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@article{190220,
        author = {Aniket Tiwari and Sonali Zunke and Ujjwal Oza and Faizan Sheikh and Harsh Gupta and Akshad Shende},
        title = {Early Flood Detection and Village Alert System with AI and LoRa and IoT to Water Dams},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {8},
        pages = {3951-3961},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=190220},
        abstract = {The overflowing dams may lead to devastating effects because of floods, particularly to remote and rural villages that have poor connectivity. This project will be an AI-based Early Flood Detection and Alert System which will use IoT sensors, LoRa SX1278 communication modules and microcontrollers of ESP8266 to detect the water levels in the dam in real time and send alerts to the nearby villages. The system constantly monitors the level of water with high- precision sensors and sends it to the central server and the LoRa-based receiver nodes deployed in villages. Emergency alerts are triggered in case of increased water levels, reaching the danger points, through alarms, LED indicators, and, optionally, SMS, and will alert the villagers early enough even where there is no internet connectivity. The Generative AI model is embedded in the backend server to interpret historical and real-time water data so that it predicts the possible overflowing cases and sends preventive notifications. This hybrid system provides robust and offline communication capabilities with active decision-making that can save lives and can reduce the response time by a large margin. Long-term analysis and forecasting is also supported on the stored data (water level, date, and time) in the central database. The system will be low-cost, scalable and highly reliable, thus, suitable in flood prone rural areas in India and other countries.},
        keywords = {},
        month = {January},
        }