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50001:2018](https://img.shields.io/badge/ISO%2050001:2018-Certified-brightgreen)](https://www.iso.org/iso-50001-energy-management.html)\n[![TISAX](https://img.shields.io/badge/TISAX-Certified-brightgreen)](https://www.enx.com/tisax/)\n\n\u003cp xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dct=\"http://purl.org/dc/terms/\"\u003e\u003ca property=\"dct:title\" rel=\"cc:attributionURL\" href=\"https://github.com/KOSASIH/egaia-core\"\u003eEGaia\u003c/a\u003e by \u003ca rel=\"cc:attributionURL dct:creator\" property=\"cc:attributionName\" href=\"https://www.linkedin.com/in/kosasih-81b46b5a\"\u003eKOSASIH\u003c/a\u003e is licensed under \u003ca href=\"https://creativecommons.org/licenses/by/4.0/?ref=chooser-v1\" target=\"_blank\" rel=\"license noopener noreferrer\" style=\"display:inline-block;\"\u003eCreative Commons Attribution 4.0 International\u003cimg style=\"height:22px!important;margin-left:3px;vertical-align:text-bottom;\" src=\"https://mirrors.creativecommons.org/presskit/icons/cc.svg?ref=chooser-v1\" alt=\"\"\u003e\u003cimg style=\"height:22px!important;margin-left:3px;vertical-align:text-bottom;\" src=\"https://mirrors.creativecommons.org/presskit/icons/by.svg?ref=chooser-v1\" alt=\"\"\u003e\u003c/a\u003e\u003c/p\u003e\n\n# egaia-core\nThe 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.\n\n# Project EGaia - Core Repository\n\n## Overview\n\nProject 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.\n\n## Features\n\n- **Biotechnology Algorithms**: Tools for genetic engineering and microbial solutions to enhance plant resilience.\n- **AI Models**: Machine learning algorithms for drone navigation and ecosystem health monitoring.\n- **Drone Control Systems**: Code for managing drone operations and data collection.\n- **Data Processing**: Functions for cleaning, analyzing, and visualizing ecological data.\n- **Community Engagement Tools**: Resources for education and citizen science participation.\n\n## Installation\n\nTo set up the `egaia-core` project locally, follow these steps:\n\n1. **Clone the Repository**:\n   ```bash\n   1 git clone https://github.com/KOSASIH/egaia-core.git\n   2 cd egaia-core\n   ```\n\n 2. **Create a Virtual Environment (optional but recommended)**:\n\n    ```bash\n    1 python -m venv venv\n    2 source venv/bin/activate  # On Windows use `venv\\Scripts\\activate`\n    ```\n\n3. **Install Dependencies**:\n\n   ```bash\n   1 pip install -r requirements.txt\n   ```\n   \n## Usage\n\n### Running Examples\n\nTo run the example scripts provided in the examples/ directory, use the following command:\n\n   ```bash\n   1 python examples/reforestation_example.py\n   ```\n\n### Running Tests\n\nTo ensure that everything is working correctly, you can run the unit tests:\n\n   ```bash\n   1 pytest tests/\n   ```\n\n# Contributing\nContributions are welcome! Please read the [CONTRIBUTING.md](CONTRIBUTING.md) file for guidelines on how to contribute to the project.\n\n# License\nThis project is licensed under the MIT License. See the [LICENSE](LICENSE) file for more details.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkosasih%2Fegaia-core","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkosasih%2Fegaia-core","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkosasih%2Fegaia-core/lists"}