research-article

Sensor-based organizational engineering

Authors:

Daniel Olguín Olguín,

Alex (Sandy) PentlandAuthors Info & Claims

ICMI-MLMI '09: Proceedings of the ICMI-MLMI '09 Workshop on Multimodal Sensor-Based Systems and Mobile Phones for Social Computing

Article No.: 4, Pages 1 - 4

https://doi.org/10.1145/1641389.1641393

Published: 06 November 2009 Publication History

Abstract

We propose the use of wearable and environmental sensors to capture and model social interactions in the workplace, combined with data mining techniques and social network analysis for organizational engineering applications. By combining behavioral sensor data with other sources of information such as text-mined documents, surveys, and performance data, it is possible to optimize organizations.

References

[1]

Bharatula, N. B., Stager, M., Lukowicz, P.,&Troster, G. (2005). Empirical Study of Design Choices in Multi-Sensor Context Recognition Systems. Proceedings of the 2nd International Forum on Applied Wearable Computing, (pp. 1--15). Zurich, Switzerland.

[2]

Bowers, C. A., Jentsch, F., Salas, E.,&Braun, C. C. (1998). Analyzing communication sequences for team training needs assessment. Human Factors, 672--679.

[3]

Cakmakci, O., Coutaz, J., Laerhoven, K. V.,&Gellersen, H.-w. (2002). Context awareness in systems with limited resources. Proceedings of the 3rd Workshop on Artificial Intelligence in Mobile Systems, (pp. 21--29).

[4]

Foltz, P. W.,&Martin, M. J. (2009). Automated Communication Analysis of Teams. In E. Salas, G. F. Goodwin,&S. Burke, Team Effectiveness in Complex Organizations (pp. 411--431). New York, NY: Taylor&Francis Group.

[5]

Gatica-Perez, D. (2009). Automatic nonverbal analysis of social interaction in small groups: A review. Image and Vision Computing.

Digital Library

[6]

Gellersen, H. W., Schmidt, A.,&Beigl, M. (2002). Multi-Sensor Context-Awareness in Mobile Devices and Smart Artefacts. Mobile Networks and Applications, 7 (5), 341--351.

Digital Library

[7]

Gibson, J. L., Ivancevich, J. M., Donnelly, J. H.,&Konopaske, R. (2009). Organizations: Behavior, Structure, Processes. New York, NY: McGraw-Hill Irwin.

[8]

Harter, A., Hopper, A., Steggles, P., Ward, A.,&Webster, P. (1999). The anatomy of a context-aware application. Proceedings of the 5th Annual ACM/IEEE International Conference on Mobile Computing and Networking, (pp. 59--68). Seattle, WA.

Digital Library

[9]

Jones, G. J.,&Brown, P. J. (2002). Challenges and Opportunities for Context-Aware Retrieval on Mobile Devices. Proceedings of the Workshop on Mobile Personal Information Retrieval at the 25th Annual International ACM SIGIR Conference, (pp. 47--56). Tampere, Finland.

[10]

Kim, T., Olguin-Olguin, D., Waber, B. N.,&Pentland, A. (2009). Sensor-Based Feedback Systems in Organizational Computing. Workshop on Social Computing with Mobile Phones and Sensors at the 2009 IEEE International Conference on Social Computing, (pp. 1--4). Vancouver, BC.

[11]

Krebs, V. (2008). Social Network Analysis. Retrieved 26 2008, April, from Orgnet: http://www.orgnet.com/sna.html

[12]

Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabási, A.-L., Brewer, D., et al. (2009). Computational Social Science. Science, 323, 721--723.

[13]

Mantyjarvy, J., Himberg, J., Kangas, P., Tuomela, U.,&Huuskonen, P. (2004). Sensor signal data set for exploring context recognition of mobile devices. Proceedings of the 2nd International Conference on Pervasive Computing, (pp. 1--6).

[14]

Nemati, H. R.,&Barko, C. D. (2004). Organizational Data Mining: Leveraging Enterprise Data Resources for Optimal Performance. London: Idea Group Publishing.

Digital Library

[15]

Olguin-Olguin, D. (2007, May). Sociometric badges: Wearable technology for measuring human behavior. Master's Thesis. Cambridge, MA, USA: Massachusetts Institute of Technology.

[16]

Olguin-Olguin, D.,&Pentland, A. (2008). Social Sensors for Automatic Data Collection. 14th Americas Conference on Information Systems (pp. 1--10). Toronto, ON: AIS.

[17]

Olguin-Olguin, D., Waber, B., Kim, T., Mohan, A., Ara, K.,&Pentland, A. (2009). Sensible Organizations: Technology and Methodology for Automatically Measuring Organizational Behavior. IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics, 43--55.

Digital Library

[18]

Oliver, N.,&Horvitz, E. (2005). A Comparison of HMMs and Dynamic Bayesian Networks for Recognizing Office Activities. In User Modeling (Vol. 3538/2005, pp. 199--209). Springer Berlin / Heidelberg.

