Article

Place lab: device positioning using radio beacons in the wild

Authors:

Anthony LaMarca,

Yatin Chawathe,

Sunny Consolvo,

Jeffrey Hightower,

Pauline Powledge,

Gaetano Borriello,

Bill SchilitAuthors Info & Claims

PERVASIVE'05: Proceedings of the Third international conference on Pervasive Computing

Pages 116 - 133

https://doi.org/10.1007/11428572_8

Published: 08 May 2005 Publication History

Abstract

Location awareness is an important capability for mobile computing. Yet inexpensive, pervasive positioning—a requirement for wide-scale adoption of location-aware computing—has been elusive. We demonstrate a radio beacon-based approach to location, called Place Lab, that can overcome the lack of ubiquity and high-cost found in existing location sensing approaches. Using Place Lab, commodity laptops, PDAs and cell phones estimate their position by listening for the cell IDs of fixed radio beacons, such as wireless access points, and referencing the beacons' positions in a cached database. We present experimental results showing that 802.11 and GSM beacons are sufficiently pervasive in the greater Seattle area to achieve 20-30 meter median accuracy with nearly 100% coverage measured by availability in people's daily lives.

References

[1]

Sequential Monte Carlo in Practice, DOUCET A. & DE FREITAS, N. (Ed.) (New York, Springer-Verlag).(2001)

[2]

JSR 179 Location API for J2ME, LOYTANA, K. (Ed.),(2003) http://www.jcp.org/en/jsr/ detail?id=179

[3]

BAHL, P. & PADMANABHAN, V. RADAR: An In-Building RF-Based User Location and Tracking System Proceedings of IEEE INFOCOM, pp. 775-784 (Tel-Aviv, Israel).(2000)

[4]

GRISWOLD, W. G., SHANAHAN, P., BROWN, S. W., BOYER, R., RATTO, M., SHAPIRO, R. B. & TRUONG, T. M. ActiveCampus - Experiments in Community-Oriented Ubiquitous Computing, To Appear: IEEE Computer.

[5]

HIGHTOWER, J. & BORRIELLO, G. Particle Filters for Location Estimation in Ubiquitous Computing: A Case Study Proceedings of the Sixth International Conference on Ubiquitous Computing (Ubicomp) (Springer-Verlag).(2004)

[6]

KRUMM, J., CERMAK, G. & HORVITZ, E. RightSPOT: A Novel Sense of Location for a Smart Personal Object, Paper presented at the UbiComp 2003.(2003)

[7]

LAASONEN, K., RAENTO, M. & TOIVONEN, H. Adaptive On-Device Location Recognition, Paper presented at the Pervasive Computing: Second International Conference.(2004)

[8]

LI, Y., JASON, I. H. & LANDAY, J. A. Topiary: A Tool for Prototyping Location-Enhanced Applications, Paper presented at the Symposium on User Interface Software and Technology - UIST'2004.(2004)

[9]

PATTERSON, D. J., LIAO, L., FOX, D. & KAUTZ, H. A. Inferring High-Level Behavior from Low-Level Sensors Proceedings of the Fifth International Conference on Ubiquitous Computing (Ubicomp), pp. 73-89 (Springer-Verlag).(2003)

[10]

PRIYANTHA, N. B., CHAKRABORTY, A. & BALAKRISHNAN, H. The Cricket Location-Support System Proceedings of MOBICOM 2000, pp. 32-43 (Boston, MA, ACM Press).(2000)

[11]

SCHILIT, B., LAMARCA, A., BORRIELLO, G., GRISWOLD, W., MCDONALD, D., LAZOWSKA, E., BALACHANDRAN, A., HONG, J. & IVERSON, V. Challenge: Ubiquitous Location-Aware Computing and the Place Lab Initiative Proceedings of the First ACM International Workshop on Wireless Mobile Applications and Services on WLAN (WMASH).(2003)

[12]

WANT, R., HOPPER, A., FALCAO, V. & GIBBONS, J. The Active Badge Location System, ACM Transactions on Information Systems, 10, 91-102. (1992)

[13]

WANT, R., SCHILIT, B., ADAMS, N., GOLD, R., PETERSEN, K., GOLDBERG, D., ELLIS, J. & WEISER, M. The ParcTab Ubiquitous Computing Experiment, in: Imielinski, T. (Ed.) Mobile Computing, pp. 45-101 (Kluwer Publishing).(1997)

[14]

WANT, R., PERING, T., DANNEELS, G., KUMAR, M., SUNDAR, M. & LIGHT, J. The Personal Server: Changing the Way We Think about Ubiquitous Computing, Paper presented at the Ubicomp 2002.(2003)

[15]

WARD, A., JONES, A. & HOPPER, A. A New Location Technique for the Active Office, IEEE Personal Communications, 4, 42-47. (1997)

Cited By

Ai HTao JAi SXu TLi NTang KZhang SYang YLi S(2022)Error model and simulation for multisource fusion indoor positioningInternational Journal of Intelligent Systems10.1002/int.2277137:3(2219-2241)Online publication date: 25-Jan-2022
https://dl.acm.org/doi/10.1002/int.22771
Fujiwara MNakatani TTian YKorpela JMaekawa THara T(2020)Smartphone-assisted Automatic Indoor Localization of BLE-enabled Appliances Using BLE and GNSS SignalsProceedings of the 7th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation10.1145/3408308.3427981(80-89)Online publication date: 18-Nov-2020
https://dl.acm.org/doi/10.1145/3408308.3427981
Ibrahim MRostami AYu BLiu HJawahar MNguyen VGruteser MBai FHoward Rde Lara EMohomed INieh JBelding E(2020)Wi-GoProceedings of the 18th International Conference on Mobile Systems, Applications, and Services10.1145/3386901.3388944(312-324)Online publication date: 15-Jun-2020
https://dl.acm.org/doi/10.1145/3386901.3388944
Show More Cited By

