Intelligent Realities For Workers Using Augmented Reality, Virtual Reality and Beyond
for Assembly Tasks” from The School
of Manufacturing and Mechanical
Engineering at The University of
Birmingham,
the
authors
investigated if AR and VR offered
potential for training of manual
skills. 9 They compared AR and VR
training methods to the use of
conventional
2D
engineering
drawings and found that AR and VR
approaches resulted in significantly
reduced task completion times.
In the 2015 paper “Augmented
Reality as a Tool for Production and
Quality Monitoring,” the authors
tested use of an AR system rendering
information from Computer Aided
Quality
(CAQ)
software
and
compared it to scenarios using only
CAQ software and using no
software. 10 AR integrated with CAQ
was found to be the fastest
approach.
integration and sense-making of raw IoT
data. This is discussed first in this section.
With the data and analytical foundations in
place, an architectural view of the reality
presentation technologies is presented for
making the best tactical last-mile UI
decisions for rendering to the workers.
IoT Data Pipeline
For real time sense making of an IoT asset, a
streaming analytics engine is necessary. 11 A
streaming analytics engine, like SAS® Event
Stream Processing, analyzes data streams in
motion as the atomic events of the stream
pass by. In addition to applying analytical
methods, it can also provide inferences
derived from machine learning models as
well as contribute to the training of such
models.
In addition to immediate presentation,
analyzed data streams can also be
transferred to data stores for further
analysis and later presentation. While the
big data problems related to IoT described
by Belli et al in “A Scalable Big Stream Cloud
Architecture for the Internet of Things” need
I NTELLIGENT R EALITY A RCHITECTURE
An architecture for an intelligent reality
should be centered on aiding a worker’s
cognition and performance. For workers in
an IoT-enabled reality, the cornerstone of an
intelligent reality architecture is the
9
A. Boud et al., “Virtual Reality and Augmented Reality as a Training Tool for Assembly Tasks,” 1999 IEEE International
Conference on Information Visualization, Jul 1999. Available:
https://pdfs.semanticscholar.org/a563/afc2156eb7285dc67c1c5be7dd3787f0db04.pdf
10
D. Segovia et al., “Augmented Reality as a Tool for Production and Quality Monitoring,” Procedia Computer Science 75:291-
300, Dec 2015. Available: https://core.ac.uk/download/pdf/81959814.pdf
11
B. Klenz, “How to Use Streaming Analytics to Create a Real-Time Digital Twin,” SAS Global Forum 2018, Mar 2018. Available:
https://www.sas.com/content/dam/SAS/support/en/sas-global-forum-proceedings/2018/2004-2018.pdf
- 7 -
March 2019