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https://github.com/n-elmer/natural-disaster-prediction-system
LANDSLIDE ⛰ PREDICTOR 📈
https://github.com/n-elmer/natural-disaster-prediction-system
arduino c c-plus-plus iot jupyter-notebook machine-learning prediction python sql system-development
Last synced: 4 days ago
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LANDSLIDE ⛰ PREDICTOR 📈
- Host: GitHub
- URL: https://github.com/n-elmer/natural-disaster-prediction-system
- Owner: N-Elmer
- License: apache-2.0
- Created: 2023-01-14T20:41:58.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2025-01-17T14:19:30.000Z (9 days ago)
- Last Synced: 2025-01-17T15:25:25.208Z (9 days ago)
- Topics: arduino, c, c-plus-plus, iot, jupyter-notebook, machine-learning, prediction, python, sql, system-development
- Language: Jupyter Notebook
- Homepage:
- Size: 9.37 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# NATURAL-DISASTER-PREDICTION-SYSTEM
LANDSLIDE ⛰📈 PREDICTOR
A comprehensive AI-Powered embedded system designed to predict the possibility of landslides in an area based on real-time environmental sensor data and machine learning analysis.
## Features
- **Real-time Monitoring**: Collects environmental data using Arduino-based sensors.
- **Data Processing**: Processes sensor data for soil moisture, temperature, humidity and light intensity.
- **Local Storage**: Stores sensor readings in local database for offline analysis.
- **Remote Storage**: Syncs data with remote database for backup and distributed access.
- **Machine Learning**: Uses scikit-learn models to predict landslide probability.
- **Visualization**: Interactive plots and graphs using matplotlib and seaborn.
- **Hardware Design**: Complete electronic system design in Proteus.
- **Web Interface**: Online dashboard for monitoring and predictions.
## Project Structure
```
NATURAL-DISASTER-PREDICTION-SYSTEM/
├── APPLICATION/ 📊
│ └── NATURAL DISASTER PREDICTION SYSTEM.ipynb 🤖 ML model training notebook
├── DATABASE/ 💾
│ ├── msodbcsql_2.msi 🔌 SQL driver
│ ├── msodbcsql.msi 🔌 SQL driver
│ ├── Plant & Environmental Data.sql 📝 SQL database
│ └── Plant & Environmental Data.sql.bak 💾 Backup file
├── DOCUMENTATION/ 📚
├── HARDWARE/ 🔧
│ ├── environmentalData_MainClass_PrimaryArduino/
│ │ └── environmentalData_MainClass_PrimaryArduino.ino 🎯 Primary Arduino code
│ ├── environmentalData_MainClass_SupportArduino/
│ │ └── environmentalData_MainClass_SupportArduino.ino 🔄 Support Arduino code
│ └── environmentalData_MonitorClass_SupportArduino/
│ └── environmentalData_MonitorClass_SupportArduino.ino 📡 Monitoring code
├── INTERFACE/ 🖥️
├── PROTEUS/ ⚡
│ ├── Electronic Design Files
│ └── Circuit Simulations
└── SCHEMATICS/ 📐
└── SOFTWARE DESIGN/
├── arduino class diagram.uxf 📊 Class diagram
├── arduino E-R diagram.uxf 📊 E-R diagram
├── arduino sequence diagram.uxf 📊 Sequence diagram
└── arduino use case diagram.uxf 📊 Use case diagram
```
## Hardware Components
- Arduino microcontroller
- Soil moisture sensors
- Temperature and humidity sensors
- Light intensity sensors
- LCD display
- Buzzers for alerts
- Relay for fan control
- Stepper motor controller
## Getting Started
### Prerequisites
- Arduino IDE
- Python 3.8+
- Proteus 8.7+
- Required sensors and components
- Web browser
### Hardware Setup
1. Follow the Proteus circuit design to assemble the hardware components
2. Upload the Arduino code to the microcontroller:
```bash
arduino-cli compile --upload Arduino_Code.ino
```
### Software Installation
1. Clone this repository:
```bash
git clone https://github.com/N-Elmer/NATURAL-DISASTER-PREDICTION-SYSTEM.git
cd NATURAL-DISASTER-PREDICTION-SYSTEM
```
2. Install Python dependencies:
```bash
pip install -r requirements.txt
```
3. Access the web interface at:
```
https://s7ac6zkycfusqzuh.anvil.app/D3COVOGNRLN7VLXFJ3FJ7DD2
```
## Key Features
### Data Collection
- Real-time sensor readings for:
- Soil moisture levels
- Temperature
- Air humidity
- Light intensity
### Data Processing
- Signal conditioning
- Noise filtering
- Data normalization
- Feature extraction
### Prediction System
- Machine learning models for landslide prediction
- Real-time probability assessment
- Historical data analysis
- Alert generation
### Visualization
- Interactive dashboards
- Time-series plots
- Sensor data graphs
- Prediction confidence metrics
## Dependencies
- **Hardware**:
- Arduino libraries
- Sensor drivers
- LCD library
- **Software**:
- pandas: Data manipulation
- scikit-learn: Machine learning
- matplotlib: Data visualization
- seaborn: Statistical plotting
## Contributing
Contributions are welcome! Please feel free to submit issues and pull requests.
## License
This project is licensed under the Apache License - see the LICENSE file for details.
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Powered by AI 🤖 and ⚡ Iot
Web Interface: [Live Demo](https://s7ac6zkycfusqzuh.anvil.app/D3COVOGNRLN7VLXFJ3FJ7DD2)
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