Enabling Context-Aware Data Analytics in Smart Environments: An Open Source Reference Implementation

In recent years, many proposals of context-aware systems applied to IoT-based smart environments have been presented in the literature. Most previous works provide a generic high-level structure of how a context-aware system can be operationalized, but do not offer clues on how to implement it. On t...

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Autores principales: Andres Munoz-Arcentales, Sonsoles López-Pernas, Javier Conde, Álvaro Alonso, Joaquín Salvachúa, Juan José Hierro
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
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IoT
Acceso en línea:https://doaj.org/article/88ae66b84fd445ef9a030a876c023ec5
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spelling oai:doaj.org-article:88ae66b84fd445ef9a030a876c023ec52021-11-11T19:06:29ZEnabling Context-Aware Data Analytics in Smart Environments: An Open Source Reference Implementation10.3390/s212170951424-8220https://doaj.org/article/88ae66b84fd445ef9a030a876c023ec52021-10-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/21/7095https://doaj.org/toc/1424-8220In recent years, many proposals of context-aware systems applied to IoT-based smart environments have been presented in the literature. Most previous works provide a generic high-level structure of how a context-aware system can be operationalized, but do not offer clues on how to implement it. On the other hand, there are many implementations of context-aware systems applied to specific IoT-based smart environments that are context-specific: it is not clear how they can be extended to other use cases. In this article, we aim to provide an open-source reference implementation for providing context-aware data analytics capabilities to IoT-based smart environments. We rely on the building blocks of the FIWARE ecosystem and the NGSI data standard, providing an agnostic end-to-end solution that considers the complete data lifecycle, covering from data acquisition and modeling, to data reasoning and dissemination. In other words, our reference implementation can be readily operationalized in any IoT-based smart environment regardless of its field of application, providing a context-aware solution that is not context-specific. Furthermore, we provide two example use cases that showcase how our reference implementation can be used in a variety of fields.Andres Munoz-ArcentalesSonsoles López-PernasJavier CondeÁlvaro AlonsoJoaquín SalvachúaJuan José HierroMDPI AGarticlecontext-aware systemsbig datadata analyticssmart environmentsIoTmachine learningChemical technologyTP1-1185ENSensors, Vol 21, Iss 7095, p 7095 (2021)
institution DOAJ
collection DOAJ
language EN
topic context-aware systems
big data
data analytics
smart environments
IoT
machine learning
Chemical technology
TP1-1185
spellingShingle context-aware systems
big data
data analytics
smart environments
IoT
machine learning
Chemical technology
TP1-1185
Andres Munoz-Arcentales
Sonsoles López-Pernas
Javier Conde
Álvaro Alonso
Joaquín Salvachúa
Juan José Hierro
Enabling Context-Aware Data Analytics in Smart Environments: An Open Source Reference Implementation
description In recent years, many proposals of context-aware systems applied to IoT-based smart environments have been presented in the literature. Most previous works provide a generic high-level structure of how a context-aware system can be operationalized, but do not offer clues on how to implement it. On the other hand, there are many implementations of context-aware systems applied to specific IoT-based smart environments that are context-specific: it is not clear how they can be extended to other use cases. In this article, we aim to provide an open-source reference implementation for providing context-aware data analytics capabilities to IoT-based smart environments. We rely on the building blocks of the FIWARE ecosystem and the NGSI data standard, providing an agnostic end-to-end solution that considers the complete data lifecycle, covering from data acquisition and modeling, to data reasoning and dissemination. In other words, our reference implementation can be readily operationalized in any IoT-based smart environment regardless of its field of application, providing a context-aware solution that is not context-specific. Furthermore, we provide two example use cases that showcase how our reference implementation can be used in a variety of fields.
format article
author Andres Munoz-Arcentales
Sonsoles López-Pernas
Javier Conde
Álvaro Alonso
Joaquín Salvachúa
Juan José Hierro
author_facet Andres Munoz-Arcentales
Sonsoles López-Pernas
Javier Conde
Álvaro Alonso
Joaquín Salvachúa
Juan José Hierro
author_sort Andres Munoz-Arcentales
title Enabling Context-Aware Data Analytics in Smart Environments: An Open Source Reference Implementation
title_short Enabling Context-Aware Data Analytics in Smart Environments: An Open Source Reference Implementation
title_full Enabling Context-Aware Data Analytics in Smart Environments: An Open Source Reference Implementation
title_fullStr Enabling Context-Aware Data Analytics in Smart Environments: An Open Source Reference Implementation
title_full_unstemmed Enabling Context-Aware Data Analytics in Smart Environments: An Open Source Reference Implementation
title_sort enabling context-aware data analytics in smart environments: an open source reference implementation
publisher MDPI AG
publishDate 2021
url https://doaj.org/article/88ae66b84fd445ef9a030a876c023ec5
work_keys_str_mv AT andresmunozarcentales enablingcontextawaredataanalyticsinsmartenvironmentsanopensourcereferenceimplementation
AT sonsoleslopezpernas enablingcontextawaredataanalyticsinsmartenvironmentsanopensourcereferenceimplementation
AT javierconde enablingcontextawaredataanalyticsinsmartenvironmentsanopensourcereferenceimplementation
AT alvaroalonso enablingcontextawaredataanalyticsinsmartenvironmentsanopensourcereferenceimplementation
AT joaquinsalvachua enablingcontextawaredataanalyticsinsmartenvironmentsanopensourcereferenceimplementation
AT juanjosehierro enablingcontextawaredataanalyticsinsmartenvironmentsanopensourcereferenceimplementation
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