egaia-core
EGaia by KOSASIH is licensed under Creative Commons Attribution 4.0 International
egaia-core
The egaia-core repository serves as the foundational framework for Project EGaia, encompassing essential algorithms, data models, and tools for ecological restoration initiatives. This core library integrates biotechnology and AI-driven solutions to facilitate the development of resilient plant species, optimize reforestation efforts, and monitor ecosystem health. Designed for collaboration and scalability, egaia-core empowers researchers, developers, and environmentalists to contribute to sustainable practices and biodiversity restoration efforts worldwide.
Project EGaia - Core Repository
Overview
Project EGaia is an innovative ecological restoration initiative that leverages biotechnology, artificial intelligence, and community engagement to combat climate change and biodiversity loss. The egaia-core repository serves as the foundational framework for the project, providing essential algorithms, data models, and tools for ecological restoration efforts.
Features
- Biotechnology Algorithms: Tools for genetic engineering and microbial solutions to enhance plant resilience.
- AI Models: Machine learning algorithms for drone navigation and ecosystem health monitoring.
- Drone Control Systems: Code for managing drone operations and data collection.
- Data Processing: Functions for cleaning, analyzing, and visualizing ecological data.
- Community Engagement Tools: Resources for education and citizen science participation.
Installation
To set up the egaia-core project locally, follow these steps:
- Clone the Repository:
1 git clone https://github.com/KOSASIH/egaia-core.git 2 cd egaia-core -
Create a Virtual Environment (optional but recommended):
1 python -m venv venv 2 source venv/bin/activate # On Windows use `venv\Scripts\activate` -
Install Dependencies:
1 pip install -r requirements.txt
Usage
Running Examples
To run the example scripts provided in the examples/ directory, use the following command:
1 python examples/reforestation_example.py
Running Tests
To ensure that everything is working correctly, you can run the unit tests:
1 pytest tests/
Contributing
Contributions are welcome! Please read the CONTRIBUTING.md file for guidelines on how to contribute to the project.
License
This project is licensed under the MIT License. See the LICENSE file for more details.