The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Nuzzer: A Large-Scale Device-Free Passive Localization System for Wireless Environments
Abstract
The widespread usage of WLANs and mobile devices has fostered the interest in localization systems for wireless environments. The majority of research in the context of wireless-based localization systems has focused on device-based active localization, in which devices are attached to tracked entities. Recently, device-free passive localization (DfP) has been proposed where the tracked entity is neither required to carry devices nor to participate actively in the localization process. Previous studies have focused on small areas and/or controlled environments. In this paper, we present the design, implementation, and analysis of Nuzzer, a large-scale DfP localization system, which tracks entities in real environments, rich in multipath. We first present probabilistic techniques for DfP localization of a single entity and evaluate their performance both analytically and in typical office buildings. Our results show that Nuzzer gives location estimates with less than 2-meters median distance error. We then give an algorithm for estimating the number of entities in an area of interest and localizing them into coarse-grained zones to enhance the scalability of the system. This indicates the suitability of Nuzzer to a large number of application domains.
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Cites
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The Horus WLAN location determination system
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Self-citationThe Mobile Radio Propagation Channel
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WLAN location determination via clustering and probability distributions
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Self-citationRadio Tomographic Imaging with Wireless Networks
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Challenges: device-free passive localization for wireless environments
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Self-citationPractical robust localization over large-scale 802.11 wireless networks
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WiFall: Device-Free Fall Detection by Wireless Networks
Wang, Y., Wu, K., & Ni, L. M. (2017) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2016.2557792 · Cited by 836
Capturing the human figure through a wall
Adib, F., Hsu, C.-Y., Mao, H., Katabi, D., & Durand, F. (2015) · ACM Transactions on Graphics · doi:10.1145/2816795.2818072 · Cited by 443
CrossCount: A Deep Learning System for Device-Free Human Counting Using WiFi
Ibrahim, O. T., Gomaa, W., & Youssef, M. (2019) · IEEE Sensors Journal · doi:10.1109/jsen.2019.2928502 · Cited by 61
Self-citationPerformance of Machine Learning Classifiers for Indoor Person Localization With Capacitive Sensors
Bin Tariq, O., Lazarescu, M. T., Iqbal, J., & Lavagno, L. (2017) · IEEE Access · doi:10.1109/access.2017.2721538 · Cited by 36
Metadata
- Authors
- Seifeldin, M., Saeed, A., Kosba, A. E., El-Keyi, A., & Youssef, M.
- Venue
- IEEE Transactions on Mobile Computing
- Published
- 2013-07
- Volume
- 12
- Issue
- 7
- Pages
- 1321-1334
- ISSN
- 1536-1233 (ISSN-L)
- OpenAlex
- W2170589361
- Cited by
- 365
- References
- 23
- FWCI
- 24.36
- Type
- journal article
- Language
- en
- Open access
- closed
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- Seifeldin, M., Saeed, A., Kosba, A. E., El-Keyi, A., & Youssef, M. (2013). Nuzzer: A Large-Scale Device-Free Passive Localization System for Wireless Environments. IEEE Transactions on Mobile Computing. https://doi.org/10.1109/tmc.2012.106
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