S. S. Arumugam, R. Badrinath, Aitor Hernandez Herranz, J. Höller, Carlos R. B. Azevedo, Bin Xiao, Valentin Tudor
{"title":"Accelerating Industrial IoT Application Deployment through Reusable AI Components","authors":"S. S. Arumugam, R. Badrinath, Aitor Hernandez Herranz, J. Höller, Carlos R. B. Azevedo, Bin Xiao, Valentin Tudor","doi":"10.1109/GIOTS.2019.8766398","DOIUrl":null,"url":null,"abstract":"The Internet of Things (IoT) is penetrating almost all sectors of the global economy, addressing a wide range of opportunities by applying different Artificial Intelligence (AI) tools to IoT data. Due to the diversity in challenges and applications, IoT solutions are often bespoke and highly domain specific. With the surge of IoT applications, this approach to solutions becomes very costly and time consuming if there is a lack of reusability and replicability across different IoT sectors. This work presents a step towards reusability of IoT solution components applied to Industrial IoT (IIoT). We start from the challenging position of two unique AI-driven applications stemming from two separate IIoT verticals - applications which may be realized using the same components. We identify a set of application independent reusable AI-centric components and show how they can be orchestrated into the unique IoT applications. Our approach shortens the time to market and reduces costs for developing IIoT solutions, and opens a path towards reusability and replicability of IIoT components, thus accelerating the IoT market uptake.","PeriodicalId":149504,"journal":{"name":"2019 Global IoT Summit (GIoTS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Global IoT Summit (GIoTS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GIOTS.2019.8766398","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
The Internet of Things (IoT) is penetrating almost all sectors of the global economy, addressing a wide range of opportunities by applying different Artificial Intelligence (AI) tools to IoT data. Due to the diversity in challenges and applications, IoT solutions are often bespoke and highly domain specific. With the surge of IoT applications, this approach to solutions becomes very costly and time consuming if there is a lack of reusability and replicability across different IoT sectors. This work presents a step towards reusability of IoT solution components applied to Industrial IoT (IIoT). We start from the challenging position of two unique AI-driven applications stemming from two separate IIoT verticals - applications which may be realized using the same components. We identify a set of application independent reusable AI-centric components and show how they can be orchestrated into the unique IoT applications. Our approach shortens the time to market and reduces costs for developing IIoT solutions, and opens a path towards reusability and replicability of IIoT components, thus accelerating the IoT market uptake.