{"title":"Computational intelligence, machine learning techniques, and IOT","authors":"K. Vijayakumar","doi":"10.1177/1063293X211001573","DOIUrl":null,"url":null,"abstract":"In the current scenario, automated approaches are widely adopted in various domains to implement the computerized monitoring and regulation. The massive advancement in the machine-driven technologies such as computational intelligence, machine-learning scheme, deep-learning scheme, and the Internet of Things (IoT) helped to advance the industrial automation to the next level, in which the automated detection and classification is easily implemented. Computerized systems are essential in a variety of domains to achieve an error free monitoring and the control without compromising the accuracy. Further, the availability of advanced computational facilities helps to achieve superior outcomes, in a variety of domains, such as industry, manufacturing, agriculture, medical, and other engineering and science domains. The integration of traditional approach with the recent computational intelligence technique also helps to achieve a better result during the problem solving practice. The integration of the recent approach along with the IoT helped to automate the entire system using the current internet technology and also supports the remote monitoring and control. When an industry is equipped with all these facility is also called as an industry ready with the essential future enhancement essential to implement ‘‘Industry 4.0’’ an essential keyword to indicate the present trend of automation and data exchange in industries which includes; cyber-physical systems, IoT, cloud computing, and cognitive computing with essential smart facilities.","PeriodicalId":10680,"journal":{"name":"Concurrent Engineering","volume":"91 1","pages":"3 - 5"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Concurrent Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/1063293X211001573","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
In the current scenario, automated approaches are widely adopted in various domains to implement the computerized monitoring and regulation. The massive advancement in the machine-driven technologies such as computational intelligence, machine-learning scheme, deep-learning scheme, and the Internet of Things (IoT) helped to advance the industrial automation to the next level, in which the automated detection and classification is easily implemented. Computerized systems are essential in a variety of domains to achieve an error free monitoring and the control without compromising the accuracy. Further, the availability of advanced computational facilities helps to achieve superior outcomes, in a variety of domains, such as industry, manufacturing, agriculture, medical, and other engineering and science domains. The integration of traditional approach with the recent computational intelligence technique also helps to achieve a better result during the problem solving practice. The integration of the recent approach along with the IoT helped to automate the entire system using the current internet technology and also supports the remote monitoring and control. When an industry is equipped with all these facility is also called as an industry ready with the essential future enhancement essential to implement ‘‘Industry 4.0’’ an essential keyword to indicate the present trend of automation and data exchange in industries which includes; cyber-physical systems, IoT, cloud computing, and cognitive computing with essential smart facilities.