{"id":15172815,"url":"https://github.com/albamerdani/iot_air_quality_ml","last_synced_at":"2026-01-27T08:33:51.352Z","repository":{"id":238981404,"uuid":"798148815","full_name":"albamerdani/iot_air_quality_ml","owner":"albamerdani","description":"IoT Project for Air Quality and Data Analysis with Machine Learning","archived":false,"fork":false,"pushed_at":"2024-05-09T11:57:23.000Z","size":308,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-06-04T12:16:05.472Z","etag":null,"topics":["air-quality","aqi","data-analysis","data-science","decision-tree","iot","machine-learning-algorithms","prediction","random-forest","raspberry-pi-3","sensors"],"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/albamerdani.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":"2024-05-09T07:29:54.000Z","updated_at":"2025-02-18T18:10:48.000Z","dependencies_parsed_at":null,"dependency_job_id":"c389639c-5985-432f-b02a-3d9652a0bb8f","html_url":"https://github.com/albamerdani/iot_air_quality_ml","commit_stats":{"total_commits":2,"total_committers":1,"mean_commits":2.0,"dds":0.0,"last_synced_commit":"8109f30110cb0d3002b0020764c4cca844a1bb3f"},"previous_names":["albamerdani/iot_air_quality_ml"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/albamerdani/iot_air_quality_ml","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/albamerdani%2Fiot_air_quality_ml","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/albamerdani%2Fiot_air_quality_ml/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/albamerdani%2Fiot_air_quality_ml/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/albamerdani%2Fiot_air_quality_ml/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/albamerdani","download_url":"https://codeload.github.com/albamerdani/iot_air_quality_ml/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/albamerdani%2Fiot_air_quality_ml/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28809627,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-27T07:41:26.337Z","status":"ssl_error","status_checked_at":"2026-01-27T07:41:08.776Z","response_time":168,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":["air-quality","aqi","data-analysis","data-science","decision-tree","iot","machine-learning-algorithms","prediction","random-forest","raspberry-pi-3","sensors"],"created_at":"2024-09-27T10:20:20.315Z","updated_at":"2026-01-27T08:33:51.328Z","avatar_url":"https://github.com/albamerdani.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# IoT for Air Quality Monitoring and Data Analyze with Machine Learning models.\n\nThis is an IoT project for Air Quality Monitoring and analyze of collected data with Machine Learning models.\n\nDataset in different formats for data of: pm2.5, pm10, temperature, humidity, air pressure, alarm.\n\nPython script for RasberryPi 3 and sensors configuration.\n\nRuns on RaspberryPi 3 to measure and collect data through sensors - `air_quality_sensor.py`\n\nPython and Jupyter scripts with ML models for data analyze for below use-cases.\n\nML Algorithms:\n- Decission Tree\n- Random Forest\n\nUse cases:\n\n- Predict alarm status for next n hours\n- Predict future n values of alarm status\n- Predict dust (or other parameters) based on historic samples in time-series\n- Predict dust (or other parameters) future n values\n- Decission Tree for alarm status based on all parameters historic values\n\n## How to run\n\nClone the repo and install the necessary libraries:\n\n`git clone https://github.com/albamerdani/iot_air_quality_ml.git\n`\n1. Install python3 and pip or pip3 - https://realpython.com/installing-python/\n2. Install libraries under requirements.txt\n\n`pip3 install -r requirements.txt`\n\n3. Run python/jupyter scripts of different use-cases\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falbamerdani%2Fiot_air_quality_ml","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Falbamerdani%2Fiot_air_quality_ml","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falbamerdani%2Fiot_air_quality_ml/lists"}