Skip to content

FireWatch AI utilizes an advanced machine learning model to predict future wildfires based on key features identified by the same AI.

Notifications You must be signed in to change notification settings

mashaaahsam/FireWatch

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 

Repository files navigation

FireWatch: Fire Prediction AI Model

Project Overview

FireWatch AI utilizes an advanced machine learning model to predict future wildfires based on key features identified by the same AI.

Features

Fire Prediction: Predict the occurrence of wildfires based on historical data and weather conditions.

Real-Time Heat Maps: Visualize predicted fire locations using interactive heat maps.

Installation

To run this project, you need to install the following libraries:

  • pandas
  • numpy
  • joblib
  • folium
pip install xgboost pandas scikit-learn folium geopandas joblib

Usage

  1. Load the Dataset: Update the file_path variable with the path to your dataset.
  2. Train the Model: The script will preprocess the data, train the XGBoost classifier, and evaluate its performance.
  3. Generate Predictions: The script will generate predictions for the entire dataset and create a heat map of predicted fire locations.
  4. Visualize: The heat map will be saved as an HTML file (fire_prediction_heatmap.html).

Code Structure

  • Data Preprocessing: Handles missing values and converts feature columns to integers.
  • Model Training: Splits the data into training, validation, and test sets. Trains the XGBoost model and evaluates its performance.
  • Model Evaluation: Outputs accuracy, classification report, and confusion matrix.
  • Model Saving: Saves the trained model using joblib.
  • Visualization: Creates a heat map of predicted fire locations using Folium.

About

FireWatch AI utilizes an advanced machine learning model to predict future wildfires based on key features identified by the same AI.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages