EV-Loc: integrating electronic and visual signals for accurate localization

  • Authors:

  • Boying Zhang;Jin Teng;Junda Zhu;Xinfeng Li;Dong Xuan;Yuan F. Zheng

  • Affiliations:

  • The Ohio State University, Columbus, OH, USA;The Ohio State University, Columbus, OH, USA;The Ohio State University, Columbus, OH, USA;The Ohio State University, Columbus, OH, USA;The Ohio State University, Columbus, OH, USA;The Ohio State University, Columbus, OH, USA

  • Venue:
  • Proceedings of the thirteenth ACM international symposium on Mobile Ad Hoc Networking and Computing
  • Year:
  • 2012

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Abstract

Nowadays, an increasing number of objects can be represented by their wireless electronic identifiers. For example, people can be recognized by their phone numbers or their phones' WiFi' MAC addresses and products can be identified by their RFID numbers. Localizing objects with electronic identifiers is increasingly important as our lives become increasingly "digitalized". However, traditional wireless localization techniques cannot meet the fast growing needs of accurate and cost efficient localization. Some of these techniques require expensive hardware to achieve high accuracy, which is impractical for massive deployment. Others, such as WiFi RSSI based localization, are inaccurate and not robust to environmental noise. In this paper, we propose a new localization technique called EV-Loc. In EV-Loc, we use visual signals to help improve the accuracy of wireless localization. Our technique fully leverages visual signals' high accuracy and electronic signals' pervasiveness. To effectively couple these two signals, we design an E-V match engine to find the correspondence between an object's electronic identifier and its visual appearance. We implement our technique on mobile devices and evaluate it in real-world scenarios. The localization error is less than 1 m. We also evaluate our approach using large scale simulations. The results show that our approach is accurate and robust.