[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122253-en":3,"doc-seo-122253-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},122253,1374391975076,"Riley","https://ap-avatar.wpscdn.com/avatar/14000253ca4ec9f6853?x-image-process=image/resize,m_fixed,w_180,h_180&k=1783305029341752051",8,"Research & Report","Analyzing Unmanned Aircraft System (UAS) Incidents from NASA ASRS Data Using Unsupervised Machine Learning - Thesis","The NASA Aviation Safety Reporting System (ASRS) aggregates voluntarily submitted aviation incident reports to identify recurring issues across the National Aviation System. Pilot narratives in this database are text-heavy, making manual parsing time consuming, technically demanding, and prone to subjectivity. This research analyzes unmanned aircraft system (UAS) incident narratives from January 2013 to August 2023 under applicable public aircraft or recreational operations regulations using unsupervised machine learning to uncover patterns and supports UAS safety prevention. The work extends prior language-processing research and aims to help operators understand causes and reduce incidents.","University of Arkansas, Fayetteville  \nScholarWorks@UARK  \n\n| Electrical Engineering and Computer Science Undergraduate Honors Theses | Electrical Engineering and Computer Science |\n| --- | --- |\n| 5-2025\u003Cbr>Analyzing Unmanned Aircraft System (UAS) Incidents from NASA ASRS Data Using Unsupervised Machine Learning\u003Cbr>Kacey Haws\u003Cbr>University of Arkansas, Fayetteville\u003Cbr>Follow this and additional works at: [https://scholarworks.uark.edu/elcsuht](https://scholarworks.uark.edu/elcsuht)\u003Cbr> Part of the Computer Sciences Commons\u003Cbr>Click here to let us know how this document benefits you. |  |\n\nCitation  \nHaws, K. (2025) . Analyzing Unmanned Aircraft System (UAS) Incidents from NASA ASRS Data Using Unsupervised Machine Learning. Electrical Engineering and Computer Science Undergraduate Honors Theses Retrieved from [https://scholarworks.uark.edu/elcsuht/24](https://scholarworks.uark.edu/elcsuht/24)  \nThis Thesis is brought to you for free and open access by the Electrical Engineering and Computer Science at ScholarWorks@UARK. It has been accepted for inclusion in Electrical Engineering and Computer Science Undergraduate Honors Theses by an authorized administrator of ScholarWorks@UARK. For more information, please contact [uarepos@uark.edu](uarepos@uark.edu).  \nAnalyzing Unmanned Aircraft System (UAS) Incidents from NASA ASRS Data Using Unsupervised Machine Learning  \nA thesis submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Honors Computer Science  \nby Kacey Haws  \nMay 2025  \nUniversity of Arkansas  \nAbstract  \nThe NASA Aviation Safety Reporting System (ASRS) assembles voluntarily submitted aviation safety incident reports in their database to act on the information provided. This database allows the government, companies, and citizens to submit incident or situational reports to its database to discern recurring issues in the National Aviation System (NAS) so that the proper officials can act [1] . The narratives provided in these reports are text-based, resulting in large amounts of data to process. Previous work in the University of Arkansas Aerospace Systems Engineering and Transportation Laboratory (ASYST) lab involved parsing unmanned aircraft system (UAS) incident reports manually. While these reports can successfully be parsed by humans, this analysis is time consuming, technically challenging, and can lead to subjectivity. There are also many different factors that can play into each report, including what type of aircraft, location, or human factors. In my research, I analyze UAS incident narratives from January 2013– August 2023, involving operations under Federal Aviation Regulations (FAR)“Public Aircraft Operations (UAS) or Recreational Operations / Section 44809 (UAS)” using unsupervised machine learning to discern patterns and prevention of these incidents. Analyzing these using unsupervised machine learning methods offers a quicker way to discern patterns between the reports, allowing for analysis of UAS safety and incident prevention. My research will also contribute to a continuation of Dr. Majumdar’s research, by further expanding on her work with language processing to analyze these reports by using unsupervised machine learning methods. The findings from my research may assist UAS operators to be aware of causes and reduce  \nincidents.  \nContents  \nAbstract ....................................................................................................................................... 2  \nIntroduction ................................................................................................................................. 4  \nLiterature Review ........................................................................................................................ 6  \nMethod......................................................................................................................................... 8  \nClustering.................................","cbCaiqv38q9i6Dsc","https://ap.wps.com/l/cbCaiqv38q9i6Dsc","pdf",1998461,1,33,"English","en",105,"# Abstract\n# Introduction\n## Background and motivation\n# Literature Review\n# Method\n## Clustering\n## Topic Modeling\n## N-grams\n# Results\n# Conclusion\n# References","[{\"question\":\"What problem does the thesis address regarding NASA ASRS incident narratives?\",\"answer\":\"Narratives are text-based, so manual parsing is time consuming, technically challenging, and can introduce subjectivity. The thesis targets this by automating pattern discovery from the reports.\"},{\"question\":\"Which time range and operational scope are analyzed in the research?\",\"answer\":\"The study analyzes UAS incident narratives from January 2013 to August 2023, focusing on operations under the specified FAR public aircraft or recreational operations context.\"},{\"question\":\"How does the thesis use unsupervised machine learning to improve incident analysis?\",\"answer\":\"It applies unsupervised methods to discern patterns across reports, enabling faster identification of themes that can support UAS safety and incident prevention.\"}]","Analyzing Unmanned Aircraft System (UAS) Incidents from NASA ASRS Data Using Unsupervised Machine Learning - Thesis | PDF",1785809647,83,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"analyzing-unmanned-aircraft-system-uas-incidents-from-nasa-asrs-data-using-unsupervised-machine-learning-thesis","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/analyzing-unmanned-aircraft-system-uas-incidents-from-nasa-asrs-data-using-unsupervised-machine-learning-thesis/122253/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What problem does the thesis address regarding NASA ASRS incident narratives?","Question",{"text":75,"@type":76},"Narratives are text-based, so manual parsing is time consuming, technically challenging, and can introduce subjectivity. The thesis targets this by automating pattern discovery from the reports.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which time range and operational scope are analyzed in the research?",{"text":80,"@type":76},"The study analyzes UAS incident narratives from January 2013 to August 2023, focusing on operations under the specified FAR public aircraft or recreational operations context.",{"name":82,"@type":73,"acceptedAnswer":83},"How does the thesis use unsupervised machine learning to improve incident analysis?",{"text":84,"@type":76},"It applies unsupervised methods to discern patterns across reports, enabling faster identification of themes that can support UAS safety and incident prevention.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]