Place lab: device positioning using radio beacons in the wild
1. Networks
  1. Network services
  2. Network types

Recommendations

Experiences with place lab: an open source toolkit for location-aware computing
ICSE '06: Proceedings of the 28th international conference on Software engineering

Location-based computing (LBC) is becoming increasing important in both industry and academia. A key challenge is the pervasive deployment of LBC technologies; to be effective they must run on a wide variety of client platforms, including laptops, PDAs, ...
Indoor Place Prediction on Smart Phones
SenSys '22: Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems

High-accuracy and low-latency indoor place prediction for mobile users is crucial to enable applications for assisted living, emergency services, smart homes, and augmented reality. Previous studies on indoor place prediction use complex infrastructure ...
Evaluation of Long-term LiDAR Place Recognition
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
We compare a state-of-the-art deep image retrieval and a deep place recognition method for place recognition using LiDAR data. Place recognition aims to detect previously visited locations and thus provides an important tool for navigation, mapping, and ...

Comments

Information & Contributors

Information

Published In

cover image Guide Proceedings

PERVASIVE'05: Proceedings of the Third international conference on Pervasive Computing

May 2005

346 pages

ISBN:3540260080

Editors:
Hans-W. Gellersen
Computing Department, Lancaster University, England
,
Roy Want
Computing Department, Intel Research, 2200 Mission College Blvd, Santa Clara, England
,
Albrecht Schmidt
Pervasive Computing and User Interface Engineering, University of Duisburg-Essen, 2200 Mission College Blvd, Santa Clara, Germany

Sponsors

INTEL: Intel Corporation
Microsoft Research: Microsoft Research
NTT DoCoMo

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 08 May 2005

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

237
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 24 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Ai HTao JAi SXu TLi NTang KZhang SYang YLi S(2022)Error model and simulation for multisource fusion indoor positioningInternational Journal of Intelligent Systems10.1002/int.2277137:3(2219-2241)Online publication date: 25-Jan-2022
https://dl.acm.org/doi/10.1002/int.22771
Fujiwara MNakatani TTian YKorpela JMaekawa THara T(2020)Smartphone-assisted Automatic Indoor Localization of BLE-enabled Appliances Using BLE and GNSS SignalsProceedings of the 7th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation10.1145/3408308.3427981(80-89)Online publication date: 18-Nov-2020
https://dl.acm.org/doi/10.1145/3408308.3427981
Ibrahim MRostami AYu BLiu HJawahar MNguyen VGruteser MBai FHoward Rde Lara EMohomed INieh JBelding E(2020)Wi-GoProceedings of the 18th International Conference on Mobile Systems, Applications, and Services10.1145/3386901.3388944(312-324)Online publication date: 15-Jun-2020
https://dl.acm.org/doi/10.1145/3386901.3388944
Ranasinghe CSchiestel NKray C(2019)Visualising Location Uncertainty to Support Navigation under Degraded GPS SignalsProceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services10.1145/3338286.3340128(1-11)Online publication date: 1-Oct-2019
https://dl.acm.org/doi/10.1145/3338286.3340128
Eshun SPalmieri PPalumbo FBecchi MSchulz MSato K(2019)A privacy-preserving protocol for indoor wi-fi localizationProceedings of the 16th ACM International Conference on Computing Frontiers10.1145/3310273.3323400(380-385)Online publication date: 30-Apr-2019
https://dl.acm.org/doi/10.1145/3310273.3323400
Ranasinghe CHeitmann SHamzin APfeiffer MKray CBuchanan GStevenson D(2018)Pedestrian navigation and GPS deteriorationsProceedings of the 30th Australian Conference on Computer-Human Interaction10.1145/3292147.3292154(266-277)Online publication date: 4-Dec-2018
https://dl.acm.org/doi/10.1145/3292147.3292154
Jaisinghani DBalan RNaik VMisra ALee YSchulzrinne HLi P(2018)Experiences & Challenges with Server-Side WiFi Indoor Localization Using Existing InfrastructureProceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services10.1145/3286978.3286989(226-235)Online publication date: 5-Nov-2018
https://dl.acm.org/doi/10.1145/3286978.3286989
Shokry ATorki MYoussef MBanaei-Kashani FHoel EGüting RTamassia RXiong L(2018)DeepLocProceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems10.1145/3274895.3274909(339-348)Online publication date: 6-Nov-2018
https://dl.acm.org/doi/10.1145/3274895.3274909
Sung CChae SKang DHan D(2018)Estimating AP Location Using Crowdsourced Wi-Fi Fingerprints with Inaccurate Location LabelsProceedings of the 2nd International Conference on Vision, Image and Signal Processing10.1145/3271553.3271582(1-6)Online publication date: 27-Aug-2018
https://dl.acm.org/doi/10.1145/3271553.3271582
Nakatani TMaekawa TShirakawa MHara T(2018)Estimating the Physical Distance between Two Locations with Wi-Fi Received Signal Strength Information Using Obstacle-aware ApproachProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/32649402:3(1-26)Online publication date: 18-Sep-2018
https://dl.acm.org/doi/10.1145/3264940
Show More Cited By

View Options

View options

Media

Figures

Other

Tables

View Table of Contents