{"id":18183632,"url":"https://github.com/aaronmalunga/omdena_hackathon_live-cinds-emissions","last_synced_at":"2025-04-07T11:46:28.946Z","repository":{"id":260539121,"uuid":"880272613","full_name":"aaronmalunga/Omdena_Hackathon_Live-CINDS-Emissions","owner":"aaronmalunga","description":"Real-time Carbon Emissions of 5 Nations [Costa Rica, Iceland, Norway,Denmark and Sweden]  that are leveraging AI to reduce Green House Gas(C02).","archived":false,"fork":false,"pushed_at":"2024-11-01T11:49:51.000Z","size":311,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-13T14:41:33.277Z","etag":null,"topics":["ai","api","geolocation","ghg-emissions","gis","streamlit","streamlit-webapp"],"latest_commit_sha":null,"homepage":"https://omdena-hackathon-live-cinds-emissions.streamlit.app/","language":"Python","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/aaronmalunga.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":"2024-10-29T12:38:13.000Z","updated_at":"2024-11-02T09:15:07.000Z","dependencies_parsed_at":"2024-11-01T12:19:28.879Z","dependency_job_id":"58f9154e-88f5-4511-91f5-b96122560f6a","html_url":"https://github.com/aaronmalunga/Omdena_Hackathon_Live-CINDS-Emissions","commit_stats":null,"previous_names":["aaronmalunga/omdena_hackathon_real-time-emissions","aaronmalunga/omdena_hackathon_live-cinds-emissions"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aaronmalunga%2FOmdena_Hackathon_Live-CINDS-Emissions","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aaronmalunga%2FOmdena_Hackathon_Live-CINDS-Emissions/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aaronmalunga%2FOmdena_Hackathon_Live-CINDS-Emissions/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aaronmalunga%2FOmdena_Hackathon_Live-CINDS-Emissions/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/aaronmalunga","download_url":"https://codeload.github.com/aaronmalunga/Omdena_Hackathon_Live-CINDS-Emissions/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247648911,"owners_count":20972942,"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","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":["ai","api","geolocation","ghg-emissions","gis","streamlit","streamlit-webapp"],"created_at":"2024-11-02T20:03:40.734Z","updated_at":"2025-04-07T11:46:28.923Z","avatar_url":"https://github.com/aaronmalunga.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\r\n# **CINDS Carbon Intensity Visualization Platform**\r\n\r\n## __Overview__\r\n\r\nThe **CINDS** Carbon Intensity Visualization Platform is a web-based application developed to provide real-time carbon intensity data from select countries with a strong commitment to low-carbon practices: **Costa Rica**, **Iceland**, **Norway**, **Denmark**, **and Sweden**. The platform maps the carbon emissions across these countries, allowing users to visually assess energy impact in specific regions and leverage data for sustainability discussions.\r\n\r\n## **Features**\r\n\r\n* **Live Carbon Intensity Data:** Integrated with the Electricity Maps API, providing up-to-date **gCO₂/kWh** values for each selected country.\r\n* **Color-Coded Intensity Indicators:** The application uses dynamic color codes on location markers to indicate varying levels of carbon intensity, ranging from green (low) to red (high).\r\n* **Country-Specific Information:** Detailed information on each country’s carbon profile, flag, and real-time intensity is displayed alongside the map for enhanced user insight.\r\n* **Interactive World Map:** A folium-powered map providing visual insights into emission data, with landmasses of selected countries colorized according to their carbon intensity levels.\r\n\r\n## **Countries in CINDS**\r\n\r\nThese countries are highlighted due to their exemplary progress toward low-carbon energy and sustainability:\r\n\r\n* **Costa Rica (CR)**\r\n* **Iceland (IS)**\r\n* **Norway (NO)**\r\n* **Denmark (DK)**\r\n* **Sweden (SE)**\r\n\r\n\r\nThe countries within the **CINDS group—Costa Rica, Iceland, Norway, Denmark, and Sweden**—are leveraging **Artificial Intelligence (AI)** to advance their energy sectors and environmental sustainability. Below is an overview of each nation's initiatives:\r\n\r\n**Costa Rica**\r\n\r\n**Costa Rica** is utilizing AI to monitor deforestation and analyze ecological data, aiding in the [protection](https://ticotimes.net/2023/11/08/ai-and-eco-acoustics-safeguard-macaws-in-costa-rica) of its rich [biodiversity](https://www.mcgill.ca/desautels/channels/news/artificial-intelligence-helping-costa-rica-ngos-preserve-biodiversity-351756). The integration of AI in these areas presents an innovative narrative that highlights the intersection of technology and environmental stewardship.