{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T03:01:42Z","timestamp":1760151702521,"version":"build-2065373602"},"reference-count":22,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2022,4,9]],"date-time":"2022-04-09T00:00:00Z","timestamp":1649462400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002462","name":"Chungnam National University","doi-asserted-by":"publisher","award":["2019"],"award-info":[{"award-number":["2019"]}],"id":[{"id":"10.13039\/501100002462","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A large number of workers and heavy equipment are used in most industrial sizes, and the prevention of safety accidents is one of the most important issues. Therefore, although a number of systems have been proposed to prevent accidents, existing studies assume that workers are gathered in some areas. These assumptions are not suitable for large-scale industrial sites in which workers form as a group and work in a large area. In other words, in a large-scale industrial site, existing schemes are unsuitable for the timely notifying of warnings of threats, and excessive energy is consumed. Therefore, we propose a k-means clustering-based safety system for a large-scale industrial site. In the proposed scheme, workers deployed over a large area are divided into an appropriate number of groups, and threat notification is delivered by a multicasting tree toward each cluster. The notification to workers is delivered through local flooding in each cluster. The simulation results show that the system is able to deliver the notification within a valid time, and it is energy efficient compared to the existing scheme.<\/jats:p>","DOI":"10.3390\/s22082897","type":"journal-article","created":{"date-parts":[[2022,4,10]],"date-time":"2022-04-10T06:02:54Z","timestamp":1649570574000},"page":"2897","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["K-Means Clustering-Based Safety System in Large-Scale Industrial Site Using Industrial Wireless Sensor Networks"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4568-2709","authenticated-orcid":false,"given":"Dongyeong","family":"Seo","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Chungnam National University, Daejeon 34134, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sangdae","family":"Kim","sequence":"additional","affiliation":[{"name":"Medical Infromation Technology Engineering, Soonchunhyang University, Asan 31538, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2139-8746","authenticated-orcid":false,"given":"Seungmin","family":"Oh","sequence":"additional","affiliation":[{"name":"Division of Computer Science and Engineering, Kongju National University, Cheonan 31080, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sang-Ha","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Chungnam National University, Daejeon 34134, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Sullivan, G., Pugh, R., Melendez, A.P., and Hunt, W. 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