Components relationship analysis in distributed remote laboratory apparatus with data clustering

Maiti, Ananda and Kist, Alexander A. and Maxwell, Andrew D. (2015) Components relationship analysis in distributed remote laboratory apparatus with data clustering. In: 2015 IEEE 24th International Symposium on Industrial Electronics (ISIE), 3-5 June 2015, Rio de Janeiro, Brazil.

Abstract

Remote Laboratories are network controlled systems operated by human users through the internet for educational purposes. A distributed version of the remote laboratory requires the experimental rigs to be designed by individuals thus making it difficult to obtain formal models of the experimental rigs. A rig consists of a micro-controller unit with multiple ports to connect sensors and actuators. This paper proposes a timed automaton based model of experimental rigs that can be common to all sites. Further, the relationship of components of a rig is analyzed based upon this automaton. The components can be grouped into multiple sets where each set has two properties - the bond between each component in the rig and how frequently they are accessed. A method to obtain the component sets and to determine these two characteristics using data clustering is described.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Copyright ©2015 by IEEE. Abstracting is permitted with credit to the source.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Mechanical and Electrical Engineering
Date Deposited: 22 Jun 2016 03:44
Last Modified: 23 Feb 2017 01:12
Uncontrolled Keywords: remote laboratories; data clustering; finite state automaton;
Fields of Research : 08 Information and Computing Sciences > 0899 Other Information and Computing Sciences > 089999 Information and Computing Sciences not elsewhere classified
09 Engineering > 0913 Mechanical Engineering > 091302 Automation and Control Engineering
09 Engineering > 0906 Electrical and Electronic Engineering > 090699 Electrical and Electronic Engineering not elsewhere classified
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970109 Expanding Knowledge in Engineering
Identification Number or DOI: 10.1109/ISIE.2015.7281571
URI: http://eprints.usq.edu.au/id/eprint/27489

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