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Modeling Inhabited Smart Spaces to Support Interoperable IoT-Based Applications

  • Roberto Yus
  • , Nada Lahjouji
  • , Georgios Bouloukakis
  • , Sharad Mehrotra
  • , Nalini Venkatasubramanian
  • Biochemical and Environmental Engineering
  • Long Beach VA and University of California
  • University of Patras

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collectionContribution à une conférenceRevue par des pairs

Résumé

IoT deployments in smart spaces can enable the development of useful services for their inhabitants. However, the diversity of smart spaces and their sensor infrastructures makes it challenging to develop space-agnostic applications. Moreover, existing schemas addressing interoperability challenges often lack the vocabulary needed to represent the integration of smart space systems and their inhabitants. We present a schema to annotate inhabited smart spaces in support of inhabitant-oriented applications. Our schema integrates well-known ontologies to represent inhabitants, events/activities, and the space itself, along with their interconnections. It also supports the representation of uncertain information from IoT and mobile sensors (e.g., a person's location or occupancy/attendance at an event). Additionally, we introduce an annotation tool that uses an easy-to-use GUI to describe a smart space based on our schema. We demonstrate the potential of our approach through a series of SPARQL queries and a system deployed at the UCI campus that annotates sensor data to support a space-agnostic occupancy monitoring application.

langue originaleAnglais
titreProceedings - 2025 26th IEEE International Conference on Mobile Data Management, MDM 2025
EditeurInstitute of Electrical and Electronics Engineers Inc.
Pages43-54
Nombre de pages12
ISBN (Electronique)9798331525699
Les DOIs
étatPublié - 1 janv. 2025
Modification externeOui
Evénement26th IEEE International Conference on Mobile Data Management, MDM 2025 - Irvine, États-Unis
Durée: 2 juin 20255 juin 2025

Série de publications

NomProceedings - IEEE International Conference on Mobile Data Management
ISSN (imprimé)1551-6245

Une conférence

Une conférence26th IEEE International Conference on Mobile Data Management, MDM 2025
Pays/TerritoireÉtats-Unis
La villeIrvine
période2/06/255/06/25

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