Intelligent Realities For Workers Using Augmented Reality, Virtual Reality and Beyond
constraints. Both VR and AR reality analytics
apps must deal with the basic problem of
putting context first. If users are going to
gain value from having their analytics in
context, then the analytics cannot overly
obscure the context. In VR, that means that
a 3D model of a factory should be visually
dominant if it is to properly contextualize a
chart about some aspect of the factory’s
operations.
An artificial expert could also carry this
burden or work in concert with a human
expert. The AI chatbot practices 20 seen at
call centers can be brought to bear. Just as
chatbots replace first level call center
representatives, they can alleviate remote
experts from first level work. Then, a single
remote expert can cover more junior
workers and focus on tougher problems.
Digital Twin Overlay
As UI space is at a premium, it becomes
important to use that space wisely. The
challenge is to give the user the best
information for their role at that point of
time and for their current location. AI can
help solve that problem. Rather than forcing
the worker in to a data exploration UI
paradigm which would require many
selection actions, AI can make content
selections on behalf of the worker.
The Industrial Internet Consortium defines a
digital twin as “a digital representation of an
entity, including attributes and behaviors,
sufficient to meet the requirements of a set
of use cases.” 21 It is not only data about a
physical asset, like its service history. A good
digital twin takes the information about the
design, production and operational life of
the asset and virtualizes it in to a digital asset
that can be tested and modified in ways that
you would never treat an operating physical
asset. Instead of a single expensive crash test
of a car, you could perform millions of
crashes virtually. Rather than a couple of
turns around a test track, a car could be
virtually driven for millions of miles across
multiple tests with different service
histories. Such tests could then be used to
feed machine learning neural nets which are
then queried when servicing the real asset.
Artificial Remote Experts
In the popular remote expert use case for
AR 19 , the remote expert could be human or
artificial. For example, a field technician
wears an AR HMD and a human remote
expert can see what the technician is seeing
through the head-mounted camera. The
remote expert could also access equipment
history and metrics.
19
E. Hadar et al., “Hybrid remote expert - an emerging pattern of industrial remote support,” CAiSE Forum, 29th International
Conference on Advanced Information System Engineering, Essen, Germany, June 2017. Available: http://ceur-ws.org/Vol-
1848/CAiSE2017_Forum_Paper5.pdf
20
K. Nimavat and T. Champaneria, “Chatbots: An Overview. Types Architecture, Tools and Future Possibilities,” International
Journal for Scientific Research & Development, October 2017
https://www.researchgate.net/publication/320307269_Chatbots_An_overview_Types_Architecture_Tools_and_Future_Possibi
lities
21
Q1 Digital Twin Interoperability TG Meeting Minutes, Feb 2019, Available:
https://workspace.iiconsortium.org/higherlogic/ws/groups/interop-tg/download/25418/latest
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