Persistent Link:
http://hdl.handle.net/10150/596429
Title:
A Program to Display Big Data
Author:
Chantaworakunakorn, Piyarat; Munoz, Michael
Advisor:
Gummadi, Vinod-Kumar; Grubbs, Elmer A.
Affiliation:
Northern Arizona University
Issue Date:
2015-10
Rights:
Copyright © held by the author; distribution rights International Foundation for Telemetering
Collection Information:
Proceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection.
Publisher:
International Foundation for Telemetering
Journal:
International Telemetering Conference Proceedings
Abstract:
This paper describes a new way to look at telemetry data. Northern Arizona University (NAU) students are researching a new approach to apply virtual reality (VR) to evaluate data from a collection of stored signals. Each signal will have limits attached which we will use to view the parts of the waveform which contain abnormalities. A program to illustrate the technique is being developed by NAU students. Initially, we were working with Vizard 5, using the Python language. However, there is another program, Unity, which will perhaps be more useful for the application we wish to achieve. Additionally, we are examining a technique to accurately access the telemetry data collected. The amount of telemetry data collected has increased over the years resulting in difficulties in identifying the relevant information. We are searching for a better approach to store and access big data and will demonstrate this approach by utilizing Oculus Rift and Microsoft Kinect.
Keywords:
telemetry; virtual reality; augmented reality
Sponsors:
International Foundation for Telemetering
ISSN:
0884-5123; 0074-9079
Additional Links:
http://www.telemetry.org/

Full metadata record

DC FieldValue Language
dc.language.isoen_USen
dc.titleA Program to Display Big Dataen_US
dc.contributor.authorChantaworakunakorn, Piyaraten
dc.contributor.authorMunoz, Michaelen
dc.contributor.advisorGummadi, Vinod-Kumaren
dc.contributor.advisorGrubbs, Elmer A.en
dc.contributor.departmentNorthern Arizona Universityen
dc.date.issued2015-10en
dc.rightsCopyright © held by the author; distribution rights International Foundation for Telemeteringen
dc.description.collectioninformationProceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection.en
dc.publisherInternational Foundation for Telemeteringen
dc.description.abstractThis paper describes a new way to look at telemetry data. Northern Arizona University (NAU) students are researching a new approach to apply virtual reality (VR) to evaluate data from a collection of stored signals. Each signal will have limits attached which we will use to view the parts of the waveform which contain abnormalities. A program to illustrate the technique is being developed by NAU students. Initially, we were working with Vizard 5, using the Python language. However, there is another program, Unity, which will perhaps be more useful for the application we wish to achieve. Additionally, we are examining a technique to accurately access the telemetry data collected. The amount of telemetry data collected has increased over the years resulting in difficulties in identifying the relevant information. We are searching for a better approach to store and access big data and will demonstrate this approach by utilizing Oculus Rift and Microsoft Kinect.en
dc.subjecttelemetryen
dc.subjectvirtual realityen
dc.subjectaugmented realityen
dc.description.sponsorshipInternational Foundation for Telemeteringen
dc.identifier.issn0884-5123en
dc.identifier.issn0074-9079en
dc.identifier.urihttp://hdl.handle.net/10150/596429en
dc.identifier.journalInternational Telemetering Conference Proceedingsen
dc.typetexten
dc.typeProceedingsen
dc.relation.urlhttp://www.telemetry.org/en
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