Rockfall Prediction System for Indian Open Pit Mines A comprehensive machine learning system for predicting rockfall hazards in Indian open pit mining operations.
🎯 Project Overview This project implements a state-of-the-art machine learning system to predict rockfall risks in open pit mines across India. The system considers geological, environmental, and operational factors specific to Indian mining conditions including monsoon impacts, diverse geology, and varying mining practices.
🔧 Features Multi-factor Risk Assessment: Considers 20+ geological, environmental, and operational parameters
Indian Mining Context: Specifically designed for Indian geological conditions and monsoon climate
Multiple ML Algorithms: Supports Random Forest, Gradient Boosting, and XGBoost
Real-time Predictions: Interactive prediction interface for immediate risk assessment
Comprehensive Reporting: Detailed risk reports with actionable recommendations
Dashboard Visualization: Interactive dashboards for risk monitoring
📁 Project Structure text rockfall_prediction_openpit_india/ ├── data/ │ ├── raw/ # Raw mining data │ ├── processed/ # Processed datasets │ └── external/ # External data sources ├── src/ │ ├── data_processing/ # Data loading and preprocessing │ ├── models/ # ML model implementations │ ├── visualization/ # Dashboard and plotting utilities │ └── utils/ # Helper functions ├── notebooks/ # Jupyter notebooks for analysis ├── reports/ # Generated reports and figures ├── models/ # Trained model artifacts ├── config/ # Configuration files ├── tests/ # Unit tests └── logs/ # Application logs 🚀 Quick Start Installation bash
git clone https://github.com/yourusername/rockfall