Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/104436
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Industrial and Systems Engineering | - |
| dc.creator | Tsang, YP | en_US |
| dc.creator | Choy, KL | en_US |
| dc.creator | Wu, CH | en_US |
| dc.creator | Ho, GTS | en_US |
| dc.date.accessioned | 2024-02-05T08:49:52Z | - |
| dc.date.available | 2024-02-05T08:49:52Z | - |
| dc.identifier.issn | 1089-7798 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/104436 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Institute of Electrical and Electronics Engineers | en_US |
| dc.rights | © 2019 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 Tsang, Y. P., Choy, K. L., Wu, C. H., & Ho, G. T. S. (2019). Multi-Objective Mapping Method for 3D Environmental Sensor Network Deployment. IEEE Communications Letters, 23(7), 1231–1235 is available at https://doi.org/10.1109/LCOMM.2019.2914440. | en_US |
| dc.subject | Environmental sensor network | en_US |
| dc.subject | Genetic algorithm | en_US |
| dc.subject | Mapping method | en_US |
| dc.subject | Multi-objective optimization | en_US |
| dc.subject | Multi-responses Taguchi method | en_US |
| dc.title | Multi-objective mapping method for 3D environmental sensor network deployment | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.spage | 1231 | en_US |
| dc.identifier.epage | 1235 | en_US |
| dc.identifier.volume | 23 | en_US |
| dc.identifier.issue | 7 | en_US |
| dc.identifier.doi | 10.1109/LCOMM.2019.2914440 | en_US |
| dcterms.abstract | Effective deployment of the emerging environmental sensor network in environmental mapping has become essential in numerous industrial applications. The essential factors for deployment include cost, coverage, connectivity, airflow of heating, ventilation, and air conditioning, system lifetime, and fault tolerance. In this letter, a three-stage deployment scheme is proposed to formulate the above-mentioned considerations, and the fuzzy temperature window is established to adjust sensor activation times over various ambient temperatures. To optimize the deployment effectively, a multi-response Taguchi-guided k-means clustering is proposed to embed in the genetic algorithm, where an improved set of the initial population is formulated and system parameters are optimized. Therefore, the computational time for repeated deployment is shortened, while the solution convergence can be improved. | - |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | IEEE communications letters, July 2019, v. 23, no. 7, p. 1231-1235 | en_US |
| dcterms.isPartOf | IEEE communications letters | en_US |
| dcterms.issued | 2019-07 | - |
| dc.identifier.scopus | 2-s2.0-85068832992 | - |
| dc.identifier.eissn | 1558-2558 | en_US |
| dc.identifier.artn | 8705334 | en_US |
| dc.description.validate | 202402 bcch | - |
| dc.description.oa | Accepted Manuscript | en_US |
| dc.identifier.FolderNumber | ISE-0460 | - |
| dc.description.fundingSource | Self-funded | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.identifier.OPUS | 53188915 | - |
| dc.description.oaCategory | Green (AAM) | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Tsang_Multi-Objective_Mapping_Method.pdf | Pre-Published version | 844.74 kB | Adobe PDF | View/Open |
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