A Fog-enabled Smart Home Analytics Platform

Theo Zschörnig, Robert Wehlitz, Bogdan Franczyk

Abstract

Although the usage of smart home devices such as smart speakers, light bulbs and thermostats has increased rapidly in the past years, their added value, compared to conventional devices, is mostly limited to simple control and automation logic. In order to provide adaptive smart home environments, it is necessary to gain deeper insights into the data generated by these devices and use it in sophisticated data processing pipelines. Providing such analytics to a multitude of consumers requires specialised architectures, which are able to overcome various challenges identified by scientific literature. Currently available smart home analytics architectures are not designed to tackle all of these issues, specifically fault-tolerance, network-usage, latency and external regulations. In this paper, we propose an architectural solution to address these challenges based on the concept of Fog computing. Furthermore, we provide insight into the motivation for this research as well as an overview of the current state of the art in this field.

Download


Paper Citation


in Harvard Style

Zschörnig T., Wehlitz R. and Franczyk B. (2019). A Fog-enabled Smart Home Analytics Platform.In Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-372-8, pages 616-622. DOI: 10.5220/0007750006160622


in Bibtex Style

@conference{iceis19,
author={Theo Zschörnig and Robert Wehlitz and Bogdan Franczyk},
title={A Fog-enabled Smart Home Analytics Platform},
booktitle={Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2019},
pages={616-622},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007750006160622},
isbn={978-989-758-372-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - A Fog-enabled Smart Home Analytics Platform
SN - 978-989-758-372-8
AU - Zschörnig T.
AU - Wehlitz R.
AU - Franczyk B.
PY - 2019
SP - 616
EP - 622
DO - 10.5220/0007750006160622