Innovative Environmental Monitoring & Early Alert System

Innovative Environmental Monitoring & Early Alert System
Author(s):
Harsh Goel, Gunjan Tripathi, Samiksha Arora, Priyanka Gupta, Dr. Tripti Sharma
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.
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.
Article Details
Unique Paper ID: 166787 Publication Volume & Issue: Volume 11, Issue 2 Page(s): 1802 - 1805
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NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

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