GPS-Free Accurate Energy-Efficient Outdoor Localization



Dejavu Basic Idea CellSense

Location-based services (LBS) have become an integral part of our daily life with applications including car navigation, location-based social networks, and context-aware predication and advertisement. Different LBS require different localization accuracies; Generally, GPS is considered the de facto standard for ubiquitous and accurate outdoor navigation. However, GPS is an energy-hungry technology that can drain the scarce battery resource of mobile devices quickly. In addition, its accuracy is limited in areas with obscured access to the satellites, e.g. in tunnels and many urban areas.
To address the GPS deficiencies, a number of outdoor localization systems have been proposed over the years. However, this saving in energy usually comes at a reduced localization accuracy.

In this project, we aim to develop ubiquitous GPS alternative systems that is capable of achieving both energy efficiency and high localization accuracy. In particular, the project targets the development of accurate outdoor localization systems for mobile devices by utilizing the different sensors available on the phone.

Sponsors

This project is partially funded by grants from Google, the KACST National Science and Technology and the KACST GIS Technology Innovation Center at Umm Al-Qura University.

People

Collaborators

  • Dr. Anas Basalamah (Umm Al-Qura University)
  • Shuja Jamil Sheikh (Umm Al-Qura University)

Talks

CellSense:

Dejavu:

Press and Media Coverage

Dejavu:

List of Publications

Journal Publications

  • Automatic Rich Map Semantics Identification through Smartphone-based Crowd-sensing
    Heba Aly, Anas Basalamah and Moustafa Youssef
    IEEE Transactions on Mobile Computing, 2016.
    Download: PDF
  • Accurate Real-time Map Matching for Challenging Environments
    Reham Mohamed, Heba Aly and Moustafa Youssef
    IEEE Transactions on Intelligent Transportation Systems, 2016.
    Download: PDF
  • Robust and Ubiquitous Smartphone-based Lane Detection
    Heba Aly, Anas Basalamah and Moustafa Youssef
    Pervasive and Mobile Computing (PMC), 2015. (Invited)
    Download: PDF
  • CellSense: An Accurate Energy-Efficient GSM Positioning System
    Mohamed Ibrahim and Moustafa Youssef
    IEEE TVT (IEEE Transactions on Vehicular Technology) 2012.
    Download: PDF

Conference Publications

  • semMatch: Road Semantics-based Accurate Map Matching for Challenging Positioning Data
    Heba Aly and Moustafa Youssef
    ACM SIGSPATIAL 2015. Full Paper Acceptance Rate 18%.
    Download: PDF
  • LaneQuest: An Accurate and Energy-Efficient Lane Detection System
    Heba Aly, Anas Basalamah and Moustafa Youssef
    IEEE PerCom 2015. Full Paper Acceptance Rate 7.7%.
    Download: PDF
  • Dejavu: An Accurate Energy-Efficient Outdoor Localization System
    Heba Aly and Moustafa Youssef
    ACM SIGSPATIAL 2013. Acceptance Rate 17%. The Best Paper Award in The ACM SIGSPATIAL’13
    Download: PDF
  • Map++: A Crowd-sensing System for Automatic Map Semantics Identification
    Heba Aly, Anas Basalamah and Moustafa Youssef
    IEEE SECON 2014. Acceptance Rate 19.8%.
    Download: PDF
  • Accurate and Efficient Map Matching for Challenging Environments
    Reham Mohamed, Heba Aly and Moustafa Youssef
    ACM SIGSPATIAL GIS 2014.
    PDF
  • A Hidden Markov Model for Localization Using Low-End GSM Cell Phones
    Mohamed Ibrahim and Moustafa Youssef
    IEEE ICC 2011.
    Download: PDF
  • CellSense: A Probabilistic RSSI-based GSM Positioning System
    Mohamed Ibrahim and Moustafa Youssef
    IEEE Globecom 2010.
    Download: PDF

Demos & Posters

  • Smartphone-based Crowd-sensing for Digital Maps Semantics Enrichment
    Heba Aly
    N2Women Workshop at ACM MobiCom 2016. The Best Poster Award
  • Demonstrating Map++: A Crowd-sensing System for Automatic Map Semantics Identification
    Shuja Jamil Sheikh, Anas Basalamah, Heba Aly and Moustafa Youssef
    IEEE SECON 2014.
    Download: PDF