# 🔥 Forest Fire Detection System
A comprehensive machine learning-based web application for predicting forest fire risks in Algeria using environmental factors such as temperature, humidity, wind conditions, and rainfall.
## 🌟 Features
### **ML-Powered Predictions**
- **Binary Classification Model**: Advanced machine learning algorithm for accurate fire risk assessment
- **Real-time Analysis**: Instant predictions based on environmental parameters
- **Risk Level Classification**: FIRE and NO FIRE risk categories
### **Interactive Dashboard**
- **Prediction History**: Track all your previous predictions with detailed analytics
- **Data Visualization**: Beautiful charts showing temperature trends, Fire Weather Index patterns, and risk distribution
- **Summary Statistics**: Total predictions, average FWI, highest/lowest FWI scores
- **Responsive Design**: Works seamlessly on desktop, tablet, and mobile devices
### **User Experience**
- **Smooth Navigation**: GSAP-powered smooth scrolling between dashboard sections
- **Active Page Indicators**: Clear navigation showing current page
- **Custom Scrollbars**: Beautiful, dark-themed scrollbars for better visibility
- **Hover Effects**: Interactive elements with smooth transitions and animations
### **Data Management**
- **Local Storage**: Secure storage of user prediction history
- **Data Persistence**: Predictions saved locally for privacy and convenience
- **Export Ready**: Structured data format for future analysis
## 🏗️ Project Structure
```
ML Project 1/
├── Backend/ # Python Flask Backend
│ ├── app.py # Main Flask application
│ ├── src/ # Source code
│ │ ├── logger.py # Logging configuration
│ │ ├── exception.py # Custom exception handling
│ │ ├── utils.py # Utility functions
│ │ └── pipeline/ # ML pipeline
│ │ ├── predict_pipeline.py # Prediction pipeline
│ …