{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T18:11:12Z","timestamp":1782151872397,"version":"3.54.5"},"reference-count":27,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2022,3,3]],"date-time":"2022-03-03T00:00:00Z","timestamp":1646265600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Future Greater-Bay Area Network Facilities for Large-scale Experiments and Applications","award":["LZC0019"],"award-info":[{"award-number":["LZC0019"]}]},{"name":"The Verification Platform of Multi-tier Coverage Communication Network for Oceans","award":["LZC0020"],"award-info":[{"award-number":["LZC0020"]}]},{"name":"Guangdong Department of Science and Technology","award":["2021A0505080002"],"award-info":[{"award-number":["2021A0505080002"]}]},{"name":"Shenzhen Science, Technology &amp; Innovation Commission","award":["20200925162216001"],"award-info":[{"award-number":["20200925162216001"]}]},{"name":"Guangdong Department of Education","award":["2021ZDZX1023"],"award-info":[{"award-number":["2021ZDZX1023"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper proposes a real-time multi-class disturbance detection algorithm based on YOLO for distributed fiber vibration sensing. The algorithm achieves real-time detection of event location and classification on external intrusions sensed by distributed optical fiber sensing system (DOFS) based on phase-sensitive optical time-domain reflectometry (\u03a6-OTDR). We conducted data collection under perimeter security scenarios and acquired five types of events with a total of 5787 samples. The data is used as a spatial\u2013temporal sensing image in the training of our proposed YOLO-based model (You Only Look Once-based method). Our scheme uses the Darknet53 network to simplify the traditional two-step object detection into a one-step process, using one network structure for both event localization and classification, thus improving the detection speed to achieve real-time operation. Compared with the traditional Fast-RCNN (Fast Region-CNN) and Faster-RCNN (Faster Region-CNN) algorithms, our scheme can achieve 22.83 frames per second (FPS) while maintaining high accuracy (96.14%), which is 44.90 times faster than Fast-RCNN and 3.79 times faster than Faster-RCNN. It achieves real-time operation for locating and classifying intrusion events with continuously recorded sensing data. Experimental results have demonstrated that this scheme provides a solution to real-time, multi-class external intrusion events detection and classification for the \u03a6-OTDR-based DOFS in practical applications.<\/jats:p>","DOI":"10.3390\/s22051994","type":"journal-article","created":{"date-parts":[[2022,3,3]],"date-time":"2022-03-03T20:36:30Z","timestamp":1646339790000},"page":"1994","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":58,"title":["Real-Time Multi-Class Disturbance Detection for \u03a6-OTDR Based on YOLO Algorithm"],"prefix":"10.3390","volume":"22","author":[{"given":"Weijie","family":"Xu","sequence":"first","affiliation":[{"name":"Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen 518055, 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China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guoqing","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Microelectronics, Shenzhen Institute of Information Technology, Shenzhen 518172, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xingliang","family":"Shen","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen 518055, China"},{"name":"The Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Kowloon, Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weizhi","family":"Wang","sequence":"additional","affiliation":[{"name":"Peng Cheng Laboratory, Shenzhen 518005, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feng","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Engineering and Applied Sciences, Nanjing University, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huanhuan","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen 518055, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1391-4736","authenticated-orcid":false,"given":"Perry Ping","family":"Shum","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen 518055, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1272-1959","authenticated-orcid":false,"given":"Liyang","family":"Shao","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen 518055, China"},{"name":"Peng 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