{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,12,2]],"date-time":"2023-12-02T00:51:11Z","timestamp":1701478271405},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684444","type":"print"},{"value":"9781643684451","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,11,30]],"date-time":"2023-11-30T00:00:00Z","timestamp":1701302400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,11,30]]},"abstract":"<jats:p>Modern site management has made significant progress, and many advancing equipment and technologies have been introduced into the site management process. During power transmission and transformation construction, safety accidents often occur due to fatigue construction or negative emotions. Embedded Devices plus AI is an advanced solution that monitors and identifies worker sentiment in real-time. The LERM model optimized in this paper can run well on embedded devices with reliable accuracy. This model can be well applied to surveillance camera equipment, at low cost, fast response, and high recognition accuracy. The application of cameras with embedded LERM models on power transmission and transformation sites can identify staff emotions in real-time and alarm managers. As a result of this application, fatigue construction or negative emotions can be avoided as a safety hazard in power transmission and transformation construction personnel.<\/jats:p>","DOI":"10.3233\/faia230787","type":"book-chapter","created":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T15:52:31Z","timestamp":1701445951000},"source":"Crossref","is-referenced-by-count":0,"title":["Application of Lightweight Emotion Recognition Model in Intelligent Construction Site Monitoring"],"prefix":"10.3233","author":[{"given":"Zhenxi","family":"Huang","sequence":"first","affiliation":[{"name":"State Grid Hubei Electric Power Co., LTD, Wuhan, 430000, China"}]},{"given":"Jia","family":"Hu","sequence":"additional","affiliation":[{"name":"State Grid Hubei Electric Power Co., LTD, Wuhan, 430000, China"}]},{"given":"Lingfeng","family":"Xu","sequence":"additional","affiliation":[{"name":"State Grid Hubei Electric Power Co., LTD, Wuhan, 430000, China"}]},{"given":"Jing","family":"Li","sequence":"additional","affiliation":[{"name":"State Grid Hubei Electric Power Co., LTD, Wuhan, 430000, China"}]},{"given":"Yuntao","family":"Zou","sequence":"additional","affiliation":[{"name":"School of computer of science and technology, Huazhong University of Science and Technology, Wuhan 430074, China"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Advances in Artificial Intelligence, Big Data and Algorithms"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA230787","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T15:52:32Z","timestamp":1701445952000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA230787"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,30]]},"ISBN":["9781643684444","9781643684451"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia230787","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11,30]]}}}