Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/117901
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dc.contributorDepartment of Electrical and Electronic Engineering-
dc.creatorShao, L-
dc.creatorZhang, J-
dc.creatorChen, X-
dc.creatorXu, D-
dc.creatorGu, H-
dc.creatorMu, Q-
dc.creatorYu, F-
dc.creatorLiu, S-
dc.creatorShi, X-
dc.creatorSun, J-
dc.creatorHuang, Z-
dc.creatorYang, X-
dc.creatorZhang, H-
dc.creatorMa, Y-
dc.creatorLu, H-
dc.creatorLiu, C-
dc.creatorYu, C-
dc.date.accessioned2026-03-05T07:57:26Z-
dc.date.available2026-03-05T07:57:26Z-
dc.identifier.urihttp://hdl.handle.net/10397/117901-
dc.language.isoenen_US
dc.publisherSpringerOpenen_US
dc.rights© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.en_US
dc.rightsThe following publication Shao, L., Zhang, J., Chen, X. et al. Artificial intelligence-driven distributed acoustic sensing technology and engineering application. PhotoniX 6, 4 (2025) is available at https://doi.org/10.1186/s43074-025-00160-z.en_US
dc.subjectArtificial intelligence (AI)en_US
dc.subjectDistributed acoustic sensing (DAS)en_US
dc.subjectEngineering applicationen_US
dc.titleArtificial intelligence-driven distributed acoustic sensing technology and engineering applicationen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume6-
dc.identifier.issue1-
dc.identifier.doi10.1186/s43074-025-00160-z-
dcterms.abstractDistributed acoustic sensing (DAS) technology is a fiber-optic based distributed sensing technology. It achieves real-time monitoring of acoustic signals by detecting weak disturbances along the fiber. It has advantages such as long measurement distance, high spatial resolution and large dynamic range. Artificial intelligence (AI) has great application potential in DAS technology, including data augmentation, preprocessing and classification and recognition of acoustic events. By introducing AI algorithms, DAS system can process massive data more automatically and intelligently. Through data analysis and prediction, AI-enabled DAS technology has wide applications in fields such as transportation, energy and security due to its accuracy of monitoring data and reliability of intelligent decision-making. In the future, the continuous advancement of AI technology will bring greater breakthroughs and innovations for the engineering application of DAS technology, play a more important role in various fields, and promote the innovation and development of the industry.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationPhotoniX, Dec. 2025, v. 6, no. 1, 4-
dcterms.isPartOfPhotoniX-
dcterms.issued2025-12-
dc.identifier.scopus2-s2.0-85218448795-
dc.identifier.eissn2662-1991-
dc.identifier.artn4-
dc.description.validate202603 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThis work was supported in part by Department of Natural Resources of Guangdong Province, grant number GDNRC [2022] No. 22; Science, Technology and Innovation Commission of Shenzhen Municipality, grant number 20220815121807001; Intelligent Laser Basic Research Laboratory, grant number PCL2021A14-B1. Key Basic Research Scheme of Shenzhen Natural Science Foundation (JCYJ20200109142010888); Hong Kong Research Grants Council(RGC) under General Research Fund 15224521.en_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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