Augmented Reality for Workforce Mobility The Next Level

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1 Augmented Reality for Workforce Mobility The Next Level John Simmins Technical Executive Information, Communication, and Cyber Security (ICCS) European Engagement Summit April 28-29, 2015

2 Agenda Augmented reality - definition Augmented reality efficiency Augmented reality First EPRI project Next EPRI project 2

environment whose elements are augmented by computer-generated sensory input such as

3 Augmented Reality: What is it and where did it come from? Augmented reality (AR) is a live, direct or indirect, view of a physical, realworld environment whose elements are augmented by computer-generated sensory input such as sound, video, graphics or GPS data. Not to be confused with virtual reality which replaces a real world with a simulated one. 3

4 Augmented Reality: What is it and where did it come from? Combines the real world with the virtual world, Is interactive and in real-time Is registered in 3 dimensions. 4

5 So, why consider augmented reality? 5

Boeing Results* 46 Participants Tablets, not HMDs Three areas of interest First time quality (lowest errors) Fastest Time Worker efficiency ** *T. Richardson, S. Gilbert, J. Holub, F. Thompson, A.

6 Boeing Results* 46 Participants Tablets, not HMDs Three areas of interest First time quality (lowest errors) Fastest Time Worker efficiency ** *T. Richardson, S. Gilbert, J. Holub, F. Thompson, A. MacAllister, R. Radkowski, E. Winer, P.Davies, and S. Terry, Fusing Self-Reported and Sensor Data from Mixed-Reality Training, Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC) **Model Based Instruction

7 Boeing Results* 46 Participants Tablets, not HMDs Three areas of interest First time quality (lowest errors) Fastest Time Worker efficiency ** *T. Richardson, S. Gilbert, J. Holub, F. Thompson, A. MacAllister, R. Radkowski, E. Winer, P.Davies, and S. Terry, Fusing Self-Reported and Sensor Data from Mixed-Reality Training, Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC) **Model Based Instruction

8 Boeing Results* 46 Participants Tablets, not HMDs Three areas of interest First time quality (lowest errors) Fastest Time Worker efficiency ** *T. Richardson, S. Gilbert, J. Holub, F. Thompson, A. MacAllister, R. Radkowski, E. Winer, P.Davies, and S. Terry, Fusing Self-Reported and Sensor Data from Mixed-Reality Training, Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC) **Model Based Instruction

9 Canadian Air Force Results* The task performance results were evaluated using five parameters: The amount of work required to do the task The level of understanding of the intent of the task The likelihood of information being lost or misplaced The likelihood of an error in the task The long-term durability of the information Results percent improvement across the five evaluation criteria Task work decreases from 119 hours to 82 hours. *NGRAIN Case Study 9

10 Canadian Air Force Results* The task was to integrate electronic technologies into the Interactive Electronic Technical Manuals (IETMs) currently used by CF CC-130 technicians: The number of technicians is smaller and less experienced. Enable novices to perform maintenance like seasoned experts Interactive animations added Results Technicians completed tasks 25% faster Technicians completed tasks with 22% more accurately *NGRAIN Case Study 10

11 Key Workflow Enablers For Utilities Infrastructure & Technology Comm protocols High speed networks Store and forward Advanced analytics Standards Enterprise Replace existing workflows Interface with existing back office systems 11

12 Field Force Data Visualization (FFDV) Showcase the power of the Common Information Model (CIM) in reducing vendor lockin Illustrate the immediate value of CIM Create a proof-of-concept as to what is possible in field force communications Demonstrate benefits in efficiencies and worker safety 12

13 Emergency Restoration Field Force Data Visualization The Keys: GIS Context Aware CIM Augmented Reality Data overlays Usable for ANY work but excels at storm damage assessment Usable for ANY asset 13

14 Successes Imported and displayed four sets of GIS data Created and tested several CIM messages Demonstrated value to utilities Illustrated data problems with CIS 14

15 Challenges Hardware GPS location services can be enhanced Robustness Data Challenges with large data sets Bad GIS data Software Presentation icons scalable Use of SDK reduced issues with AR Define more CIM messages 15

16 New Supplemental Project 16

17 Accelerating Augmented Reality for the Electricity Industry Project Description Establish list of use cases Pair up leading AR companies with participants Develop AR solutions Incorporate standards Measure results Calculate cost/benefit 17

18 Accelerating Augmented Reality for the Electricity Industry Value Direct interaction with leading augmented reality technology providers Identify and define the utility activities that the technology providers will focus on First to demonstrate vendor products Clear understanding of the value of augmented reality for utility applications 18

19 Together Shaping the Future of Electricity 19

20 GWAC Stack 20

Field Force Operational Data Visualization What s So Smart About It?

Field Force Operational Data Visualization What s So Smart About It? John J. Simmins, Ph.D. Electric Power Research Institute Smart Grid Information Sharing Call November 27, 2012 The self healing grid