Components relationship analysis in distributed remote laboratory apparatus with data clustering
Paper
Paper/Presentation Title | Components relationship analysis in distributed remote laboratory apparatus with data clustering |
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Presentation Type | Paper |
Authors | Maiti, Ananda (Author), Kist, Alexander A. (Author) and Maxwell, Andrew D. (Author) |
Journal or Proceedings Title | Proceedings of the 2015 IEEE 24th International Symposium on Industrial Electronics (ISIE) |
ERA Conference ID | 60327 |
Number of Pages | 6 |
Year | 2015 |
Place of Publication | United States |
ISBN | 9781467375542 |
Digital Object Identifier (DOI) | https://doi.org/10.1109/ISIE.2015.7281571 |
Web Address (URL) of Paper | https://ieeexplore.ieee.org/document/7281571 |
Conference/Event | 2015 IEEE 24th International Symposium on Industrial Electronics (ISIE) |
IEEE International Symposium on Industrial Electronics (ISIE) | |
Event Details | 2015 IEEE 24th International Symposium on Industrial Electronics (ISIE) Event Date 03 to end of 05 Jun 2015 Event Location Rio de Janeiro, Brazil |
Event Details | IEEE International Symposium on Industrial Electronics (ISIE) ISIE |
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. |
Keywords | remote laboratories; data clustering; finite stateautomaton; |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
400799. Control engineering, mechatronics and robotics not elsewhere classified | |
400899. Electrical engineering not elsewhere classified | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | School of Mechanical and Electrical Engineering |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q3048/components-relationship-analysis-in-distributed-remote-laboratory-apparatus-with-data-clustering
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