Knowledge Management Process for Air Quality Systems based on Data Warehouse Specification

Even though several systems for Air Quality (AQ) monitoring have been in existence for over a decade, a research model for Knowledge Management (KM) of AQ data has to be created in order to enhance the decision-making and organize the air quality data collected from the Internet of Things (IoT) cons...

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Bibliographic Details
Published in:Procedia computer science 2021, Vol.192, p.29-38
Main Authors: Hadj Sassi, Mohamed Saifeddine, Chaari Fourati, Lamia, Zekri, Manel, Ben Yahia, Sadok
Format: Article
Language:English
Subjects:
Air Quality
Conceptual Data Model
Data Warehouse
Knowledge Management
Multidimensional Design
Ontology
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Summary:Even though several systems for Air Quality (AQ) monitoring have been in existence for over a decade, a research model for Knowledge Management (KM) of AQ data has to be created in order to enhance the decision-making and organize the air quality data collected from the Internet of Things (IoT) consumer devices. This model should be made more performant by ensuring greater flexibility and interoperability between devices and emerging technologies. In this context, we propose an approach for representing Data WareHouse (DWH) schema based on an ontology that captures the multidimensional knowledge of tools, techniques, and technologies used for novel AQ systems. This enhances decision-making by coping with potential problems such as data sources heterogeneity and covering the various phases of the decision-making life cycle.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2021.08.004