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🔥 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.
🎯 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
🧠 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
🏗️ System Architecture
+----------------------+
| 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 |
+----------------------+
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