1. What Artificial Intelligence Means to the Internet of Things
Justin Grammens
Cofounder, Lab 651

2. Who is Justin Grammens? Background Serial Entrepreneur
Cofounder of Lab 651
20+ years Architecting & Engineering Software Solutions
MS in Software Engineering from University of Saint Thomas
Cofounder of IoT Fuse
501 (c)(3) non-profit to advance the Internet of Things in Minnesota and beyond
Owner of IoT Weekly News
Adjunct Professor at the University of Saint Thomas teaching an advanced graduate level course on IoT

3. Who is Lab 651? Decades of Experience Building “Smart” Products
Physical Product Design
User Experience & Feel
Mechanical Engineering
Electrical Hardware & Firmware
Connectivity / Wireless Design
Power Optimization
Electrical Engineering
Mobile Applications
Cloud / Web Applications
Machine Learning / AI
Software Engineering & Data Science

4. S4, Solution Specialist Sales Summit
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S4, Solution Specialist Sales Summit
Where Did IoT Come From?
6/13/ :13 AM
Term was coined key Kevin Ashton at MIT in 1999
People had connected and controlled machines for decades
1977 – Smart electric meter created
1980’s - Members of Carnegie-Mellon connected Coke Machine
1994 – Xerox PARC demonstrates wearable device recording interactions
1995 – Siemens demonstrates connected vehicle telematics & monitoring
Really started to gain adoption in 2013
Kevin recently has started calling it: “The Internet For Things”
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5. Google Trends for IoT Trends
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S4, Solution Specialist Sales Summit
Google Trends for IoT
6/13/ :13 AM
Trends
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6. Google Trends for IoT & Big Data Trends
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S4, Solution Specialist Sales Summit
Google Trends for IoT & Big Data
6/13/ :13 AM
Trends
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7. Google Trends for IoT, Big Data & ML Trends
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S4, Solution Specialist Sales Summit
Google Trends for IoT, Big Data & ML
6/13/ :13 AM
Trends
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8. S4, Solution Specialist Sales Summit
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S4, Solution Specialist Sales Summit
How To Think of the IoT
6/13/ :13 AM
Companies need to move beyond the technology of IoT to applying an industry lens and relevant use cases
IoT should be thought of in conjunction with other technologies
Machine Learning / Artificial Intelligence
Augmented Reality / Virtual Reality
Data Visualization & Analytics
Blockchain
All of the above
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9. What is AI

10. What is AI

11. What is AI & IoT
What makes AI different when talking about IoT is that it can reach out and touch you.

12. Where IoT and AI is Today
Still in the early stage of acceptance
Many companies don’t see the value of the data
Aren’t aware of the possible sensor technologies
Think they need to hire a team of data scientists
Have not been through physical product development
Don’t know where to start - technology alphabet soup
Too much focus on the “what”, not enough on the “why”
Stuck on data visualization and not on the AI that drives actions ( Indy Car Racing example )
To apply AI to data from IoT devices we need a lot of data
Cellular connectivity costs are coming down
Pushing more intelligence to the edge with gateways

13. Industrial Scenario(s)
You own a manufacturing company
Biggest source of lost time and cost is machine failure – thousands of dollars per hour.
What if you could track machine behavior?
Predict movements that are indicators of failure
Order parts for maintenance during scheduled downtimes
Prevent waste by only doing maintenance when it’s need
You are a machine manufacturer
Currently you only receive revenue when the machine is purchased or need repair (low margin)
Offer a service to monitor and prevent downtime with your customer (high margin)
Better quality of service and experience by the customer using your product

14. Manufacturing Process
Spikes show potential failure before downtime occurs and poor quality in production

15. Quality & AI - Weld Splatter
•Avoid quality problems due to spatters from resistance welding by identifying previously unknown patterns in the process data
•Learn how to detect and avoid splatters before they occur
•Generate knowledge by data mining algorithms to minimize spatters
•The weld controller can react – for example, by reducing the power for every individual welding process to avoid spatters

16. Consumer Usage Patterns
Usage of Craftsman and Kenmore Products by Consumers

17. Intelligent Consumer Products
Appliance monitoring
Proactive maintenance (ex. before refrigerator compressor failure)
Order replacement parts & alert service technicians
Real-time usage and performance of models
Energy savings
Run electrical components at time of less energy cost
Manufacturer performance
Which manufacturers are performing better than others

18. Intelligent Hydraulic Hoses
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S4, Solution Specialist Sales Summit
Intelligent Hydraulic Hoses
6/13/ :13 AM
Eaton has been manufacturing hoses for a hundred years
Process was to replace the hose when they failed
What if they could predict before the hose broke?
Customer avoids downtime
Customer avoids environmental mess of hydraulic fluid
Customer avoids potential injury to employee
Eaton now could sell less hoses ( less margin )
However now has higher margin selling a monitoring service
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19. Intelligent Classrooms
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S4, Solution Specialist Sales Summit
Intelligent Classrooms
6/13/ :13 AM
Wildflower Montessori Schools wanted to improve outcomes in the classroom
What if they could monitor lessons, students and teachers relative location to create a super teacher?
Team at Lab 651 built
Intelligent lesson trays
Sensor for each student’s slippers
Sensor for the teacher’s pocket
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20. Intelligent Waste Water Treatment Cost of Clean H2O
It takes 1-2 KW to create 264 gallons of water from wastewater (higher in states like CA)
One NYC WWTP treats 1.4B gallons a day (5.3M KWh)
Almost $1M a day in energy costs
$690,000 spent on pumping and aeration
Pumps being run at 100% capacity due to the best possible but unknown output

21. Intelligent Waste Water Treatment
21,200 WWTP in the US
Each one averages 760,000 gallons a day
Average of 4,318 kWh / day / facility
$10.9M / day we spend on WWT
69% of energy costs are spent on pumping and aeration = $7.5M a day or $2.8B a year
Cost $1, / IoT sensor
At 10% energy reduction - upside of $260M a year
IoT Data w/
Artificial Intelligence

22. “What AI Means to the IoT “
Due to the massive datasets required
AI is a requirement for IoT to provide value

23. Thank You! Justin Grammens Cofounder, Lab 651 justin@lab651.com
6/13/2018
© 2012 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.
The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.
Thank You!
Justin Grammens
Cofounder, Lab 651