Room-level proximity detection based on RSS of dual-band Wi-Fi signals

Yugo Agata, Jihoon Hong, Tomoaki Ohtsuki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Proximity information of users can be used in various applications (e.g., user interactions in social networks). Applying conventional works to room-level proximity detection is difficult because there is a limitation of the proximity range within 5 m. In this paper, we propose a room-level proximity detection method based on the similarity of received information of Wi-Fi signals between users. We use Wi-Fi signals in both 2.4 GHz band and 5 GHz band, and use relevant features that indicate the similarity of received signal strength (RSS) of beacon frames and access points (APs) sets from which users receives them. Through extensive experiments, in which we recognize whether or not users exist in the same room with a size approximately from 10 to 15 m square, we demonstrate that our proposed method can realize room-level proximity detection with high robustness to relative location of users and APs.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Communications, ICC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479966646
DOIs
Publication statusPublished - 2016 Jul 12
Event2016 IEEE International Conference on Communications, ICC 2016 - Kuala Lumpur, Malaysia
Duration: 2016 May 222016 May 27

Other

Other2016 IEEE International Conference on Communications, ICC 2016
CountryMalaysia
CityKuala Lumpur
Period16/5/2216/5/27

Fingerprint

Wi-Fi
Experiments

ASJC Scopus subject areas

  • Computer Networks and Communications

Cite this

Agata, Y., Hong, J., & Ohtsuki, T. (2016). Room-level proximity detection based on RSS of dual-band Wi-Fi signals. In 2016 IEEE International Conference on Communications, ICC 2016 [7510880] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICC.2016.7510880

Room-level proximity detection based on RSS of dual-band Wi-Fi signals. / Agata, Yugo; Hong, Jihoon; Ohtsuki, Tomoaki.

2016 IEEE International Conference on Communications, ICC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. 7510880.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Agata, Y, Hong, J & Ohtsuki, T 2016, Room-level proximity detection based on RSS of dual-band Wi-Fi signals. in 2016 IEEE International Conference on Communications, ICC 2016., 7510880, Institute of Electrical and Electronics Engineers Inc., 2016 IEEE International Conference on Communications, ICC 2016, Kuala Lumpur, Malaysia, 16/5/22. https://doi.org/10.1109/ICC.2016.7510880
Agata Y, Hong J, Ohtsuki T. Room-level proximity detection based on RSS of dual-band Wi-Fi signals. In 2016 IEEE International Conference on Communications, ICC 2016. Institute of Electrical and Electronics Engineers Inc. 2016. 7510880 https://doi.org/10.1109/ICC.2016.7510880
Agata, Yugo ; Hong, Jihoon ; Ohtsuki, Tomoaki. / Room-level proximity detection based on RSS of dual-band Wi-Fi signals. 2016 IEEE International Conference on Communications, ICC 2016. Institute of Electrical and Electronics Engineers Inc., 2016.
@inproceedings{958f4b0d67274180b2d34b014549e0b4,
title = "Room-level proximity detection based on RSS of dual-band Wi-Fi signals",
abstract = "Proximity information of users can be used in various applications (e.g., user interactions in social networks). Applying conventional works to room-level proximity detection is difficult because there is a limitation of the proximity range within 5 m. In this paper, we propose a room-level proximity detection method based on the similarity of received information of Wi-Fi signals between users. We use Wi-Fi signals in both 2.4 GHz band and 5 GHz band, and use relevant features that indicate the similarity of received signal strength (RSS) of beacon frames and access points (APs) sets from which users receives them. Through extensive experiments, in which we recognize whether or not users exist in the same room with a size approximately from 10 to 15 m square, we demonstrate that our proposed method can realize room-level proximity detection with high robustness to relative location of users and APs.",
author = "Yugo Agata and Jihoon Hong and Tomoaki Ohtsuki",
year = "2016",
month = "7",
day = "12",
doi = "10.1109/ICC.2016.7510880",
language = "English",
booktitle = "2016 IEEE International Conference on Communications, ICC 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Room-level proximity detection based on RSS of dual-band Wi-Fi signals

AU - Agata, Yugo

AU - Hong, Jihoon

AU - Ohtsuki, Tomoaki

PY - 2016/7/12

Y1 - 2016/7/12

N2 - Proximity information of users can be used in various applications (e.g., user interactions in social networks). Applying conventional works to room-level proximity detection is difficult because there is a limitation of the proximity range within 5 m. In this paper, we propose a room-level proximity detection method based on the similarity of received information of Wi-Fi signals between users. We use Wi-Fi signals in both 2.4 GHz band and 5 GHz band, and use relevant features that indicate the similarity of received signal strength (RSS) of beacon frames and access points (APs) sets from which users receives them. Through extensive experiments, in which we recognize whether or not users exist in the same room with a size approximately from 10 to 15 m square, we demonstrate that our proposed method can realize room-level proximity detection with high robustness to relative location of users and APs.

AB - Proximity information of users can be used in various applications (e.g., user interactions in social networks). Applying conventional works to room-level proximity detection is difficult because there is a limitation of the proximity range within 5 m. In this paper, we propose a room-level proximity detection method based on the similarity of received information of Wi-Fi signals between users. We use Wi-Fi signals in both 2.4 GHz band and 5 GHz band, and use relevant features that indicate the similarity of received signal strength (RSS) of beacon frames and access points (APs) sets from which users receives them. Through extensive experiments, in which we recognize whether or not users exist in the same room with a size approximately from 10 to 15 m square, we demonstrate that our proposed method can realize room-level proximity detection with high robustness to relative location of users and APs.

UR - http://www.scopus.com/inward/record.url?scp=84981297741&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84981297741&partnerID=8YFLogxK

U2 - 10.1109/ICC.2016.7510880

DO - 10.1109/ICC.2016.7510880

M3 - Conference contribution

AN - SCOPUS:84981297741

BT - 2016 IEEE International Conference on Communications, ICC 2016

PB - Institute of Electrical and Electronics Engineers Inc.

ER -