---
title: README
emoji: 🏢
colorFrom: purple
colorTo: indigo
sdk: static
pinned: false
---

# 🔥 FireFusion: Bushfire Prediction & Risk Intelligence System

## 📌 Overview
**FireFusion** is an AI-powered system designed to predict bushfire risk and support early warning efforts across Victoria, Australia. By integrating multi-source environmental data and applying machine learning models, the project aims to provide accurate, timely, and actionable fire risk insights.

This project combines **predictive modelling**, **data engineering**, and **real-time data integration** to address the growing challenges of bushfire management and misinformation during crisis events.

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## 🎯 Objectives
- Predict bushfire risk using environmental and temporal data  
- Support early warning systems for communities and authorities  
- Integrate heterogeneous data sources into a unified pipeline  
- Provide reliable, data-driven insights to reduce misinformation  

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## 🧠 Model Description

### Approach
The system leverages a combination of:
- Supervised machine learning models (e.g., Random Forest, XGBoost)  
- Time-series forecasting techniques  
- Geospatial data analysis  

### Features
- Temperature, humidity, wind speed  
- Vegetation and fuel conditions  
- Historical fire records  
- Geographic and temporal patterns  

### Future Improvements
- Deep learning models (LSTM, Transformer-based forecasting)  
- Satellite imagery integration  
- Real-time streaming pipelines  

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## 🏗️ System Architecture

```text
            +----------------------+
            |   Data Sources       |
            |----------------------|
            | Weather APIs         |
            | Sensor Data          |
            | Historical Fire Data |
            +----------+-----------+
                       |
                       v
            +----------------------+
            | Data Ingestion Layer |
            +----------------------+
                       |
                       v
            +----------------------+
            | Data Processing      |
            |----------------------|
            | Cleaning             |
            | Feature Engineering  |
            +----------+-----------+
                       |
                       v
            +----------------------+
            | Modeling Layer       |
            |----------------------|
            | Training             |
            | Evaluation           |
            +----------+-----------+
                       |
                       v
            +----------------------+
            | Deployment Layer     |
            |----------------------|
            | API / Dashboard      |
            +----------------------+