• DocumentCode
    601186
  • Title

    Panoptes: Crowd-sourced Cars with a Cause

  • Author

    Drolia, Utsav ; Mankodiya, Kunal ; Mickulicz, N. ; Narasimhan, Priya

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA
  • fYear
    2012
  • fDate
    12-16 Dec. 2012
  • Firstpage
    148
  • Lastpage
    153
  • Abstract
    There is no consolidated, integral, quantifiable, granular, updated source of information for the roads we traverse and the environment we live in everyday. This leads to ambiguity about road conditions, which is tolerable during normal conditions but extremely problematic in adverse conditions such as snow blockages, water-logging due to storms, degraded roads and potholes. Without such knowledge, city authorities cannot take effective action against such problems. Also, one only has knowledge about ones immediate surroundings in a car, and not what to expect further down the road. Our approach is to deploy a number of embedded modules capable of sensing, computing and reporting, each of which can simply be plugged into any vehicle. Hence this enables each vehicle´s connectivity to the cloud and larger coverage as compared to static sensors. The data reported by each module itself might be prone to errors. Therefore, the cloud crowd sources the data from these modules and merges it to increase confidence in the information. Our work, Panoptes, demonstrates these aspects through crowdsourced pothole detection for city roads.
  • Keywords
    Global Positioning System; automobiles; cloud computing; Panoptes; adverse conditions; city authorities; city road conditions; cloud crowd-sourced cars; crowdsourced pothole detection; degraded roads; embedded modules; normal conditions; snow blockages; storms; vehicle connectivity; water-logging;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Connected Vehicles and Expo (ICCVE), 2012 International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4673-4705-1
  • Type

    conf

  • DOI
    10.1109/ICCVE.2012.35
  • Filename
    6519559