Thelma Leonor Estévez Dorantes, David B Hernandez, Arnulfo León Reyes, Cynthia Elena Miranda Medina
{"title":"Development of a powerful facial recognition system through an API using ESP32-Cam and Amazon Rekognition service as tools offered by Industry 5.0","authors":"Thelma Leonor Estévez Dorantes, David B Hernandez, Arnulfo León Reyes, Cynthia Elena Miranda Medina","doi":"10.1145/3523111.3523122","DOIUrl":null,"url":null,"abstract":"The main intention of this work is to show how the evolution of Industry 5.0 has impacted on the development of highly advanced cloud tools to be integrated into any large-scale technological project. This work describes an Application Program Interface (API) development to take advantage of two major technologies, the use of ESP32-Cam as a means of image acquisition for IoT projects and the artificial intelligence service for facial recognition from Amazon Rekognition as part of the cloud computing and Industry 5.0. This API Integrates both technologies to create a facial recognition and people validation system in the cloud. The end-user system provides a high-speed response latency taking about 5 seconds to identify a person, offering a similarity match greater than 95%.","PeriodicalId":410530,"journal":{"name":"International Conference on Machine Vision and Applications","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Machine Vision and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3523111.3523122","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The main intention of this work is to show how the evolution of Industry 5.0 has impacted on the development of highly advanced cloud tools to be integrated into any large-scale technological project. This work describes an Application Program Interface (API) development to take advantage of two major technologies, the use of ESP32-Cam as a means of image acquisition for IoT projects and the artificial intelligence service for facial recognition from Amazon Rekognition as part of the cloud computing and Industry 5.0. This API Integrates both technologies to create a facial recognition and people validation system in the cloud. The end-user system provides a high-speed response latency taking about 5 seconds to identify a person, offering a similarity match greater than 95%.