abbaimam3/ResilientAI

A climate-resilience early warning system using AI, satellite data, and local languages to prevent flood disasters in Maiduguri and beyond. 🌍 ResilientAI – Predict. Prepare. Protect. ResilientAI is an AI-powered early warning and decision-support system designed to predict and mitigate the devastating impacts of flooding in vulnerable regions across Africa — starting with northeastern Nigeria. By combining weather, hydrological, and environmental data, ResilientAI empowers governments, NGOs, and communities with timely, accessible, and actionable alerts before disasters strike. --- 🚨 Problem Statement Flooding is one of the most recurring and destructive climate-related disasters in Nigeria. In September 2024, the collapse of the Alau Dam in Maiduguri displaced over 100,000 people, destroying homes, farmland, and livelihoods. The most vulnerable communities often receive little to no warning, leaving them unprepared to act. Existing early warning systems are fragmented, reactive, and largely inaccessible — especially to rural populations with limited internet access. ResilientAI aims to change this. --- 💡 Our Solution ResilientAI is a proactive, AI-powered platform that predicts flood risks up to 7 days in advance and delivers life-saving alerts through SMS, USSD, and web dashboards — even in low-connectivity regions. ✨ Core Features 📡 Data Integration: Real-time weather, river-level, and satellite data collection. 🧠 AI Flood Prediction: Machine learning models to forecast flood probability and severity. 📊 Dashboard: Interactive visualization for agencies and emergency responders. 📱 Multi-Channel Alerts: SMS/USSD notifications in Hausa, Kanuri, and English. 🌐 Scalable Architecture: Easily expandable to other regions and disaster types. --- 🛠️ Current Status This repository is under active development as part of the 3MTT Resilience Through Innovation Hackathon (2025). Current work includes: 📁 Architecture design and system planning. 📊 Prototype components for the data pipeline and dashboard. 📜 Documentation for model structure and integration. Future updates will include: ✅ Com …