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“Chatty Devices” and edge-based activity classification

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journal contribution
posted on 11.11.2021, 15:04 by Mike Lakoju, Amir Javed, Omer Rana, Pete Burnap, Samuelson T. Atiba, Soumaya Cherkaoui
With increasing automation of manufacturing processes (focusing on technologies such as robotics and human-robot interaction), there is a realisation that the manufacturing process and the artefacts/products it produces can be better connected post-production. Built on this requirement, a “chatty" factory involves creating products which are able to send data back to the manufacturing/production environment as they are used, whilst still ensuring user privacy. The intended use of a product during design phase may different significantly from actual usage. Understanding how this data can be used to support continuous product refinement, and how the manufacturing process can be dynamically adapted based on the availability of this data provides a number of opportunities. We describe how data collected on product use can be used to: (i) classify product use; (ii) associate a label with product use using unsupervised learning—making use of edge-based analytics; (iii) transmission of this data to a cloud environment where labels can be compared across different products of the same type. Federated learning strategies are used on edge devices to ensure that any data captured from a product can be analysed locally (ensuring data privacy).

History

Published in

Discover Internet of Things

Publisher

Springer

Acceptance Date

24/12/2020

Publication Date

24/02/2021

Version

VoR (Version of Record)

Citation

Lakoju, M., Javed, A., Rana, O., Burnap, P., Atiba, S.T. and Cherkaoui, S. (2021) '“Chatty devices” and edge-based activity classification', Discover Internet of Things, 1(1), pp.1-15.

Electronic ISSN

2730-7239

Cardiff Met Affiliation

  • Cardiff School of Technologies

Cardiff Met Authors

Mike Lakoju

Copyright Holder

© The Authors

Language

en