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AuthorHussain A.M.
AuthorAzmy S.B.
AuthorAbuzrara A.
AuthorAl-Hajjaji K.
AuthorHassan A.
AuthorKhamdan H.
AuthorEzzin M.
AuthorHassani A.
AuthorZorba N.
Available date2020-03-03T06:19:38Z
Publication Date2018
Publication Name2018 14th International Wireless Communications and Mobile Computing Conference, IWCMC 2018
URIhttp://dx.doi.org/10.1109/IWCMC.2018.8450414
URIhttp://hdl.handle.net/10576/13226
AbstractAir pollution is a major issue contributing to global warming that threaten the quality of life on Earth. Numerous research disciplines are combining their efforts to combat air pollution by developing new methods to monitor and control pollution. For this to happen, researchers need to have instant access to new data. In this paper, we have developed a Semi-Autonomous Unmanned Aerial Vehicle (UAV) loaded with sensors to measure different quantities indicating air pollution, in particular: temperature, humidity, dust, carbon monoxide, carbon dioxide, and ozone. The purpose of this UAV is to automatically patrol high altitudes to obtain sensor readings, and transmit raw data to a centralized server via mobile network for visualization and storage. Actual measurements and data collection is carried out in Qatar. This combination of the UAVs' mobility, remote sensing, and networking facilities allows concerned parties such as researchers, smart city administrators and crowd managers, to view and visualize relevant data with significant ease via a web interface, or an android app.
SponsorThis work was made possible by NPRP grant NPRP 9-185-2-096 from the Qatar National Research Fund (a member of The Qatar Foundation). The statements made herein are solely the responsibility of the authors.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
dc.source Scopus
SubjectCrowd management
SubjectCrowd sensing
SubjectData Acquisition
SubjectData Classification
SubjectData Visualization
SubjectPollution
SubjectRemote Sensing
SubjectSmart infrastructure
SubjectUnmanned Aerial Vehicle
TitleUAV-based Semi-Autonomous Data Acquisition and Classification
TypeConference Paper
Pagination1273 - 1277


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