[19]

Organizational Engineering Institute. (2007). Organizational Research and Knowledge. Retrieved 12 19, 2007, from Organizational Engineering Institute: http://www.oeinstitute.org/index.htm

[20]

Pantic, M., Pentland, A., Nijholt, A.,&Hunag, T. S. (2007). Human Computing and Machine Understanding of Human Behavior: A Survey. In T. H. al., Human Computing (pp. 47--71). Berlin, Germany: Springer-Verlag.

Digital Library

[21]

Pentland, A. (2005). Socially aware computation and communication. IEEE Computer, 38 (3), 33--40.

Digital Library

[22]

Robbins, S. P. (2005). Essentials of Organizational Behavior. Upper Saddle River, NJ: Pearson Prentice Hall.

[23]

Slaughter, A. J., Yu, J.,&Koehly, L. M. (2009). Social Network Analysis: Understanding the Role of Context in Small Groups and Organizations. In E. Salas, G. F. Goodwin,&S. Burke, Team Effectiveness in Complex Organizations (pp. 433--459). Taylor&Francis Group LLC.

[24]

Snijders, T. A. (2009). Introduction to stochastic actor-based models for network dynamics. Social Networks.

[25]

Snijders, T. A. (2006). New Specifications for Exponential Random Graph Models. Sociological Methodology, 99--153.

[26]

Snijders, T. A. (2001). The Statistical Evaluation of Social Network Dynamics. Sociological Methodology, 361--395.

[27]

Tushman, M. L.,&Nadler, D. A. (1978). Information Processing as an Integrating Cocept in Organizational Design. Academy of Management Review, 613--624.

[28]

Van Laerhoven, K., Schmidt, A.,&Gellersen, H. W. (2002). Multi-sensor context aware clothing. Proceedings of the 6th International Symposium on Wearable Computers, (pp. 49--56).

Digital Library

[29]

Wasserman, S.,&Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press: London.

Cited By

Hoseinitabatabaei SGluhak ATafazolli RHeadley W(2014)Design, Realization, and Evaluation of uDirect-An Approach for Pervasive Observation of User Facing Direction on Mobile PhonesIEEE Transactions on Mobile Computing10.1109/TMC.2013.5313:9(1981-1994)Online publication date: Sep-2014
https://doi.org/10.1109/TMC.2013.53

Index Terms

Sensor-based organizational engineering

Recommendations

An energy efficient Genetic Algorithm based approach for sensor-to-sink binding in multi-sink wireless sensor networks

Wireless sensor networks (WSNs) are ad-hoc networks in which sensors, that are designed to relay data back to sink nodes and/or Base Stations, are deployed in an area and may be configured in real time. Sensors, however, have limited energy supplies and ...
Towards a GOD-theory for organizational engineering: continuously modeling the continuous (re)generation, operation and deletion of the enterprise
SAC '10: Proceedings of the 2010 ACM Symposium on Applied Computing

Much time is lost, in organizations, in the handling of unknown exceptions because organizational models are not current or coherent with reality and there is a lack of concepts and methods in organizational engineering (OE), for a continuous and timely ...
Multi-level clustering architecture and protocol designs for wireless sensor networks
WICON '08: Proceedings of the 4th Annual International Conference on Wireless Internet

Wireless sensor network (WSN) consists of sensors for measuring and gathering data in a variety of environments. These sensors, with the size and battery constraints, usually have limited transmission ranges due to the low-power wireless radio ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

ICMI-MLMI '09: Proceedings of the ICMI-MLMI '09 Workshop on Multimodal Sensor-Based Systems and Mobile Phones for Social Computing

November 2009

27 pages

ISBN:9781605586946

DOI:10.1145/1641389

General Chairs:
James Crowley
INRIA
,
Yuri Ivanov
MERL
,
Christopher Wren
Google
,
Program Chairs:
Daniel Gatica-Perez
Idiap Research Institute
,
Michael Johnston
AT&T Research
,
Rainer Stiefelhagen
University of Karlsruhe

Copyright © 2009 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 November 2009

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

ICMI-MLMI '09

Sponsor:

SIGCHI

ICMI-MLMI '09: INTERNATIONAL CONFERENCE ON MULTIMODAL INTERFACES/WORKSHOP ON MACHINE LEARNING FOR MULTIMODAL INTERFACES

November 6, 2009

Massachusetts, Cambridge

Acceptance Rates

Overall Acceptance Rate 453 of 1,080 submissions, 42%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

1
Total Citations
View Citations
174
Total Downloads

Downloads (Last 12 months)2
Downloads (Last 6 weeks)0

Reflects downloads up to 25 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Hoseinitabatabaei SGluhak ATafazolli RHeadley W(2014)Design, Realization, and Evaluation of uDirect-An Approach for Pervasive Observation of User Facing Direction on Mobile PhonesIEEE Transactions on Mobile Computing10.1109/TMC.2013.5313:9(1981-1994)Online publication date: Sep-2014
https://doi.org/10.1109/TMC.2013.53

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten