Non-obstructive room-level locating system in home environments using activity fingerprints from smartwatch

Seungwoo Lee; Yungeun Kim; Daye Ahn; Rhan Ha; Kyoungwoo Lee; Hojung Cha

doi:10.1145/2750858.2804272

Non-obstructive room-level locating system in home environments using activity fingerprints from smartwatch

Seungwoo Lee, Yungeun Kim, Daye Ahn, Rhan Ha, Kyoungwoo Lee, Hojung Cha

College of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

17 Citations (Scopus)

Abstract

Many smart home applications, such as monitoring for the elderly and home automation, require location information for individual occupants. Several techniques have been proposed for tracking occupants in a home environment. However, the current techniques do not provide a seamless in-home locating system owing to the occupants' devicefree movement and the lack of cost-effective infrastructure for home location tracking. In this paper, we propose a home occupant tracking system that uses a smartphone and an off-The-shelf smartwatch without additional infrastructure. In our system, activity fingerprints are automatically generated from the microphone and the inertial sensors of the smartwatch, and location information is periodically obtained from the smartphone. We designed a hidden Markov model using the relationship between home activities and the room's location. Extensive experiments showed that our system tracks the location of users with 87% accuracy, even when there is no manual training for activities.

Original language	English
Title of host publication	UbiComp 2015 - Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing
Publisher	Association for Computing Machinery, Inc
Pages	939-950
Number of pages	12
ISBN (Electronic)	9781450335744
DOIs	https://doi.org/10.1145/2750858.2804272
Publication status	Published - 2015 Sept 7
Event	3rd ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2015 - Osaka, Japan Duration: 2015 Sept 7 → 2015 Sept 11

Publication series

Name	UbiComp 2015 - Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing

Other

Other	3rd ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2015
Country/Territory	Japan
City	Osaka
Period	15/9/7 → 15/9/11

Bibliographical note

Publisher Copyright:
© ACM 978-1-4503-3574-4/15/09..15.00.

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Hardware and Architecture
Software

Access to Document

10.1145/2750858.2804272

Cite this

Lee, S., Kim, Y., Ahn, D., Ha, R., Lee, K., & Cha, H. (2015). Non-obstructive room-level locating system in home environments using activity fingerprints from smartwatch. In UbiComp 2015 - Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 939-950). (UbiComp 2015 - Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing). Association for Computing Machinery, Inc. https://doi.org/10.1145/2750858.2804272

Lee, Seungwoo ; Kim, Yungeun ; Ahn, Daye et al. / Non-obstructive room-level locating system in home environments using activity fingerprints from smartwatch. UbiComp 2015 - Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing. Association for Computing Machinery, Inc, 2015. pp. 939-950 (UbiComp 2015 - Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing).

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abstract = "Many smart home applications, such as monitoring for the elderly and home automation, require location information for individual occupants. Several techniques have been proposed for tracking occupants in a home environment. However, the current techniques do not provide a seamless in-home locating system owing to the occupants' devicefree movement and the lack of cost-effective infrastructure for home location tracking. In this paper, we propose a home occupant tracking system that uses a smartphone and an off-The-shelf smartwatch without additional infrastructure. In our system, activity fingerprints are automatically generated from the microphone and the inertial sensors of the smartwatch, and location information is periodically obtained from the smartphone. We designed a hidden Markov model using the relationship between home activities and the room's location. Extensive experiments showed that our system tracks the location of users with 87% accuracy, even when there is no manual training for activities.",

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Lee, S, Kim, Y, Ahn, D, Ha, R, Lee, K & Cha, H 2015, Non-obstructive room-level locating system in home environments using activity fingerprints from smartwatch. in UbiComp 2015 - Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing. UbiComp 2015 - Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Association for Computing Machinery, Inc, pp. 939-950, 3rd ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2015, Osaka, Japan, 15/9/7. https://doi.org/10.1145/2750858.2804272

Non-obstructive room-level locating system in home environments using activity fingerprints from smartwatch. / Lee, Seungwoo; Kim, Yungeun; Ahn, Daye et al.
UbiComp 2015 - Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing. Association for Computing Machinery, Inc, 2015. p. 939-950 (UbiComp 2015 - Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Kim, Yungeun

AU - Ahn, Daye

AU - Ha, Rhan

AU - Lee, Kyoungwoo

AU - Cha, Hojung

N1 - Publisher Copyright: © ACM 978-1-4503-3574-4/15/09..15.00.

PY - 2015/9/7

Y1 - 2015/9/7

N2 - Many smart home applications, such as monitoring for the elderly and home automation, require location information for individual occupants. Several techniques have been proposed for tracking occupants in a home environment. However, the current techniques do not provide a seamless in-home locating system owing to the occupants' devicefree movement and the lack of cost-effective infrastructure for home location tracking. In this paper, we propose a home occupant tracking system that uses a smartphone and an off-The-shelf smartwatch without additional infrastructure. In our system, activity fingerprints are automatically generated from the microphone and the inertial sensors of the smartwatch, and location information is periodically obtained from the smartphone. We designed a hidden Markov model using the relationship between home activities and the room's location. Extensive experiments showed that our system tracks the location of users with 87% accuracy, even when there is no manual training for activities.

AB - Many smart home applications, such as monitoring for the elderly and home automation, require location information for individual occupants. Several techniques have been proposed for tracking occupants in a home environment. However, the current techniques do not provide a seamless in-home locating system owing to the occupants' devicefree movement and the lack of cost-effective infrastructure for home location tracking. In this paper, we propose a home occupant tracking system that uses a smartphone and an off-The-shelf smartwatch without additional infrastructure. In our system, activity fingerprints are automatically generated from the microphone and the inertial sensors of the smartwatch, and location information is periodically obtained from the smartphone. We designed a hidden Markov model using the relationship between home activities and the room's location. Extensive experiments showed that our system tracks the location of users with 87% accuracy, even when there is no manual training for activities.

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Lee S, Kim Y, Ahn D, Ha R, Lee K , Cha H. Non-obstructive room-level locating system in home environments using activity fingerprints from smartwatch. In UbiComp 2015 - Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing. Association for Computing Machinery, Inc. 2015. p. 939-950. (UbiComp 2015 - Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing). doi: 10.1145/2750858.2804272

Non-obstructive room-level locating system in home environments using activity fingerprints from smartwatch

Abstract

Publication series

Other

Bibliographical note

All Science Journal Classification (ASJC) codes

Access to Document

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Cite this