Innovative Environmental Monitoring & Early Alert System

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Harsh Goel; Gunjan Tripathi; Samiksha Arora; Priyanka Gupta; Dr. Tripti Sharma

Innovative Environmental Monitoring & Early Alert System

Authors: Harsh Goel, Gunjan Tripathi, Samiksha Arora, Priyanka Gupta, Dr. Tripti Sharma

Unique Paper ID: 166787
Volume: 11
Issue: 2
PageNo: 1802-1805

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.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 2
PageNo: 1802-1805

Innovative Environmental Monitoring & Early Alert System

Available:https://ijirt.org/article?manuscript=166787

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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