{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T15:14:55Z","timestamp":1778339695564,"version":"3.51.4"},"reference-count":15,"publisher":"SAGE Publications","issue":"11","license":[{"start":{"date-parts":[[2021,11,1]],"date-time":"2021-11-01T00:00:00Z","timestamp":1635724800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Major Scientific Research Instrument Development Project","award":["6202780085"],"award-info":[{"award-number":["6202780085"]}]},{"name":"National Key R&D Project","award":["2018YFB2200900"],"award-info":[{"award-number":["2018YFB2200900"]}]},{"name":"The General Object of National Natural Science Foundation","award":["61972273"],"award-info":[{"award-number":["61972273"]}]},{"name":"Shanxi Province key technology and Generic technology R & D project","award":["2020XXX007"],"award-info":[{"award-number":["2020XXX007"]}]},{"name":"NSFC program","award":["61672372"],"award-info":[{"award-number":["61672372"]}]},{"name":"Scientific and Technologial Innovation Programs of Higher Education Institutions in Shanxi","award":["2019L1009"],"award-info":[{"award-number":["2019L1009"]}]},{"name":"Scientific and Technologial Innovation Programs of Higher Education Institutions in Shanxi","award":["2019L0473"],"award-info":[{"award-number":["2019L0473"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Distributed Sensor Networks"],"published-print":{"date-parts":[[2021,11]]},"abstract":"<jats:p> The photovoltaic industry is a strategic and sunrise industry with international competitive advantages. Driven by policy guidance and market demand, the new energy industry represented by the photovoltaic industry has been a significant emerging industry in developing the national economy and people\u2019s livelihood. Stable photovoltaic power generation capacity supply is a critical issue in the photovoltaic industry. With the popularization of industrial Internet technology and Internet of things technology, more and more academic and industrial circles begin to introduce new technologies to provide the latest research results and solutions for the photovoltaic industry. Electroluminescence is a standard detection method for photovoltaic production in the application of solar energy production. This method uses human vision to detect whether the solar silicon unit is defective. In this article, due to the three core pain points in traditional electroluminescence detection: low efficiency of offline identification, low accuracy and accuracy of data detection, and no online diagnosis and prediction, we carry out ISEE research based on edge computing unit. ISEE uses the edge device to collect the real-time video image of the solar panel through the camera. Then it uses the powerful neural network processing unit module of the edge computing unit, combined with the convolutional neural network algorithm transplanted to the edge, to detect the defects of solar panels in real time. It completes the research on intelligent detection of photovoltaic power generation production defects based on the Internet of Things. After a large number of experimental design verification, ISEE effectively improves the automation degree and identification accuracy in the production and detection process of solar photovoltaic cells and reduces the cost of operation and maintenance. The accuracy rate reaches 93.75%, which has significant theoretical research significance and practical application value. <\/jats:p>","DOI":"10.1177\/15501477211050552","type":"journal-article","created":{"date-parts":[[2021,11,9]],"date-time":"2021-11-09T08:50:27Z","timestamp":1636447827000},"page":"155014772110505","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":12,"title":["ISEE: Industrial Internet of Things perception in solar cell detection based on edge computing"],"prefix":"10.1177","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0510-6192","authenticated-orcid":false,"given":"Meiya","family":"Dong","sequence":"first","affiliation":[{"name":"College of Information and Computer, Taiyuan University of Technology, Taiyuan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jumin","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Information and Computer, Taiyuan University of Technology, Taiyuan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Deng-ao","family":"Li","sequence":"additional","affiliation":[{"name":"College of Information and Computer, Taiyuan University of Technology, Taiyuan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Biaokai","family":"Zhu","sequence":"additional","affiliation":[{"name":"Network Security Department, Shanxi Police College, Taiyuan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sihai","family":"An","sequence":"additional","affiliation":[{"name":"Engineering Department, GengDan Institute of Beijing University of Technology, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhaobin","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer engineering, Suzhou Vocational University, Suzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2021,11,9]]},"reference":[{"issue":"2","key":"bibr2-15501477211050552","first-page":"21","volume":"100","author":"Hoffman A.","year":"2014","journal-title":"Washing Acad Sci: J Washing Acad Sci"},{"key":"bibr3-15501477211050552","doi-asserted-by":"publisher","DOI":"10.1016\/j.rser.2015.04.001"},{"key":"bibr4-15501477211050552","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2015.11.007"},{"key":"bibr5-15501477211050552","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclepro.2019.01.150"},{"key":"bibr6-15501477211050552","first-page":"1","volume":"33","author":"Zhang S","year":"2020","journal-title":"Neur Comput Appl"},{"issue":"1","key":"bibr7-15501477211050552","first-page":"388","volume":"2013","author":"Ganescu V","year":"2013","journal-title":"Inter Symp 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