A dining context-aware system with mobile and wearable devices

Kee Hoon Kim; Sung Bae Cho

doi:10.1109/CIT/IUCC/DASC/PICOM.2015.2

A dining context-aware system with mobile and wearable devices

Kee Hoon Kim, Sung Bae Cho

College of Computing

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

2 Citations (Scopus)

Abstract

With development of various sensors attached to mobile and wearable devices, recognizing user's current context and giving an appropriate service come to hot issue. In this paper, we propose the context-aware system recognizing user's dining context that can occur within a great variety of contexts. The model uses low-level sensor data from mobile and wristwearable devices that can be widely available in daily life. To cope with innate complexity and fuzziness in high-level contexts like dining, a context model represents the related contexts systemically based on 4 components of activity theory and 5 W's, and tree-structured Bayesian network can recognizes the dining context probabilistically. To verify the proposed system, we collected 383 minutes of data from 4 people in a week and found that the proposed method outperforms the conventional machine learning methods, as to accuracy (94.57%). Also we built an Android application to investigate its practicality, and conducted a scenario-based test to investigate the effect of individual context for recognition.

Original language	English
Title of host publication	Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015
Editors	Luigi Atzori, Xiaolong Jin, Stephen Jarvis, Lei Liu, Ramon Aguero Calvo, Jia Hu, Geyong Min, Nektarios Georgalas, Yulei Wu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2381-2386
Number of pages	6
ISBN (Electronic)	9781509001545
DOIs	https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.2
Publication status	Published - 2015 Dec 22
Event	15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015 - Liverpool, United Kingdom Duration: 2015 Oct 26 → 2015 Oct 28

Publication series

Name	Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015

Other

Other	15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015
Country/Territory	United Kingdom
City	Liverpool
Period	15/10/26 → 15/10/28

Bibliographical note

Funding Information:
This work is supported by the National Strategic R&D Program for Industrial Technology (10044828, Development of augmenting multisensory technology for enhancing significant effect on service industry), funded by the Ministry of Trade, Industry and Energy (MOTIE).

Publisher Copyright:
© 2015 IEEE.

All Science Journal Classification (ASJC) codes

Information Systems
Artificial Intelligence
Computer Networks and Communications

Access to Document

10.1109/CIT/IUCC/DASC/PICOM.2015.2

Cite this

Kim, K. H., & Cho, S. B. (2015). A dining context-aware system with mobile and wearable devices. In L. Atzori, X. Jin, S. Jarvis, L. Liu, R. A. Calvo, J. Hu, G. Min, N. Georgalas, & Y. Wu (Eds.), Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015 (pp. 2381-2386). Article 7363398 (Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.2

Kim, Kee Hoon ; Cho, Sung Bae. / A dining context-aware system with mobile and wearable devices. Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015. editor / Luigi Atzori ; Xiaolong Jin ; Stephen Jarvis ; Lei Liu ; Ramon Aguero Calvo ; Jia Hu ; Geyong Min ; Nektarios Georgalas ; Yulei Wu. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 2381-2386 (Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015).

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title = "A dining context-aware system with mobile and wearable devices",

abstract = "With development of various sensors attached to mobile and wearable devices, recognizing user's current context and giving an appropriate service come to hot issue. In this paper, we propose the context-aware system recognizing user's dining context that can occur within a great variety of contexts. The model uses low-level sensor data from mobile and wristwearable devices that can be widely available in daily life. To cope with innate complexity and fuzziness in high-level contexts like dining, a context model represents the related contexts systemically based on 4 components of activity theory and 5 W's, and tree-structured Bayesian network can recognizes the dining context probabilistically. To verify the proposed system, we collected 383 minutes of data from 4 people in a week and found that the proposed method outperforms the conventional machine learning methods, as to accuracy (94.57%). Also we built an Android application to investigate its practicality, and conducted a scenario-based test to investigate the effect of individual context for recognition.",

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note = "Funding Information: This work is supported by the National Strategic R&D Program for Industrial Technology (10044828, Development of augmenting multisensory technology for enhancing significant effect on service industry), funded by the Ministry of Trade, Industry and Energy (MOTIE). Publisher Copyright: {\textcopyright} 2015 IEEE.; 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015 ; Conference date: 26-10-2015 Through 28-10-2015",

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editor = "Luigi Atzori and Xiaolong Jin and Stephen Jarvis and Lei Liu and Calvo, {Ramon Aguero} and Jia Hu and Geyong Min and Nektarios Georgalas and Yulei Wu",

booktitle = "Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015",

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Kim, KH & Cho, SB 2015, A dining context-aware system with mobile and wearable devices. in L Atzori, X Jin, S Jarvis, L Liu, RA Calvo, J Hu, G Min, N Georgalas & Y Wu (eds), Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015., 7363398, Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015, Institute of Electrical and Electronics Engineers Inc., pp. 2381-2386, 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015, Liverpool, United Kingdom, 15/10/26. https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.2

A dining context-aware system with mobile and wearable devices. / Kim, Kee Hoon; Cho, Sung Bae.
Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015. ed. / Luigi Atzori; Xiaolong Jin; Stephen Jarvis; Lei Liu; Ramon Aguero Calvo; Jia Hu; Geyong Min; Nektarios Georgalas; Yulei Wu. Institute of Electrical and Electronics Engineers Inc., 2015. p. 2381-2386 7363398 (Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015).

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

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N2 - With development of various sensors attached to mobile and wearable devices, recognizing user's current context and giving an appropriate service come to hot issue. In this paper, we propose the context-aware system recognizing user's dining context that can occur within a great variety of contexts. The model uses low-level sensor data from mobile and wristwearable devices that can be widely available in daily life. To cope with innate complexity and fuzziness in high-level contexts like dining, a context model represents the related contexts systemically based on 4 components of activity theory and 5 W's, and tree-structured Bayesian network can recognizes the dining context probabilistically. To verify the proposed system, we collected 383 minutes of data from 4 people in a week and found that the proposed method outperforms the conventional machine learning methods, as to accuracy (94.57%). Also we built an Android application to investigate its practicality, and conducted a scenario-based test to investigate the effect of individual context for recognition.

AB - With development of various sensors attached to mobile and wearable devices, recognizing user's current context and giving an appropriate service come to hot issue. In this paper, we propose the context-aware system recognizing user's dining context that can occur within a great variety of contexts. The model uses low-level sensor data from mobile and wristwearable devices that can be widely available in daily life. To cope with innate complexity and fuzziness in high-level contexts like dining, a context model represents the related contexts systemically based on 4 components of activity theory and 5 W's, and tree-structured Bayesian network can recognizes the dining context probabilistically. To verify the proposed system, we collected 383 minutes of data from 4 people in a week and found that the proposed method outperforms the conventional machine learning methods, as to accuracy (94.57%). Also we built an Android application to investigate its practicality, and conducted a scenario-based test to investigate the effect of individual context for recognition.

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AN - SCOPUS:84964240908

T3 - Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015

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Kim KH, Cho SB. A dining context-aware system with mobile and wearable devices. In Atzori L, Jin X, Jarvis S, Liu L, Calvo RA, Hu J, Min G, Georgalas N, Wu Y, editors, Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 2381-2386. 7363398. (Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015). doi: 10.1109/CIT/IUCC/DASC/PICOM.2015.2

A dining context-aware system with mobile and wearable devices

Abstract

Publication series

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Bibliographical note

All Science Journal Classification (ASJC) codes

Access to Document

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