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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MDPI AG
2021
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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) |
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artificial intelligence machine learning internet of things cloud technology semantic web multi-agent systems Chemical technology TP1-1185 |
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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 |
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