The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
No need to war-drive: unsupervised indoor localization
Abstract
We propose UnLoc, an unsupervised indoor localization scheme that bypasses the need for war-driving. Our key observation is that certain locations in an indoor environment present identifiable signatures on one or more sensing dimensions. An elevator, for instance, imposes a distinct pattern on a smartphone's accelerometer; a corridor-corner may overhear a unique set of WiFi access points; a specific spot may experience an unusual magnetic fluctuation. We hypothesize that these kind of signatures naturally exist in the environment, and can be envisioned as internal landmarks of a building. Mobile devices that "sense" these landmarks can recalibrate their locations, while dead-reckoning schemes can track them between landmarks. Results from 3 different indoor settings, including a shopping mall, demonstrate median location errors of 1:69m. War-driving is not necessary, neither are floorplans the system simultaneously computes the locations of users and landmarks, in a manner that they converge reasonably quickly. We believe this is an unconventional approach to indoor localization, holding promise for real-world deployment.
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Cites
RADAR: an in-building RF-based user location and tracking system
Bahl, P., & Padmanabhan, V. N. (2002) · Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064) · doi:10.1109/infcom.2000.832252 · Cited by 8,380
Activity Recognition from User-Annotated Acceleration Data
Bao, L., & Intille, S. S. (2004) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-24646-6_1 · Cited by 3,147
Dynamic fine-grained localization in Ad-Hoc networks of sensors
Savvides, A., Han, C.-C., & Strivastava, M. B. (2001) · Proceedings of the 7th annual international conference on Mobile computing and networking · doi:10.1145/381677.381693 · Cited by 2,694
FastSLAM: a factored solution to the simultaneous localization and mapping problem
Montemerlo, M., Thrun, S., Koller, D., & Wegbreit, B. (2002) · doi:10.5555/777092.777184 · Cited by 2,012
The Horus WLAN location determination system
Youssef, M., & Agrawala, A. (2005) · Proceedings of the 3rd international conference on Mobile systems, applications, and services · doi:10.1145/1067170.1067193 · Cited by 1,653
Self-citationIndoor localization without the pain
Chintalapudi, K., Padmanabha Iyer, A., & Padmanabhan, V. N. (2010) · Proceedings of the sixteenth annual international conference on Mobile computing and networking · doi:10.1145/1859995.1860016 · Cited by 962
SurroundSense: mobile phone localization via ambience fingerprinting
Azizyan, M., Constandache, I., & Roy Choudhury, R. (2009) · Proceedings of the 15th annual international conference on Mobile computing and networking · doi:10.1145/1614320.1614350 · Cited by 723
Proceedings of the National Conference on Artificial Intelligence
Jensen, S., Boley, D. L., Gini, M. L., & Schrater, P. (2005) · Innovative Applications of Artificial Intelligence · Cited by 612
WiFi-SLAM Using G aussian Process Latent Variable Models
Ferris, B., Fox, D., & Lawrence, N. D. (2007) · Cited by 523
Pedestrian localisation for indoor environments
Woodman, O., & Harle, R. (2008) · Proceedings of the 10th international conference on Ubiquitous computing · doi:10.1145/1409635.1409651 · Cited by 486
Cited by
Wi-Fi Fingerprint-Based Indoor Positioning: Recent Advances and Comparisons
He, S., & Chan, S.-H. G. (2016) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2015.2464084 · Cited by 1,355
Recent Advances in Indoor Localization: A Survey on Theoretical Approaches and Applications
Yassin, A., Nasser, Y., Awad, M., Al-Dubai, A., Liu, R., Yuen, C., Raulefs, R., & Aboutanios, E. (2017) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2016.2632427 · Cited by 916
Torres-Sospedra, J., Montoliu, R., Martinez-Uso, A., Avariento, J. P., Arnau, T. J., Benedito-Bordonau, M., & Huerta, J. (2014) · 2014 International Conference on Indoor Positioning and Indoor Navigation (IPIN) · doi:10.1109/ipin.2014.7275492 · Cited by 615
Accurate indoor localization with zero start-up cost
Kumar, S., Gil, S., Katabi, D., & Rus, D. (2014) · Proceedings of the 20th annual international conference on Mobile computing and networking · doi:10.1145/2639108.2639142 · Cited by 386
Smartphones Based Crowdsourcing for Indoor Localization
Wu, C., Yang, Z., & Liu, Y. (2015) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2014.2320254 · Cited by 383
Metadata
- Authors
- Wang, H., Sen, S., Elgohary, A., Farid, M., Youssef, M., & Choudhury, R. R.
- Venue
- Proceedings of the 10th international conference on Mobile systems, applications, and services
- Publisher
- ACM
- Published
- 2012-06-25
- Pages
- 197-210
- OpenAlex
- W2054602086
- Cited by
- 828
- References
- 24
- FWCI
- 106.44
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Wang, H., Sen, S., Elgohary, A., Farid, M., Youssef, M., & Choudhury, R. R. (2012). No need to war-drive: unsupervised indoor localization. Proceedings of the 10th international conference on Mobile systems, applications, and services. https://doi.org/10.1145/2307636.2307655
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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