{"id":25627157,"url":"https://github.com/rohitinu6/room-occupancy-detection","last_synced_at":"2026-05-06T15:40:12.740Z","repository":{"id":269772969,"uuid":"908418283","full_name":"rohitinu6/Room-Occupancy-Detection","owner":"rohitinu6","description":"This project predicts room occupancy based on sensor data using machine learning techniques.","archived":false,"fork":false,"pushed_at":"2025-02-06T03:10:42.000Z","size":1449,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-22T17:37:54.302Z","etag":null,"topics":["data-science","eda","jupyter-notebook","machine-learning","machine-learning-algorithms","python","room-occupancy","sensor-data","visualization"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/rohitinu6.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-12-26T03:09:30.000Z","updated_at":"2025-02-06T03:11:38.000Z","dependencies_parsed_at":"2024-12-26T04:20:59.375Z","dependency_job_id":"372d4346-50de-4b12-981a-beb2a1d1a1eb","html_url":"https://github.com/rohitinu6/Room-Occupancy-Detection","commit_stats":null,"previous_names":["rohitinu6/room-occupancy-detection"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/rohitinu6/Room-Occupancy-Detection","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rohitinu6%2FRoom-Occupancy-Detection","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rohitinu6%2FRoom-Occupancy-Detection/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rohitinu6%2FRoom-Occupancy-Detection/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rohitinu6%2FRoom-Occupancy-Detection/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/rohitinu6","download_url":"https://codeload.github.com/rohitinu6/Room-Occupancy-Detection/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rohitinu6%2FRoom-Occupancy-Detection/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":284236310,"owners_count":26970090,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-11-13T02:00:06.582Z","response_time":61,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["data-science","eda","jupyter-notebook","machine-learning","machine-learning-algorithms","python","room-occupancy","sensor-data","visualization"],"created_at":"2025-02-22T17:32:32.649Z","updated_at":"2025-11-13T15:01:45.612Z","avatar_url":"https://github.com/rohitinu6.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Room Occupancy Detection\n\n## 📌 Project Overview\n\nThis project predicts room occupancy based on sensor data using machine learning techniques. The goal is to improve energy efficiency in buildings by dynamically adjusting heating, lighting, and cooling based on occupancy status.\n\n## 🚀 Features\n\n- Data preprocessing and exploratory data analysis (EDA)\n- Feature engineering and sensor data analysis\n- Machine learning model development and evaluation\n- Model interpretability and visualization\n\n## 🛠 Tech Stack\n\n- Python\n- Pandas, NumPy\n- Scikit-learn\n- Matplotlib, Seaborn\n- Jupyter Notebook\n\n## 📂 Dataset\n\nThe dataset consists of sensor readings such as:\n\n- **Temperature**\n- **Humidity**\n- **Light Levels**\n- **CO2 Levels**\n- **Occupancy Status**\n\n## 📊 Machine Learning Models Used\n\n- Logistic Regression\n- Random Forest Classifier\n- Support Vector Machine (SVM)\n- XGBoost\n\n## 🔥 Results\n\nThe models are evaluated based on accuracy, precision, recall, and AUC-ROC score. The best model provides reliable predictions for room occupancy.\n\n## 📁 Repository Structure\n\n```\n📂 Room-Occupancy-Detection\n👉 📂 data (Dataset \u0026 processed data)\n👉 📂 notebooks (Jupyter Notebooks)\n👉 📂 models (Trained models)\n👉 📂 images (Code and Results Screenshots)\n👉 📄 README.md (Project documentation)\n```\n\n## 🖼 Code and Results\n\nInclude images of code and results in the `images` folder. Example:\n\n\u0026#x20;\n\n## 📝 How to Run the Project\n\n1. Clone the repository:\n   ```bash\n   git clone https://github.com/rohitinu6/Room-Occupancy-Detection.git\n   ```\n2. Navigate to the project folder:\n   ```bash\n   cd Room-Occupancy-Detection\n   ```\n3. Install dependencies:\n   ```bash\n   pip install -r requirements.txt\n   ```\n4. Run the Jupyter Notebook or Python scripts to train and test models.\n\n## 📡 Links\n\n- **GitHub Repository:** [Room Occupancy Detection](https://github.com/rohitinu6/Room-Occupancy-Detection.git)\n- **Portfolio:** [Rohit Dubey](https://tinyurl.com/dubeyrohit)\n- **GitHub Profile:** [rohitinu6](https://github.com/rohitinu6)\n- **LinkedIn:** [Rohit Dubey](https://www.linkedin.com/in/rohit-dubey-d/)\n- **Twitter/X:** [@rohitdubey003](https://x.com/rohitdubey003)\n\n## 💖 Tags\n\n`Machine Learning` `Room Occupancy` `Sensor Data` `Data Science` `Python` `EDA`\n\n## 📝 License\n\nThis project is licensed under the [MIT License](https://opensource.org/licenses/MIT).\n\n---\n\n💡 **For any queries or collaboration opportunities, feel free to connect!** 🚀\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frohitinu6%2Froom-occupancy-detection","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frohitinu6%2Froom-occupancy-detection","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frohitinu6%2Froom-occupancy-detection/lists"}