A Real-Time Location-Based Flood and Landslide Risk Prediction System Using Machine Learning and Live Weather Data

• Author(s): G. Poovizhi; M. Sirisha; S. Sobana; A. Vidhyalakshmi; M. Samundeeswari
• Paper ID: 1717650
• Page: 1443-1451
• Published Date: 13-05-2026
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 11 May-2026

Abstract

Every year, millions of lives are lost because of floods, landslides, and other types of natural disasters, particularly in South Asia, owing to the absence of early warning systems that can be considered effective. The purpose of this paper is to present our product, "Flood Guard Pro" – a system to predict imminent flooding and landslides using real-time data and location-based information. The proposed system uses a three-layered architecture consisting of the React 18 frontend and Python Flask backend as well as the SQLite database. Data on live weather conditions, including rainfall, humidity, temperature, and pressure, will be provided by OpenWeatherMap.The risk zones will be assessed based on the rule-based algorithm, together with the usage of Haversine distance. Thus, it will be possible to establish whether a particular area poses low, medium, or high risks (safe zone, flood, and landslide prone areas correspondingly).Additionally, the system will feature a two-language chatbot, created using AI technology and capable of offering safety guidelines to users. Other important additions will include offline availability, OTP login, voice commands and notifications, admin panel, etc.

Keywords

Flood Prediction, Landslide Risk, Real-Time Alert System, Haversine Distance, OpenWeatherMap API, React, Flask, Progressive Web App, Geolocation, Bilingual Chatbot, Disaster Management

Citations

IRE Journals:
G. Poovizhi, M. Sirisha, S. Sobana, A. Vidhyalakshmi, M. Samundeeswari "A Real-Time Location-Based Flood and Landslide Risk Prediction System Using Machine Learning and Live Weather Data" Iconic Research And Engineering Journals Volume 9 Issue 11 2026 Page 1443-1451

IEEE:
G. Poovizhi, M. Sirisha, S. Sobana, A. Vidhyalakshmi, M. Samundeeswari "A Real-Time Location-Based Flood and Landslide Risk Prediction System Using Machine Learning and Live Weather Data" Iconic Research And Engineering Journals, 9(11)