Indoor localization without infrastructure using the acoustic background spectrum

  • Authors:

  • Stephen P. Tarzia;Peter A. Dinda;Robert P. Dick;Gokhan Memik

  • Affiliations:

  • Northwestern University, Evanston, IL, USA;Northwestern University, Evanston, IL, USA;University of Michigan, Ann Arbor, MI, USA;Northwestern University, Evanston, IL, USA

  • Venue:
  • MobiSys '11 Proceedings of the 9th international conference on Mobile systems, applications, and services
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

We introduce a new technique for determining a mobile phone's indoor location even when Wi-Fi infrastructure is unavailable or sparse. Our technique is based on a new ambient sound fingerprint called the Acoustic Background Spectrum (ABS). An ABS serves well as a room fingerprint because it is compact, easily computed, robust to transient sounds, and surprisingly distinctive. As with other fingerprint-based localization techniques, location is determined by measuring the current fingerprint and then choosing the "closest" fingerprint from a database. An experiment involving 33 rooms yielded 69% correct fingerprint matches meaning that, in the majority of observations, the fingerprint was closer to a previous visit's fingerprint than to any fingerprints from the other 32 rooms. An implementation of ABS-localization called Batphone is publicly available for Apple iPhones. We used Batphone to show the benefit of using ABS-localization together with a commercial Wi-Fi-based localization method. In this second experiment, adding ABS improved room-level localization accuracy from 30% (Wi-Fi only) to 69% (Wi-Fi and ABS). While Wi-Fi-based localization has difficulty distinguishing nearby rooms, Batphone performs just as well with nearby rooms; it can distinguish pairs of adjacent rooms with 92% accuracy.