{"id":16719505,"url":"https://github.com/junzis/flight-data-processor","last_synced_at":"2025-03-21T21:30:35.821Z","repository":{"id":87602018,"uuid":"52149903","full_name":"junzis/flight-data-processor","owner":"junzis","description":"Flight data clustering and flight phase identification","archived":false,"fork":false,"pushed_at":"2020-07-23T21:43:28.000Z","size":4340,"stargazers_count":54,"open_issues_count":1,"forks_count":18,"subscribers_count":8,"default_branch":"master","last_synced_at":"2025-03-01T09:51:23.528Z","etag":null,"topics":["fuzzy-logic","machine-learning"],"latest_commit_sha":null,"homepage":"","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/junzis.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}},"created_at":"2016-02-20T11:23:27.000Z","updated_at":"2025-02-17T21:28:22.000Z","dependencies_parsed_at":null,"dependency_job_id":"6b8ddf44-eadd-403b-9c64-17a999897b62","html_url":"https://github.com/junzis/flight-data-processor","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/junzis%2Fflight-data-processor","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/junzis%2Fflight-data-processor/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/junzis%2Fflight-data-processor/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/junzis%2Fflight-data-processor/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/junzis","download_url":"https://codeload.github.com/junzis/flight-data-processor/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244160020,"owners_count":20408019,"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":["fuzzy-logic","machine-learning"],"created_at":"2024-10-12T21:41:54.161Z","updated_at":"2025-03-21T21:30:34.475Z","avatar_url":"https://github.com/junzis.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Flight Data Processor\n\nThis is a python library to process and analyze flight data (e.g. from decoded ADS-B messages). Following functions and algorithms are implemented:\n\n- Extract continuous full or partial flight path data\n  - Unsupervised Machine Learning, Clustering using DBSCAN\n- Smoothing, filtering, and interpolating flight data\n  - Spline filtering\n  - Weighted average filtering\n  - Time-based weighted average filtering\n- Segmenting flight into different phases:\n  - using Fuzzy Logic with data interpolation methods\n  - supporting phases: ground, climb, descend, cruise, and level flight\n\n# Paper and citation\n\nThe source code of this repository complements the following publication:\n\nhttps://arc.aiaa.org/doi/10.2514/1.I010520\n\nIf you use the code for your research, please cite:\n```\n@article{sun2017flight,\n  title={Flight Extraction and Phase Identification for Large Automatic Dependent Surveillance--Broadcast Datasets},\n  author={Sun, Junzi and Ellerbroek, Joost and Hoekstra, Jacco},\n  journal={Journal of Aerospace Information Systems},\n  pages={1--6},\n  year={2017},\n  publisher={American Institute of Aeronautics and Astronautics}\n}\n```\n\n# Required software\n- Python 3.x\n- MongoDB 3\n- Dependent Python libraries\n  - scipy\n  - scikit-learn\n  - skfuzzy\n  - pymongo\n\n# Code examples\n\n## 1. Flight clustering\n\n1. install MongoDB\n\n2. extract flight from ADS-B positions\n\n    ```bash\n    $ python flightextract.py --csv data/sample_adsb_decoded.csv --db test_db --coll flights\n    ```\n\n## 2. Fuzzy segmentation\nYou can use previously created collection in MongoDB. Or, using provided pickled data, run:\n\n```bash\n$ python test_phases.py\n```\n\nThe essential code to identify the flight phases is:\n\n```python\nimport flightphase\nflightphase.fuzzylabels(times, alts, spds, rocs)\n```\n\n## 3. View flights\n\nUse the same previously created MongoDB collection:\n\n```bash\n$ python flightview.py --db test_db --coll flights\n```\n\n\n## Screen shots\n### example flight phase identification\n![flight phases](data/images/phase.png?raw=true)\n\n### example fuzzy logic membership functions\n![fuzzy logic membership](data/images/membership.png?raw=true)\n\n### example flight viewer\n![flight viewer](data/images/flightview.png?raw=true)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjunzis%2Fflight-data-processor","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjunzis%2Fflight-data-processor","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjunzis%2Fflight-data-processor/lists"}