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@article{166787,
        author = {Harsh Goel and Gunjan Tripathi and Samiksha Arora and Priyanka Gupta and Dr. Tripti Sharma},
        title = {Innovative Environmental Monitoring & Early Alert System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {2},
        pages = {1802-1805},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=166787},
        abstract = {This paper presents an innovative flood forecasting system integrating machine learning techniques such as k-Nearest Neighbors, logistic regression, decision trees, random forest classification, and ensemble learning. Analyzes data from weather stations, gauges, satellite imagery and GIS databases to improve accuracy and timeliness. A key feature is an SMS alert system sending real-time alerts to residents of flood-prone areas, providing information on risks, basic precautions and emergency contact numbers. This system aims to enhance disaster risk reduction efforts and community resilience.},
        keywords = {Flood prediction, Early warning system, Machine learning, SMS notification, Environmental monitoring, k-Nearest Neighbors (kNN), Logistic regression, Decision trees, Random forest classification, Ensemble learning, GIS database.},
        month = {July},
        }