Abstract
Internet of Things (IoT) technologies interconnect increasing numbers of artifacts (e.g., robots, sensors) and individuals, allowing the setting up of Internet of Robotic Things (IoRT) systems in a dynamic environment (e.g., homes, hospitals). Semantic heterogeneity is among the main challenges that arise for developing those systems. Particularly to deal with the dynamic knowledge extraction from the heterogeneity of sensors and data that are spatially and temporally distributed, the sporadic occurrence of events, and also if there is a causality chain that explains an ordered occurrence of these events. Ontologies constitute de facto an ineluctable design to reduce this ambiguity by creating a semantic link between low-level digital data, allowing: i) dynamic knowledge management, and ii) enhancing environmental perception and anchoring functions.
This approach uses a model that overcomes the disadvantages of the semantic Web standards such as OWL/RDF-S. An IoRT system dedicated to monitoring and assisting the elderly in their everyday living is described and evaluated.
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© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Lyazid, S. (2022). Internet of Robot Things in a Dynamic Environment: Narrative-Based Knowledge Representation and Reasoning. In: Hara, T., Yamaguchi, H. (eds) Mobile and Ubiquitous Systems: Computing, Networking and Services. MobiQuitous 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 419. Springer, Cham. https://doi.org/10.1007/978-3-030-94822-1_33
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DOI: https://doi.org/10.1007/978-3-030-94822-1_33
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