A Conceptual Data Model and Its Automatic Implementation for IoT-Based Business Intelligence Applications

In the context of Industry 4.0, the analysis of Internet-of-Things (IoT) data with business intelligence (BI) technologies has acquired high relevance. However, designing and implementing IoT-based BI applications is hard for several reasons. Therefore, we propose a novel conceptual data model based...

Full description

Saved in:
Bibliographic Details
Published in:IEEE internet of things journal 2020-10, Vol.7 (10), p.10719-10732
Main Authors: Plazas, Julian Eduardo, Bimonte, Sandro, de Vaulx, Christophe, Schneider, Michel, Nguyen, Quang-Duy, Chanet, Jean-Pierre, Shi, Hongling, Hou, Kun Mean, Carlos Corrales, Juan
Format: Article
Language:English
Subjects:
Automatic implementation
Business intelligence
business intelligence (BI)
Computer Science
data centric
Data models
Engineering Sciences
Industrial applications
Industry 4.0
Information management
Intelligence (information)
Internet of Things
Internet of Things (IoT)
Irrigation
model-driven architecture (MDA)
Networking and Internet Architecture
smart farming
Subsystems
Temperature sensors
UML profile
Unified modeling language
wireless sensor networks (WSNs)
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In the context of Industry 4.0, the analysis of Internet-of-Things (IoT) data with business intelligence (BI) technologies has acquired high relevance. However, designing and implementing IoT-based BI applications is hard for several reasons. Therefore, we propose a novel conceptual data model based on UML profiles and model-driven architecture (MDA) for modeling and implementing IoT-based BI applications. Our approach provides highly readable data models of IoT, which are also compatible with traditional BI data models. Furthermore, it could help in the implementation process of the IoT subsystem through automatic code generation.
ISSN:2327-4662
2372-2541
2327-4662
DOI:10.1109/JIOT.2020.3016608