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IoT and Fog Analytics for Industrial Robot Applications
Publication Type:
Conference/Workshop Paper
Venue:
The 25th IEEE International Conference on Emerging Technologies and Factory Automation
Abstract
The rapid development of IoT, cloud and fog computing has increased the potential for developing smart services
for IoT devices. Such services require not only connectivity and high computing capacity, but also fast response time and throughput of inferencing results. In this paper we present our ongoing work, investigating the potential for implementing smart services in the context of industrial robot applications with focus on analytic inferencing on fog and cloud computing platforms. We review different use cases that we have found in the literature and
we divide them into two suggested categories, "distributed deep models" and "distributed interconnected models". We analyze the characteristics of IoT data in industrial robot applications and present two concrete use cases of smart services where inferencing in a fog and a cloud architecture, respectively, is needed. We also reason about important considerations and design decisions for the development process of analytic services.
Bibtex
@inproceedings{Lager5942,
author = {Anders Lager and Alessandro Papadopoulos and Thomas Nolte},
title = {IoT and Fog Analytics for Industrial Robot Applications},
month = {September},
year = {2020},
booktitle = {The 25th IEEE International Conference on Emerging Technologies and Factory Automation},
url = {http://www.es.mdu.se/publications/5942-}
}