Multi-person localization via RF body reflections
We have recently witnessed the emergence of RF-based indoor localization systems that can track user motion without requiring the user to hold or wear any device. These systems can localize a user and track his gestures by relying solely on the reflections of wireless signals off his body, and work...
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| Format: | Article |
| Language: | en_US |
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USENIX Association
2018
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| Online Access: | http://hdl.handle.net/1721.1/116257 https://orcid.org/0000-0003-2593-2069 https://orcid.org/0000-0001-8835-7810 https://orcid.org/0000-0003-4854-4157 |
| _version_ | 1826211174150045696 |
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| author | Adib, Fadel Kabelac, Zachary E. Katabi, Dina |
| author2 | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
| author_facet | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Adib, Fadel Kabelac, Zachary E. Katabi, Dina |
| author_sort | Adib, Fadel |
| collection | MIT |
| description | We have recently witnessed the emergence of RF-based indoor localization systems that can track user motion without requiring the user to hold or wear any device. These systems can localize a user and track his gestures by relying solely on the reflections of wireless signals off his body, and work even if the user is behind a wall or obstruction. However, in order for these systems to become practical, they need to address two main challenges: 1) They need to be able to operate in the presence of more than one user in the environment, and 2) they must be able to localize a user without requiring him to move or change his position.
This paper presents WiTrack2.0, a multi-person localization system that operates in multipath-rich indoor environments and pinpoints users’ locations based purely on the reflections of wireless signals off their bodies. WiTrack2.0 can even localize static users, and does so by sensing the minute movements due to their breathing.We built a prototype of WiTrack2.0 and evaluated it in a standard office building. Our results show that it can localize up to five people simultaneously with a median accuracy of 11.7 cm in each of the x=y dimensions. Furthermore, WiTrack2.0 provides coarse tracking of body parts, identifying the direction of a pointing hand with a median error of 12.5º, for multiple users in the environment. |
| first_indexed | 2024-09-23T15:02:04Z |
| format | Article |
| id | mit-1721.1/116257 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T15:02:04Z |
| publishDate | 2018 |
| publisher | USENIX Association |
| record_format | dspace |
| spelling | mit-1721.1/1162572022-10-02T00:08:36Z Multi-person localization via RF body reflections Adib, Fadel Kabelac, Zachary E. Katabi, Dina Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Program in Media Arts and Sciences (Massachusetts Institute of Technology) Adib, Fadel Kabelac, Zachary E. Katabi, Dina We have recently witnessed the emergence of RF-based indoor localization systems that can track user motion without requiring the user to hold or wear any device. These systems can localize a user and track his gestures by relying solely on the reflections of wireless signals off his body, and work even if the user is behind a wall or obstruction. However, in order for these systems to become practical, they need to address two main challenges: 1) They need to be able to operate in the presence of more than one user in the environment, and 2) they must be able to localize a user without requiring him to move or change his position. This paper presents WiTrack2.0, a multi-person localization system that operates in multipath-rich indoor environments and pinpoints users’ locations based purely on the reflections of wireless signals off their bodies. WiTrack2.0 can even localize static users, and does so by sensing the minute movements due to their breathing.We built a prototype of WiTrack2.0 and evaluated it in a standard office building. Our results show that it can localize up to five people simultaneously with a median accuracy of 11.7 cm in each of the x=y dimensions. Furthermore, WiTrack2.0 provides coarse tracking of body parts, identifying the direction of a pointing hand with a median error of 12.5º, for multiple users in the environment. 2018-06-12T15:23:47Z 2018-06-12T15:23:47Z 2015-05 Article http://purl.org/eprint/type/ConferencePaper http://hdl.handle.net/1721.1/116257 Adib, Fadel, Zachary Kabelac, and Dina Katabi. "Multi-Person Localization via RF Body Reflections." 12th USENIX Symposium on Networked Systems Design and Implementation." 4-6 May, 2015, Oakland, California, USENIX, 2015. https://orcid.org/0000-0003-2593-2069 https://orcid.org/0000-0001-8835-7810 https://orcid.org/0000-0003-4854-4157 en_US https://www.usenix.org/node/188986 12th USENIX Symposium on Networked Systems Design and Implementation Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf USENIX Association MIT Web Domain |
| spellingShingle | Adib, Fadel Kabelac, Zachary E. Katabi, Dina Multi-person localization via RF body reflections |
| title | Multi-person localization via RF body reflections |
| title_full | Multi-person localization via RF body reflections |
| title_fullStr | Multi-person localization via RF body reflections |
| title_full_unstemmed | Multi-person localization via RF body reflections |
| title_short | Multi-person localization via RF body reflections |
| title_sort | multi person localization via rf body reflections |
| url | http://hdl.handle.net/1721.1/116257 https://orcid.org/0000-0003-2593-2069 https://orcid.org/0000-0001-8835-7810 https://orcid.org/0000-0003-4854-4157 |
| work_keys_str_mv | AT adibfadel multipersonlocalizationviarfbodyreflections AT kabelaczacharye multipersonlocalizationviarfbodyreflections AT katabidina multipersonlocalizationviarfbodyreflections |