Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/162347
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dc.contributor.authorHu, Xintingen_US
dc.contributor.authorPang, Bizhaoen_US
dc.contributor.authorLow, Kin Huaten_US
dc.date.accessioned2022-11-04T01:22:49Z-
dc.date.available2022-11-04T01:22:49Z-
dc.date.issued2022-
dc.identifier.citationHu, X., Pang, B. & Low, K. H. (2022). Wind patterns analysis on temporal scales for safe UAV operations using statistical approaches. 2022 IEEE/AIAA 41st Digital Avionics Systems Conference (DASC). https://dx.doi.org/10.1109/DASC55683.2022.9925790en_US
dc.identifier.isbn978-1-6654-8607-1-
dc.identifier.issn2155-7209-
dc.identifier.urihttps://hdl.handle.net/10356/162347-
dc.description.abstractThe wind is one of the major factors that may cause unmanned aerial vehicles (UAVs) to crash and pose fatality risk to the population and property damage risk to infrastructures. This paper investigates wind patterns on temporal scales to identify high-risk periods in terms of wind conditions for safe UAV operations in urban airspace. The research starts with the historical wind speed data analysis using statistical approaches. As the wind speed data does not follow normal distribution after checking, a nonparametric approach of the Kruskal-Wallis test is applied for hypothesis testing to see if there is a significant difference in the median wind speed in different years. Regression analyses are also performed for monthly wind speed data to check any significant trends that could facilitate the predictions of average wind speed in the long term. This study will contribute to safe air traffic management for UAV operations in low-altitude urban airspace by mitigating adverse wind effects.en_US
dc.description.sponsorshipCivil Aviation Authority of Singapore (CAAS)en_US
dc.description.sponsorshipNanyang Technological Universityen_US
dc.description.sponsorshipNational Research Foundation (NRF)en_US
dc.language.isoenen_US
dc.rights© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/DASC55683.2022.9925790.en_US
dc.subjectEngineering::Mechanical engineeringen_US
dc.titleWind patterns analysis on temporal scales for safe UAV operations using statistical approachesen_US
dc.typeConference Paperen
dc.contributor.schoolSchool of Mechanical and Aerospace Engineeringen_US
dc.contributor.conference2022 IEEE/AIAA 41st Digital Avionics Systems Conference (DASC)en_US
dc.contributor.researchAir Traffic Management Research Instituteen_US
dc.identifier.doi10.1109/DASC55683.2022.9925790-
dc.description.versionSubmitted/Accepted versionen_US
dc.subject.keywordsUnmanned Aerial Vehiclesen_US
dc.subject.keywordsWind Speeden_US
dc.subject.keywordsOperational Safetyen_US
dc.subject.keywordsUrban Airspaceen_US
dc.subject.keywordsNonparametric Statisticsen_US
dc.citation.conferencelocationPortsmouth, VA, USAen_US
dc.description.acknowledgementThis research is supported by the National Research Foundation, Singapore, and the Civil Aviation Authority of Singapore, under the Aviation Transformation Programme. The Research Student Scholarship (RSS) provided by the Nanyang Technological University (NTU) to the second author is also acknowledged.en_US
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