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.

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.

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

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.

Spatio-Temporal flood prediction using Graph Neural Networks on Kerala Floods 2018 dataset

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

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

An end-to-end ML pipeline for flood risk prediction in Pakistan. Automates weather/terrain data collection, engineers time-series & topographical features, and trains an XGBoost model. A CLI runs the modular data, training, and prediction pipeline. Built for scalability with centralized logging.

Submission for Kenguruji team for Arnes Hackathon 2024

A collection of python notebooks containing unsupervised ML algorithms, supervised ML algorithms, and regression models I wrote as part of my research project on flood prediction.