The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
Accurate indoor localization with zero start-up cost
Abstract
Recent years have seen the advent of new RF-localization systems that demonstrate tens of centimeters of accuracy. However, such systems require either deployment of new infrastructure, or extensive fingerprinting of the environment through training or crowdsourcing, impeding their wide-scale adoption.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Bundle Adjustment — A Modern Synthesis
Triggs, B., McLauchlan, P. F., Hartley, R. I., & Fitzgibbon, A. W. (2000) · Lecture Notes in Computer Science · doi:10.1007/3-540-44480-7_21 · Cited by 3,988
Tool release: gathering 802.11n traces with channel state information
Halperin, D., Hu, W., Sheth, A., & Wetherall, D. (2011) · ACM SIGCOMM Computer Communication Review · doi:10.1145/1925861.1925870 · Cited by 1,761
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
Zee: zero-effort crowdsourcing for indoor localization
Rai, A., Chintalapudi, K. K., Padmanabhan, V. N., & Sen, R. (2012) · Proceedings of the 18th annual international conference on Mobile computing and networking · doi:10.1145/2348543.2348580 · Cited by 1,039
Extension of phase correlation to subpixel registration
Foroosh, H., Zerubia, J. B., & Berthod, M. (2002) · IEEE Transactions on Image Processing · doi:10.1109/83.988953 · Cited by 978
Indoor 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
No need to war-drive: unsupervised indoor localization
Wang, H., Sen, S., Elgohary, A., Farid, M., Youssef, M., & Choudhury, R. R. (2012) · Proceedings of the 10th international conference on Mobile systems, applications, and services · doi:10.1145/2307636.2307655 · Cited by 828
ArrayTrack: a fine-grained indoor location system
Xiong, J., & Jamieson, K. (2013) · Cited by 821
Locating in fingerprint space: wireless indoor localization with little human intervention
Yang, Z., Wu, C., & Liu, Y. (2012) · Proceedings of the 18th annual international conference on Mobile computing and networking · doi:10.1145/2348543.2348578 · Cited by 739
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
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
ToneTrack: Leveraging Frequency-Agile Radios for Time-Based Indoor Wireless Localization
Xiong, J., Sundaresan, K., & Jamieson, K. (2015) · Proceedings of the 21st Annual International Conference on Mobile Computing and Networking · doi:10.1145/2789168.2790125 · Cited by 331
Improving Indoor Localization Using Bluetooth Low Energy Beacons
Kriz, P., Maly, F., & Kozel, T. (2016) · Mobile Information Systems · doi:10.1155/2016/2083094 · Cited by 256
Metadata
- Authors
- Kumar, S., Gil, S., Katabi, D., & Rus, D.
- Venue
- Proceedings of the 20th annual international conference on Mobile computing and networking
- Publisher
- ACM
- Published
- 2014-09-07
- Pages
- 483-494
- ISSN
- 1543-5679 (ISSN-L)
- OpenAlex
- W2013503669
- Cited by
- 386
- References
- 29
- FWCI
- 41.04
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Accurate indoor localization with zero start-up cost. https://app.cochat.ai/papers/10.1145/2639108.2639142
- The paper
- Kumar, S., Gil, S., Katabi, D., & Rus, D. (2014). Accurate indoor localization with zero start-up cost. Proceedings of the 20th annual international conference on Mobile computing and networking. https://doi.org/10.1145/2639108.2639142
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
