Session from the North American Collaboration Summit on using Azure Cognitive Services to check images taken from a Raspberry Pi for the presence of our food truck. If present it informs the user in MS Teams or Skype.
Nacs 2018 Office 365, Azure and a Raspberry Pi - a 21st century lunch bell
1. OFFICE 365, AZURE AND A
RASPBERRY PI: A 21ST CENTURY
LUNCH BELL
NACS 2018, Branson, MO – Thomas Gölles
2. THOMAS GÖLLES
Head of Modern Workplace Solutions
Co-Organizer of SharePoint Saturday Vienna (#SPSVIE),
Office 365 Meetup Graz, Office 365 Meetup Vienna
http://www.modernworkplacesolutions.rocks/
@thomyg
3. MAKE SURE TO THANK OUR SPONSORS!
WEAR YOUR NACS WRISTBAND FOR
LUNCH SPECIALS ON BRANSON LANDING
PLAY VENDOR BINGO FOR YOUR
CHANCE TO WIN A i7 16GB 1TB SURFACE
BOOK
10. POSSIBLE SOLUTIONS
Create a recurrent event in Outlook
“Ping” a colleague everyday
Stand up and have a look
Use technology to solve the problem
11. MOCADESYMO
Penny: Well, you know, it’s the Cheesecake Factory. People order
cheesecake, and I bring it to them.
Leonard: So, you sort of act as a Carbohydrate Delivery System.
Penny: Yeah, call it whatever you want, I get minimum wage.
Mobile Monitor
15. MAKE SURE TO
ATTEND THE
ATTENDEE PARTY
FRIDAY NIGHT AT
7:30PM AT BLACK
OAK GRILL FOR
GREATE LIVE
MUSIC
GET YOUR FREE
DRINK TICKETS AT
THE END OF THE
DAY SESSION ON
FRIDAY
17. Chatbots 101
“a computer program designed to have a
conversation with a human being, especially over the
internet” *
* https://dictionary.cambridge.org/dictionary/english/chatbot
18. “HOW DO YOU PERCEIVE COMPANIES THAT OFFER A CHATBOT?”
https://insights.ubisend.com/2017-chatbot-report
24. Researchers took a traditional machine learning approach
• Example: HoG Detectors
- Histogram of oriented
gradients (HoG) features
- Sliding window detector
- SVM Classifier
- Very fast OpenCV
implementation (<100ms)
25. Deep Neural Network for Computer Vision
cat? YES
dog? NO
car? NO
Convolutional Layers
Fully
Connected
Layers
Complex Objects
& Scenes
(people, animals,
cars, beach
scene, etc.)
Image
Low-Level Features
(lines, edges,
color fields, etc.)
High-Level Features
(corners, contours,
simple shapes)
Object Parts
(wheels, faces,
windows, etc.)
33. AZURE FUNCTION
• Min. Visual Studio 2017
Update 2
• Usage of custom library
• Including PnP library
• Gets triggered by the
curl request from the Pi
• Takes the image from
the blob storage
34. AZURE FUNCTION
• Calls Custom Vision API
• Gets back the prediction
result from http request
• Stores data to log and
state tables
• Informs users in Teams
by calling a connector if
prediction is above a
certain threshold
• uploads pictures to a
SharePoint Portal
35. CUSTOM VISION API
• Project with sample data
• Start with at least 30
images
• Train the models
• Use live data to learn in
iterations
• Be prepared to
understand prediction
results
• Getting above 95% with
~450 images now
40. Log table with every call
and result from the
Custom Vision API
State Table with
timestamps at arriving and
leaving for easier
integration of other
systems in the future
(Cortana, Alexa, bot
framework)
STORAGE TABLES
49. PRIZE DRAWINGS HAPPEN AFTER THE END OF THE DAY SESSIONS ON FRIDAY AND
SATURDAY. YOU MUST ATTEND THE END OF THE DAY SESSION TO WIN.
Editor's Notes
Die Fotos vom Fotoshooting können frei verwendet werden und liegen hier: http://bit.ly/SOLVIONFOTOS
Solvion Logos liegen hier: http://bit.ly/SOLVIONLOGO
Für die richtige Anreihung der Elemente „Lineal“ und „Führungslinien“ unter „Ansicht“ aktivieren
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