\r\n\r\n**Iceland**\r\n\r\nLeveraging its geothermal resources, **Iceland** has invested in **AI** to optimize energy production and consumption. The country is also exploring **AI** applications in managing [fisheries](https://vericatch.com/the-rise-of-ai-in-fisheries-technology/), ensuring sustainable practices that protect marine ecosystems. This narrative illustrates the role of **AI** in supporting sustainable practices in unique environmental contexts. \r\n\r\n**Norway**\r\n\r\n**Norway** is a global leader in electric vehicle [(EV)](https://www.mckinsey.com/industries/automotive-and-assembly/our-insights/what-norways-experience-reveals-about-the-ev-charging-market) adoption and has implemented AI-driven solutions for managing its energy grid. The country utilizes predictive analytics to forecast energy demand and optimize the dispatch of renewable resources. This synergy between **AI** and energy management provides a compelling narrative about how technology can facilitate the transition to a low-carbon economy. \r\n\r\n**Denmark**\r\n\r\n**Denmark** is recognized for its ambitious climate goals and has integrated **AI** into its wind energy sector to enhance predictive maintenance and operational efficiency. The country's focus on smart grids and energy storage solutions showcases the transformative potential of [**AI**](https://www.energycluster.dk/en/new-drone-technology-uses-artificial-intelligence-to-examine-offshore-wind-turbine-blades/) in maximizing renewable energy output and achieving carbon neutrality. \r\n\r\n**Sweden**\r\n\r\nKnown for its advanced energy policies, **Sweden** has made significant strides in reducing carbon emissions through the use of [**AI**](https://www.ai.se/en/sector-initiatives/energy). The country is leveraging machine learning algorithms to optimize energy consumption, improve renewable energy integration, and enhance public transportation systems. This positions Sweden as a leader in utilizing **AI** for climate action, making it a pertinent case study in the **AI** domain.\r\n  \r\nEach of these nations represents a significant case study in sustainable energy, ranging from extensive renewable energy use to pioneering *carbon-neutrality initiatives*.\r\n\r\n## **Technology Stack**\r\n\r\n* **Streamlit:** For interactive web interface.\r\n* **Folium:** For map rendering and visualization.\r\n* **Electricity Maps API:** For real-time carbon intensity data.\r\n* **Python:** Primary language for backend processing.\r\n* **Environment Management:** .env file for securely managing API keys.\r\n\r\n## Setup and Installation\r\n\r\n1. Clone the repository:\r\n```bash\r\ngit clone https://github.com/aaronmalunga/Omdena_Hackathon_Real-Time-Emissions.git\r\n```\r\n```\r\ncd Omdena_Hackathon_Real-Time-Emissions\r\n```\r\n\r\n2. Install dependencies:\r\n```bash\r\npip install -r requirements.txt\r\n```\r\n\r\n3. Add your [Electricity Maps API key](https://api-portal.electricitymaps.com/) in the `.streamlit/secrets.toml` file:\r\n```plaintext\r\n[api_keys]\r\nELECTRICITY_MAPS_API_KEY = \"your_api_key_here\"\r\n```\r\n\r\n4. Run the application:\r\n```bash\r\nstreamlit run app.py\r\n```\r\n\r\n## **Usage**\r\n\r\nOnce the application is running, users can:\r\n\r\n1. View real-time carbon intensity data by country on the map.\r\n2. Access country-specific information on carbon intensity and sustainability initiatives, shown on the side panel.\r\n\r\n \u003cdiv align=\"center\"\u003e  \r\n   \r\n![Carbon intensity Map](https://github.com/aaronmalunga/Omdena_Hackathon_Real-Time-Emissions/blob/main/Carbon%20intensity%20map.PNG)\r\n\r\n\u003c/div\u003e\r\n\r\n## **Sample Output**\r\n\r\n\u003cdiv align=\"center\"\u003e\r\n  \r\n![Carbon intensity CINDS](https://github.com/aaronmalunga/Omdena_Hackathon_Real-Time-Emissions/blob/main/carbon%20intensity%20CINDS.PNG)\r\n\r\n\u003c/div\u003e\r\n\r\n## **Future Improvements**\r\n\r\n* **Expanded Country Data:** Adding more countries from different regions.\r\n* **Historical Data Analysis:** Incorporating historical emission data to track trends.\r\n* **Comparative Analytics:** Enabling comparison between current and past data.\r\n  \r\n## **License**\r\n\r\nThis project is licensed under the MIT License.\r\n\r\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faaronmalunga%2Fomdena_hackathon_live-cinds-emissions","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Faaronmalunga%2Fomdena_hackathon_live-cinds-emissions","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faaronmalunga%2Fomdena_hackathon_live-cinds-emissions/lists"}