AI-powered flood intelligence system featuring h2oGPTe Agent + NVIDIA NIM integration (A2A), NAT pipeline with Nemotron 49B, and real-time flood risk assessment. Part of NVIDIA–H2O.ai AI for Good Blueprint for disaster response and monitoring.

Code for papers Optimal Reservoir Operations using Long Short-Term Memory Network and Bi-directional Storage Capacity and Elevation Level Calculator for Reservoir Operation Management

The main motive of the project is to predict the amount of rainfall in a particular division or state well in advance. We predict the amount of rainfall using past data.

Heterogenous Graph Attention Transformer for high-resolution, distributed spatiotemporal flood prediction. Published at ACM SIGSPATIAL 2025.

This project develops a machine learning model that predicts the likelihood of flooding in a given area using data sourced from various APIs. The model analyzes topographical and environmental factors to generate predictions, aiding in flood risk assessment and mitigation.

The Disaster Monitoring System is an app for flood prediction and earthquake classification. It uses water level, weather, and sensor data for insights.

Reinforcing-a-Monitoring-System-of-a-Regulated-River-using-ML. A multilevel intelligent flood forecast model using a combination of multi recurrent neural network (RNN) and regression models. Through comparisons with autoregressive integrated moving average (ARIMA), Gated Recurrent Unit (GRN), Long-Short Term Memory (LSTM), and BiLSTM.

The official repository accompanying the paper "Deep Vision-Based Framework for Coastal Flood Prediction Under Climate Change Impacts and Shoreline Adaptations".

Pralay Mitra is an AI-powered disaster management system designed to assist government officials in making informed decisions during emergencies. It provides real-time insights, response plans, and resource allocation strategies to handle disasters efficiently.

AquaGuard is a native iOS application designed to protect communities during flood disasters. It provides real-time alerts, safety guides, and a crowdsourced reporting system to coordinate rescue efforts effectively.

Machine learning-based flood and flash flood prediction across 8 Malaysian cities using Decision Tree, Random Forest, and XGBoost. 16-year NASA POWER MERRA-2 dataset (2010–2026).

Sahay - A predictive disaster intelligence and rapid emergency response platform. Features ML-driven river flood forecasting (ARIMA), CNN-based rainfall analysis, a lightning-fast blood bank locator, and interactive disaster SOPs. Built for DSN3099 Engineering Project in Community Service @ VIT

A small flood prediction project using Kaggle dataset,it is my first repository,I hope it will be ok QWQ

LSTM-based deep learning model for river flood prediction using PyTorch | R2=0.899 | NSE=0.899

The Flood Risk Prediction System leverages advanced machine learning and real-time weather data to accurately assess flood probability. By analyzing rainfall, humidity, and wind patterns, we provide immediate risk alerts and next-day forecasts to help communities stay safe and prepared.

Emergency Flood Forecasting (2011) 💧 How Do You Predict Floods When All Models Fail? : Grassroots forecasting system that helped 13M people prepare during Thailand's worst disaster - using only existing water data and adaptive research-based models, when conventional prediction tools broke down.

Sahay - Flood & Rainfall Intelligence: a Python web app using 1D‑CNN deep learning and ARIMA time‑series forecasting for monthly precipitation prediction and flood-risk classification. Developed for the DSN2099 Project Exhibition - II @ VIT

Machine learning research exploring flood prediction in coastal West Africa using environmental and meteorological data.

A mobile application that saves lives by notifying flood risks and provides Safe routes, tips and tricks and survival Guides.

Multi-disaster management system with IoT monitoring, emergency response & real-time alerts