• English
    • العربية
  • العربية
  • Login
  • QU
  • QU Library
  •  Home
  • Communities & Collections
  • Help
    • Item Submission
    • Publisher policies
    • User guides
    • FAQs
  • About QSpace
    • Vision & Mission
View Item 
  •   Qatar University Digital Hub
  • Qatar University Institutional Repository
  • Academic
  • Faculty Contributions
  • College of Engineering
  • Electrical Engineering
  • View Item
  • Qatar University Digital Hub
  • Qatar University Institutional Repository
  • Academic
  • Faculty Contributions
  • College of Engineering
  • Electrical Engineering
  • View Item
  •      
  •  
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    UAV-based Semi-Autonomous Data Acquisition and Classification

    Thumbnail
    Date
    2018
    Author
    Hussain A.M.
    Azmy S.B.
    Abuzrara A.
    Al-Hajjaji K.
    Hassan A.
    Khamdan H.
    Ezzin M.
    Hassani A.
    Zorba N.
    ...show more authors ...show less authors
    Metadata
    Show full item record
    Abstract
    Air 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.
    DOI/handle
    http://dx.doi.org/10.1109/IWCMC.2018.8450414
    http://hdl.handle.net/10576/13226
    Collections
    • Electrical Engineering [‎2840‎ items ]

    entitlement


    Qatar University Digital Hub is a digital collection operated and maintained by the Qatar University Library and supported by the ITS department

    Contact Us | Send Feedback
    Contact Us | Send Feedback | QU

     

     

    Home

    Submit your QU affiliated work

    Browse

    All of Digital Hub
      Communities & Collections Publication Date Author Title Subject Type Language Publisher
    This Collection
      Publication Date Author Title Subject Type Language Publisher

    My Account

    Login

    Statistics

    View Usage Statistics

    About QSpace

    Vision & Mission

    Help

    Item Submission Publisher policiesUser guides FAQs

    Qatar University Digital Hub is a digital collection operated and maintained by the Qatar University Library and supported by the ITS department

    Contact Us | Send Feedback
    Contact Us | Send Feedback | QU

     

     

    Video