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A Cloud-based Analytics Architecture for the Application of Online Machine Learning Algorithms on Data Streams in Consumer-centric Internet of Things Domains

Topics: Analytics as a Service (AaaS) for any Types of Analytics; Big Data as a Service (BDaaS) including Frameworks, Empirical Approaches and Data Processing Techniques; Data Processing ; Machine Learning and Deep Learning Approaches Data Analytics; Modeling, Experiments, Sharing Technologies & Platforms

Authors: Theo Zschörnig 1 ; Jonah Windolph 1 ; Robert Wehlitz 1 and Bogdan Franczyk 2

Affiliations: 1 Institute for Applied Informatics (InfAI), Goerdelerring 9, 04109 Leipzig, Germany ; 2 Information Systems Institute, Leipzig University, Grimmaische Str. 12, 04109 Leipzig, Germany, Business Informatics Institute, Wrocaw University of Economics, ul. Komandorska 118-120, 53-345 Wrocaw, Poland

ISBN: 978-989-758-426-8

ISSN: 2184-4976

Keyword(s): Internet of Things, Stream Processing, Online Machine Learning, Kappa Architecture.

Abstract: The increasing number of smart devices in private households has lead to a large quantity of smart homes worldwide. In order to gain meaningful insights into their generated data and offer extended information and added value for consumers, data analytics architectures are essential. In addition, the development and improvement of machine learning techniques and algorithms in the past years has lead to the availability of powerful analytics tools, which have the potential to allow even more sophisticated insights at the cost of changed challenges and requierements for analytics architectures. However, architectural solutions, which offer the ability to deploy flexible, machine learning-based analytics pipelines on streaming data, are missing in research as well as in industry. In this paper, we present the motivation and a concept for machine learning-based data processing on streaming data for consumer-centric Internet of Things domains, such as smart home. This approach was evaluate d in terms of its performance and may serve as a basis for further development and discussion. (More)

CC BY-NC-ND 4.0

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Paper citation in several formats:
Zschörnig, T.; Windolph, J.; Wehlitz, R. and Franczyk, B. (2020). A Cloud-based Analytics Architecture for the Application of Online Machine Learning Algorithms on Data Streams in Consumer-centric Internet of Things Domains. In Proceedings of the 5th International Conference on Internet of Things, Big Data and Security - IoTBDS, ISBN 978-989-758-426-8; ISSN 2184-4976, pages 189-196. DOI: 10.5220/0009339501890196

@conference{iotbds20,
author={Theo Zschörnig. and Jonah Windolph. and Robert Wehlitz. and Bogdan Franczyk.},
title={A Cloud-based Analytics Architecture for the Application of Online Machine Learning Algorithms on Data Streams in Consumer-centric Internet of Things Domains},
booktitle={Proceedings of the 5th International Conference on Internet of Things, Big Data and Security - IoTBDS,},
year={2020},
pages={189-196},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009339501890196},
isbn={978-989-758-426-8},
issn={2184-4976},
}

TY - CONF

JO - Proceedings of the 5th International Conference on Internet of Things, Big Data and Security - IoTBDS,
TI - A Cloud-based Analytics Architecture for the Application of Online Machine Learning Algorithms on Data Streams in Consumer-centric Internet of Things Domains
SN - 978-989-758-426-8
IS - 2184-4976
AU - Zschörnig, T.
AU - Windolph, J.
AU - Wehlitz, R.
AU - Franczyk, B.
PY - 2020
SP - 189
EP - 196
DO - 10.5220/0009339501890196

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