Landslide and Flood Predictor and Alert Dissemination System

Author(s)	Abhilash Ramachandran, Abhiram Anish, Dhanasree M, Sourabh Suresh, Rithya K
Country	India
Abstract	This project proposes a machine learning-based system to predict landslides and floods using historicaland real-time climate data. Traditional models often rely on static threshold values, which limits theiraccuracy. By leveraging advanced ML techniques and algorithms, this system analyses environmentalfactors like rainfall, elevation, humidity, and river water levels to provide more reliable forecasts. Themodel is trained on past disaster records and continuously improves by learning from newly fed data. Auser-friendly website will display live updates and warnings, while an alert system will send SMSnotifications to at-risk residents. By integrating real-time weather APIs and optimizing predictiveaccuracy, this project aims to enhance disaster preparedness, reduces chances of false alarms, andpromotes resilience against natural hazards for the community.
Field	Engineering
Published In	Volume 16, Issue 2, April-June 2025
Published On	2025-04-03
Cite This	Landslide and Flood Predictor and Alert Dissemination System - Abhilash Ramachandran, Abhiram Anish, Dhanasree M, Sourabh Suresh, Rithya K - IJSAT Volume 16, Issue 2, April-June 2025.

About IJSAT Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us	Message on WhatsApp	+91-9687-182-185	editor@ijsat.org

International Journal on Science and Technology