This prototype presents the full technical, conceptual, and computational design of my AI-based Flood Prediction System, created for the Model Display Competition by Islami Jamiat Talibat Sialkot (The Beacon) under the theme “Can We Stop the Next Flood?”.

I developed every component—the machine learning model, data preprocessing pipeline, risk scoring system, explainability logic, recommendation engine, and Gradio-based chatbot interface. My teammate Tooba Noor created the dynamic Flood-Risk Meter (visual display), and we integrated both components into a unified system.

This project secured 1st Position in a city-wide Model Display Competition, standing out among all competing models for its technical depth, innovation, and practical real-world relevance.

Problem Statement

Floods in Pakistan are a recurring natural disaster, causing significant human, economic, and environmental losses. Contributing factors include monsoon variability, climate change, rapid urbanization, poor drainage systems, and melting glaciers. Current flood monitoring and prediction systems often suffer from delayed reporting, limited real-time insights, and a lack of accessible visualizations, which results in:

• Delayed emergency responses
• Insufficient early warnings for vulnerable communities
• Inefficient resource allocation by disaster management authorities
• Limited public awareness about flood risks

Therefore, there is a need for an AI-powered system that can:

1. Analyze multiple environmental factors automatically.
2. Predict flood risk with measurable accuracy
3. Offer real-time, visual, and intuitive alerts
4. Provide recommendations to reduce damage

Objective of the Project