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A Deep Learning Framework for Industrial Wireless Networks

Published

Author(s)

Mohamed Hany, Rick Candell

Abstract

In this report, we introduce a framework to analyze, monitor, and identify the state of industrial wireless networks and their impact on industrial use cases. This framework is based on a deep learning approach for modeling the interactions between the wireless network and industrial use cases. The framework uses the information from different system layers including the spectrum measurements, physical layer metrics, network layer packets, and application layer production-related metrics in order to study the industrial wireless network behavior. The output of the framework can be generally used to improve system management and optimization functions.
Citation
Technical Note (NIST TN) - 2257
Report Number
2257

Keywords

cyber-physical system modeling, deep learning, industrial wireless, system identification.

Citation

Hany, M. and Candell, R. (2023), A Deep Learning Framework for Industrial Wireless Networks, Technical Note (NIST TN), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://doi.org/10.6028/NIST.TN.2257, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=956211 (Accessed May 20, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created July 25, 2023