Orchestrating Heterogeneous Devices and AI Services as Virtual Sensors for Secure Cloud-Based IoT Applications

The concept of the cloud-to-thing continuum addresses advancements made possible by the widespread adoption of cloud, edge, and IoT resources. It opens the possibility of combining classical symbolic AI with advanced machine learning approaches in a meaningful way. In this paper, we present a thing...

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Autores principales:	Sebastian Alberternst, Alexander Anisimov, Andre Antakli, Benjamin Duppe, Hilko Hoffmann, Michael Meiser, Muhammad Muaz, Daniel Spieldenner, Ingo Zinnikus
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	artificial intelligence machine learning internet of things cloud technology semantic web multi-agent systems Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/b0663e21bdff4a02ba7b75c924d6c851
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id	oai:doaj.org-article:b0663e21bdff4a02ba7b75c924d6c851
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spelling	oai:doaj.org-article:b0663e21bdff4a02ba7b75c924d6c8512021-11-25T18:57:01ZOrchestrating Heterogeneous Devices and AI Services as Virtual Sensors for Secure Cloud-Based IoT Applications10.3390/s212275091424-8220https://doaj.org/article/b0663e21bdff4a02ba7b75c924d6c8512021-11-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/22/7509https://doaj.org/toc/1424-8220The concept of the cloud-to-thing continuum addresses advancements made possible by the widespread adoption of cloud, edge, and IoT resources. It opens the possibility of combining classical symbolic AI with advanced machine learning approaches in a meaningful way. In this paper, we present a thing registry and an agent-based orchestration framework, which we combine to support semantic orchestration of IoT use cases across several federated cloud environments. We use the concept of <i>virtual sensors</i> based on machine learning (ML) services as abstraction, mediating between the instance level and the semantic level. We present examples of virtual sensors based on ML models for activity recognition and describe an approach to remedy the problem of missing or scarce training data. We illustrate the approach with a use case from an assisted living scenario.Sebastian AlberternstAlexander AnisimovAndre AntakliBenjamin DuppeHilko HoffmannMichael MeiserMuhammad MuazDaniel SpieldennerIngo ZinnikusMDPI AGarticleartificial intelligencemachine learninginternet of thingscloud technologysemantic webmulti-agent systemsChemical technologyTP1-1185ENSensors, Vol 21, Iss 7509, p 7509 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	artificial intelligence machine learning internet of things cloud technology semantic web multi-agent systems Chemical technology TP1-1185
spellingShingle	artificial intelligence machine learning internet of things cloud technology semantic web multi-agent systems Chemical technology TP1-1185 Sebastian Alberternst Alexander Anisimov Andre Antakli Benjamin Duppe Hilko Hoffmann Michael Meiser Muhammad Muaz Daniel Spieldenner Ingo Zinnikus Orchestrating Heterogeneous Devices and AI Services as Virtual Sensors for Secure Cloud-Based IoT Applications
description	The concept of the cloud-to-thing continuum addresses advancements made possible by the widespread adoption of cloud, edge, and IoT resources. It opens the possibility of combining classical symbolic AI with advanced machine learning approaches in a meaningful way. In this paper, we present a thing registry and an agent-based orchestration framework, which we combine to support semantic orchestration of IoT use cases across several federated cloud environments. We use the concept of <i>virtual sensors</i> based on machine learning (ML) services as abstraction, mediating between the instance level and the semantic level. We present examples of virtual sensors based on ML models for activity recognition and describe an approach to remedy the problem of missing or scarce training data. We illustrate the approach with a use case from an assisted living scenario.
format	article
author	Sebastian Alberternst Alexander Anisimov Andre Antakli Benjamin Duppe Hilko Hoffmann Michael Meiser Muhammad Muaz Daniel Spieldenner Ingo Zinnikus
author_facet	Sebastian Alberternst Alexander Anisimov Andre Antakli Benjamin Duppe Hilko Hoffmann Michael Meiser Muhammad Muaz Daniel Spieldenner Ingo Zinnikus
author_sort	Sebastian Alberternst
title	Orchestrating Heterogeneous Devices and AI Services as Virtual Sensors for Secure Cloud-Based IoT Applications
title_short	Orchestrating Heterogeneous Devices and AI Services as Virtual Sensors for Secure Cloud-Based IoT Applications
title_full	Orchestrating Heterogeneous Devices and AI Services as Virtual Sensors for Secure Cloud-Based IoT Applications
title_fullStr	Orchestrating Heterogeneous Devices and AI Services as Virtual Sensors for Secure Cloud-Based IoT Applications
title_full_unstemmed	Orchestrating Heterogeneous Devices and AI Services as Virtual Sensors for Secure Cloud-Based IoT Applications
title_sort	orchestrating heterogeneous devices and ai services as virtual sensors for secure cloud-based iot applications
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/b0663e21bdff4a02ba7b75c924d6c851
work_keys_str_mv	AT sebastianalberternst orchestratingheterogeneousdevicesandaiservicesasvirtualsensorsforsecurecloudbasediotapplications AT alexanderanisimov orchestratingheterogeneousdevicesandaiservicesasvirtualsensorsforsecurecloudbasediotapplications AT andreantakli orchestratingheterogeneousdevicesandaiservicesasvirtualsensorsforsecurecloudbasediotapplications AT benjaminduppe orchestratingheterogeneousdevicesandaiservicesasvirtualsensorsforsecurecloudbasediotapplications AT hilkohoffmann orchestratingheterogeneousdevicesandaiservicesasvirtualsensorsforsecurecloudbasediotapplications AT michaelmeiser orchestratingheterogeneousdevicesandaiservicesasvirtualsensorsforsecurecloudbasediotapplications AT muhammadmuaz orchestratingheterogeneousdevicesandaiservicesasvirtualsensorsforsecurecloudbasediotapplications AT danielspieldenner orchestratingheterogeneousdevicesandaiservicesasvirtualsensorsforsecurecloudbasediotapplications AT ingozinnikus orchestratingheterogeneousdevicesandaiservicesasvirtualsensorsforsecurecloudbasediotapplications
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Orchestrating Heterogeneous Devices and AI Services as Virtual Sensors for Secure Cloud-Based IoT Applications

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