Ana Rita Santiago, M. Antunes, J. Barraca, D. Gomes, R. Aguiar
{"title":"SCoTv2: Large Scale Data Acquisition, Processing, and Visualization Platform","authors":"Ana Rita Santiago, M. Antunes, J. Barraca, D. Gomes, R. Aguiar","doi":"10.1109/FiCloud.2019.00053","DOIUrl":null,"url":null,"abstract":"Internet of Things (IoT) solutions are becoming very popular since everything can now be processed through a technological service. Currently, data is digital information, creating the need to design platforms and services that fill the gap between data sensors and processing frameworks. IoT Platforms are responsible for attaching data sources with the remaining processing architecture. This paper presents a Machine to Machine (M2M) platform able to monitor data acquisition, processing, and visualization. The use of SCoTv2 allows users to integrate several sources and obtain relevant information only by connecting their sensors with the platform. As our preeminent goal is creating a large scale platform useful for several scenarios, a significant part of the study is related to software challenges, and the connection between technologies. Therefore, our principal contribution is the definition of effective architecture able to reply to different use cases.","PeriodicalId":268882,"journal":{"name":"2019 7th International Conference on Future Internet of Things and Cloud (FiCloud)","volume":"53 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 7th International Conference on Future Internet of Things and Cloud (FiCloud)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FiCloud.2019.00053","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Internet of Things (IoT) solutions are becoming very popular since everything can now be processed through a technological service. Currently, data is digital information, creating the need to design platforms and services that fill the gap between data sensors and processing frameworks. IoT Platforms are responsible for attaching data sources with the remaining processing architecture. This paper presents a Machine to Machine (M2M) platform able to monitor data acquisition, processing, and visualization. The use of SCoTv2 allows users to integrate several sources and obtain relevant information only by connecting their sensors with the platform. As our preeminent goal is creating a large scale platform useful for several scenarios, a significant part of the study is related to software challenges, and the connection between technologies. Therefore, our principal contribution is the definition of effective architecture able to reply to different use cases.