Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/105699
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Computing | - |
dc.creator | Alam Bhuiyan, MZ | en_US |
dc.creator | Wu, J | en_US |
dc.creator | Wang, G | en_US |
dc.creator | Cao, J | en_US |
dc.date.accessioned | 2024-04-15T07:35:58Z | - |
dc.date.available | 2024-04-15T07:35:58Z | - |
dc.identifier.issn | 1551-3203 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/105699 | - |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers | en_US |
dc.rights | ©2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en_US |
dc.rights | The following publication M. Z. Alam Bhuiyan, J. Wu, G. Wang and J. Cao, "Sensing and Decision Making in Cyber-Physical Systems: The Case of Structural Event Monitoring," in IEEE Transactions on Industrial Informatics, vol. 12, no. 6, pp. 2103-2114, Dec. 2016 is available at https://doi.org/10.1109/TII.2016.2518642. | en_US |
dc.subject | Decision making | en_US |
dc.subject | In-network processing | en_US |
dc.subject | Sensor fusion | en_US |
dc.subject | Structural health monitoring (SHM) | en_US |
dc.subject | Wireless sensor networks (WSN) | en_US |
dc.title | Sensing and decision making in cyber-physical systems : the case of structural event monitoring | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 2103 | en_US |
dc.identifier.epage | 2114 | en_US |
dc.identifier.volume | 12 | en_US |
dc.identifier.issue | 6 | en_US |
dc.identifier.doi | 10.1109/TII.2016.2518642 | en_US |
dcterms.abstract | Wireless sensor networks (WSNs) are being suggested at an increasing rate for structural health monitoring (SHM). The objective is to monitor complex events (e.g., damage) in structures (e.g., an industrial machine and a high-rise building) that are usually carried out with wired-based SHM systems. However, monitoring events with a WSN deployed over large structures is challenging due to WSN constraints (high-resolution data transmission and energy) and the quality of monitoring. In this paper, we attempt to design a cyber-physical system (CPS) of structural event monitoring with WSNs and propose a novel model-based in-network decision making in the CPS named MODEM. We think of the idea of generic event detection (like target/object) schemes, and enable each sensor to sense and make a simplified local decision (0/1) on the complex events. We then think of the formation of engineering structures and find that a large physical structure consists of a number of substructures. We enable deployed sensors to be organized into groups in such a way that a groupwise final decision (e.g., 0/1) can be provided for each substructure independently so that the existence of an event (if there is any) in a specific substructure can be identified by WSNs. MODEM is fully distributed in nature, promises to have the monitoring quality similar to the original wired-based schemes, and consumes much less energy for transmissions and computations than existing schemes do. The effectiveness of MODEM is shown via both simulations and real experiments. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | IEEE transactions on industrial informatics, Dec. 2016, v. 12, no. 6, p. 2103-2114 | en_US |
dcterms.isPartOf | IEEE transactions on industrial informatics | en_US |
dcterms.issued | 2016-12 | - |
dc.identifier.scopus | 2-s2.0-85006699736 | - |
dc.identifier.eissn | 1941-0050 | en_US |
dc.description.validate | 202402 bcch | - |
dc.description.oa | Author’s Original | en_US |
dc.identifier.FolderNumber | COMP-1404 | - |
dc.description.fundingSource | RGC | en_US |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | NSF grants; National Natural Science Foundation of China; ISTCP grant; China Hunan Provincial Science & Technology Program; ‘Mobile Health’ Ministry of Education – China Mobile Joint Laboratory; China postdoctoral research fund | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 6706042 | - |
dc.description.oaCategory | Green (AO) | en_US |
Appears in Collections: | Journal/Magazine Article |
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File | Description | Size | Format | |
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Cao_Sensing_Decision_Making.pdf | Preprint version | 3.35 MB | Adobe PDF | View/Open |
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