infrastructure.},
        keywords = {},
        month = {April},
        }