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

Autor: Andres Munoz-Arcentales, Sonsoles López-Pernas, Javier Conde, Álvaro Alonso, Joaquín Salvachúa, Juan José Hierro
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Sensors, Vol 21, Iss 21, p 7095 (2021)
Druh dokumentu: article
ISSN: 1424-8220
DOI: 10.3390/s21217095
Popis: 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.
Databáze: Directory of Open Access Journals