{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T05:35:33Z","timestamp":1769924133393,"version":"3.49.0"},"reference-count":20,"publisher":"Walter de Gruyter GmbH","issue":"1","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,10,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>The safety monitoring system has been used to monitor and manage engineering safety operation. The application scope of the safety monitoring system is very wide. It has a wide range of applications in the fields of pipeline safety monitoring, electrical safety monitoring and household safety monitoring. This article studied the application process of the household safety monitoring system. Many home safety accidents are caused by inadequate monitoring of safety problems. Therefore, it is very important to establish a household safety monitoring system. Traditional home safety monitoring systems only rely on cameras for safety monitoring, and the traditional home safety monitoring system uses too few sensors. With the continuous development of wireless sensor network (WSN) technology, it is possible to build a sensor node network, but provides real-time information for home security monitoring to the greatest extent. This article compared the home safety monitoring system based on the WSN technology of artificial intelligence (AI) with the traditional home safety monitoring system. The experimental results showed that in the large-scale home environment, the average monitoring accuracy of the traditional home security monitoring system and the home security monitoring system based on the WSN technology of AI was 77.76 and 89.36%, respectively. In the small-scale home environment, the average monitoring accuracy of the traditional home safety monitoring system and the home safety monitoring system based on the WSN technology of AI were 87.63 and 94.43%, respectively. Monitoring accuracy refers to the accuracy of the household safety monitoring system in detecting safety issues. Therefore, the application of the WSN technology based on artificial intelligence to the home safety monitoring system can effectively improve the accuracy of home safety monitoring.<\/jats:p>","DOI":"10.1515\/comp-2022-0280","type":"journal-article","created":{"date-parts":[[2023,10,4]],"date-time":"2023-10-04T12:20:40Z","timestamp":1696422040000},"source":"Crossref","is-referenced-by-count":7,"title":["Application of wireless sensor network technology based on artificial intelligence in security monitoring system"],"prefix":"10.1515","volume":"13","author":[{"given":"Yajuan","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Information Engineering, Hainan Vocational University of Science and Technology , Haikou 571126, Hainan , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ru","family":"Jing","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, Hainan Vocational University of Science and Technology , Haikou 571126, Hainan , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiang","family":"Ji","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, Hainan Vocational University of Science and Technology , Haikou 571126, Hainan , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nan","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of Business Administration, Hainan Vocational University of Science and Technology , Haikou 571126, Hainan , China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2023,10,4]]},"reference":[{"key":"2023100412203494972_j_comp-2022-0280_ref_001","doi-asserted-by":"crossref","unstructured":"H. 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