M. O. Silva, Gustavo M. Torres, Myke D. M. Valadão, E. V. C. U. Mattos, Antônio M. C. Pereira, Matheus S. Uchôa, Lucas M. Torres, N. ValneyM., Victor L. G. Cavalcante, José E. B. S. Linhares, Adriel V. Dos Santos, Agemilson P. Silva, Caio F. S. Cruz, Rômulo Fabrício, Ruan J. S. Belém, Lucas Fujita, Felipe A.A. Araújo, Carlos A. Monteiro, Thiago B. Bezerra, W. S. S. Júnior, Celso B. Carvalho
{"title":"Action and Assembly Time Measurement System of Industry Workers using Jetson Nano","authors":"M. O. Silva, Gustavo M. Torres, Myke D. M. Valadão, E. V. C. U. Mattos, Antônio M. C. Pereira, Matheus S. Uchôa, Lucas M. Torres, N. ValneyM., Victor L. G. Cavalcante, José E. B. S. Linhares, Adriel V. Dos Santos, Agemilson P. Silva, Caio F. S. Cruz, Rômulo Fabrício, Ruan J. S. Belém, Lucas Fujita, Felipe A.A. Araújo, Carlos A. Monteiro, Thiago B. Bezerra, W. S. S. Júnior, Celso B. Carvalho","doi":"10.1109/ICCE-Taiwan55306.2022.9869028","DOIUrl":null,"url":null,"abstract":"In this work, conducted by three partners, called UFAM/CETELI, Envision (TPV Group) and ICTS, we present an embedded system capable of recognizing actions and measuring the assembly time of human workers on an industrial production line. The system is composed of machine learning algorithms and the embedded platform NVIDIA Jetson Nano. In terms of performance, the system achieved rates (best case) 91%.","PeriodicalId":164671,"journal":{"name":"2022 IEEE International Conference on Consumer Electronics - Taiwan","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Consumer Electronics - Taiwan","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCE-Taiwan55306.2022.9869028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this work, conducted by three partners, called UFAM/CETELI, Envision (TPV Group) and ICTS, we present an embedded system capable of recognizing actions and measuring the assembly time of human workers on an industrial production line. The system is composed of machine learning algorithms and the embedded platform NVIDIA Jetson Nano. In terms of performance, the system achieved rates (best case) 91%.
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