Distributed sensing for quality and productivity improvements

Yu Ding; Elsayed A. Elsayed; Soundar Kumara; Jye Chyi Lu; Feng Niu; Jianjun Shi

doi:10.1109/TASE.2006.876610

Distributed sensing for quality and productivity improvements

Yu Ding, Elsayed A. Elsayed, Soundar Kumara, Jye Chyi Lu, Feng Niu, Jianjun Shi

Research output: Contribution to journal › Article › peer-review

51 Scopus citations

Abstract

Distributed sensing, a system-wide deployment of sensing devices, has resulted in both temporally and spatially dense data-rich environments. This new technology provides unprecedented opportunities for quality and productivity improvement. This paper discusses the state-of-the-art practice, research challenges, and future directions related to distributed sensing. The discussion includes the optimal design of distributed sensor systems, information criteria, and processing for distributed sensing and optimal decision making in distributed sensing. The discussion also provides applications based on the authors' research experiences.

Original language	English (US)
Article number	1707953
Pages (from-to)	344-358
Number of pages	15
Journal	IEEE Transactions on Automation Science and Engineering
Volume	3
Issue number	4
DOIs	https://doi.org/10.1109/TASE.2006.876610
State	Published - Oct 2006

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Electrical and Electronic Engineering

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10.1109/TASE.2006.876610

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title = "Distributed sensing for quality and productivity improvements",

abstract = "Distributed sensing, a system-wide deployment of sensing devices, has resulted in both temporally and spatially dense data-rich environments. This new technology provides unprecedented opportunities for quality and productivity improvement. This paper discusses the state-of-the-art practice, research challenges, and future directions related to distributed sensing. The discussion includes the optimal design of distributed sensor systems, information criteria, and processing for distributed sensing and optimal decision making in distributed sensing. The discussion also provides applications based on the authors' research experiences.",

author = "Yu Ding and Elsayed, {Elsayed A.} and Soundar Kumara and Lu, {Jye Chyi} and Feng Niu and Jianjun Shi",

note = "Funding Information: Manuscript received July 23, 2004; revised March 15, 2005. This work was supported in part by the National Science Foundation under Grants DMI-0348150, DMI-0400071, DMI-021739, DMI-0400071, and in part by the State of Texas Advanced Technology Program under Grant 000512-0237-2003. This paper is based on a panel discussion which was convened during INFORMS 2003 at Atlanta, GA. Y. Ding was the moderator of the panel and the others were invited panelists. This paper was recommended for publication by Associate Editor M. Lawley and Editor P. Ferreira upon evaluation of the reviewers{\textquoteright} comments.",

year = "2006",

month = oct,

doi = "10.1109/TASE.2006.876610",

language = "English (US)",

volume = "3",

pages = "344--358",

journal = "IEEE Transactions on Automation Science and Engineering",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

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T1 - Distributed sensing for quality and productivity improvements

AU - Ding, Yu

AU - Elsayed, Elsayed A.

AU - Kumara, Soundar

AU - Lu, Jye Chyi

AU - Niu, Feng

AU - Shi, Jianjun

N1 - Funding Information: Manuscript received July 23, 2004; revised March 15, 2005. This work was supported in part by the National Science Foundation under Grants DMI-0348150, DMI-0400071, DMI-021739, DMI-0400071, and in part by the State of Texas Advanced Technology Program under Grant 000512-0237-2003. This paper is based on a panel discussion which was convened during INFORMS 2003 at Atlanta, GA. Y. Ding was the moderator of the panel and the others were invited panelists. This paper was recommended for publication by Associate Editor M. Lawley and Editor P. Ferreira upon evaluation of the reviewers’ comments.

PY - 2006/10

Y1 - 2006/10

N2 - Distributed sensing, a system-wide deployment of sensing devices, has resulted in both temporally and spatially dense data-rich environments. This new technology provides unprecedented opportunities for quality and productivity improvement. This paper discusses the state-of-the-art practice, research challenges, and future directions related to distributed sensing. The discussion includes the optimal design of distributed sensor systems, information criteria, and processing for distributed sensing and optimal decision making in distributed sensing. The discussion also provides applications based on the authors' research experiences.

AB - Distributed sensing, a system-wide deployment of sensing devices, has resulted in both temporally and spatially dense data-rich environments. This new technology provides unprecedented opportunities for quality and productivity improvement. This paper discusses the state-of-the-art practice, research challenges, and future directions related to distributed sensing. The discussion includes the optimal design of distributed sensor systems, information criteria, and processing for distributed sensing and optimal decision making in distributed sensing. The discussion also provides applications based on the authors' research experiences.

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Distributed sensing for quality and productivity improvements

Abstract

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