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SEDIA: A Platform for Semantically Enriched IoT Data Integration and Development of Smart City Applications

Author

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  • Dimitrios Lymperis

    (Information and Communication Systems Engineering Department, University of the Aegean, 83200 Samos, Greece)

  • Christos Goumopoulos

    (Information and Communication Systems Engineering Department, University of the Aegean, 83200 Samos, Greece)

Abstract

The development of smart city applications often encounters a variety of challenges. These include the need to address complex requirements such as integrating diverse data sources and incorporating geographical data that reflect the physical urban environment. Platforms designed for smart cities hold a pivotal position in materializing these applications, given that they offer a suite of high-level services, which can be repurposed by developers. Although a variety of platforms are available to aid the creation of smart city applications, most fail to couple their services with geographical data, do not offer the ability to execute semantic queries on the available data, and possess restrictions that could impede the development process. This paper introduces SEDIA, a platform for developing smart applications based on diverse data sources, including geographical information, to support a semantically enriched data model for effective data analysis and integration. It also discusses the efficacy of SEDIA in a proof-of-concept smart city application related to air quality monitoring. The platform utilizes ontology classes and properties to semantically annotate collected data, and the Neo4j graph database facilitates the recognition of patterns and relationships within the data. This research also offers empirical data demonstrating the performance evaluation of SEDIA. These contributions collectively advance our understanding of semantically enriched data integration within the realm of smart city applications.

Suggested Citation

  • Dimitrios Lymperis & Christos Goumopoulos, 2023. "SEDIA: A Platform for Semantically Enriched IoT Data Integration and Development of Smart City Applications," Future Internet, MDPI, vol. 15(8), pages 1-38, August.
    • Handle: RePEc:gam:jftint:v:15:y:2023:i:8:p:276-:d:1220283
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    References listed on IDEAS

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    1. Biswajeeban Mishra & Biswaranjan Mishra & Attila Kertesz, 2021. "Stress-Testing MQTT Brokers: A Comparative Analysis of Performance Measurements," Energies, MDPI, vol. 14(18), pages 1-20, September.
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    Cited by:

    1. Mahmoud Elkhodr & Samiya Khan & Ergun Gide, 2024. "A Novel Semantic IoT Middleware for Secure Data Management: Blockchain and AI-Driven Context Awareness," Future Internet, MDPI, vol. 16(1), pages 1-31, January.

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