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Building an intelligent Pullup-Classifier - Iterations, Learnings, Thoughts

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Building an intelligent Pullup-Classifier - Iterations, Learnings, Thoughts

  1. 1. OMM Solutions TECHtalk #1 www.omm-solutions.de 30.03.2017 < OMM Solutions GmbH > 1 www.tech-talks.eu
  2. 2. Einmal im Monat ist TECHtalk Zeit! First come first served! < OMM Solutions GmbH > 2
  3. 3. Talk: Building an intelligent Pullup-Classifier Speaker: Olaf Horstmann 3< OMM Solutions GmbH >
  4. 4. 30.03.2017 < OMM Solutions GmbH > 4
  5. 5. • should COUNT the pullups • should detect WHO • should classify the QUALITY The Goal 30.03.2017 < OMM Solutions GmbH > 5
  6. 6. Image from: http://www.instructables.com/id/Pull-Up-Counter/ Existing solutions 30.03.2017 < OMM Solutions GmbH > 6
  7. 7. 30.03.2017 < OMM Solutions GmbH > 7
  8. 8. ✓ COUNT × WHO × QUALITY Can we use it? 30.03.2017 < OMM Solutions GmbH > 8
  9. 9. The Pressure-Sensor Iteration #1 30.03.2017 < OMM Solutions GmbH > 9
  10. 10. Let‘s try it! 30.03.2017 < OMM Solutions GmbH > 10
  11. 11. OKAY… 30.03.2017 < OMM Solutions GmbH > 11
  12. 12. The Ultrasonic-Sensor Iteration #2 30.03.2017 < OMM Solutions GmbH > 12
  13. 13. 30.03.2017 < OMM Solutions GmbH > 13
  14. 14. 30.03.2017 < OMM Solutions GmbH > 14
  15. 15. • Only works on perpendicular angles (+/-15°) • Only works on „flat“ surfaces (hair or clothes = bad) • You can hear it when it is quiet BUT… 30.03.2017 < OMM Solutions GmbH > 15
  16. 16. An optical sensor Iteration #3 30.03.2017 < OMM Solutions GmbH > 16
  17. 17. 30.03.2017 < OMM Solutions GmbH > 17
  18. 18. 30.03.2017 < OMM Solutions GmbH > 18
  19. 19. Success 30.03.2017 < OMM Solutions GmbH > 19
  20. 20. • Cost more than the other sensors • Inaccurate/slow > 2m • Might not work very well in direct sunlight (did not test) Any Drawbacks? 30.03.2017 < OMM Solutions GmbH > 20
  21. 21. • Collected data from different people • Prepate the data • Implement an AI to classify the data Now what? 30.03.2017 < OMM Solutions GmbH > 21
  22. 22. Collecting/Comparing Data 30.03.2017 < OMM Solutions GmbH > 22
  23. 23. • Algorithm to detect individual pullups (=> count) • Label each data-set manually (=> who & quality) Data-Preparation 30.03.2017 < OMM Solutions GmbH > 23
  24. 24. Data-Preparation 30.03.2017 < OMM Solutions GmbH > 24
  25. 25. • Throw in the raw data (~200 pullups) • Train it • See what happens • => accuracy ~60% With Tensorflow AI Iteration #1 30.03.2017 < OMM Solutions GmbH > 25
  26. 26. • More data (a lot more!) • Adjust the network (not really better) • Use meta-data instead of raw data How can we improve this? 30.03.2017 < OMM Solutions GmbH > 26
  27. 27. • Using ~15 different meta-data-points • => accuracy ~85% AI Iteration #2 30.03.2017 < OMM Solutions GmbH > 27
  28. 28. • Normalize data (high values are bad!) • …and more data! …but there‘s still room for improvements It‘s Okay… 30.03.2017 < OMM Solutions GmbH > 28
  29. 29. • Normalized data • => accuracy at +90% AI Iteration #3 30.03.2017 < OMM Solutions GmbH > 29
  30. 30. „The Product“ 30.03.2017 < OMM Solutions GmbH > 30
  31. 31. • Data preparation is probably the most important step • Visualizing the data helps analyzing it • Less data can be compensated by transforming the data first • Having more classes can help with the accuracy of the whole model • More data is always better Learnings 30.03.2017 < OMM Solutions GmbH > 31
  32. 32. Vielen Dank für Eure Aufmerksamkeit! 32< OMM Solutions GmbH >
  33. 33. Ihr persönlicher Ansprechpartner Fragen oder Interesse? < OMM Solutions GmbH > 33 Olaf Horstmann Technology & Innovation OMM Solutions GmbH Vor dem Lauch 4 70567 Stuttgart Germany oh@omm-solutions.de +49 (0)711 75 86 46 04
  34. 34. 34< OMM Solutions GmbH > www.omm-solutions.de OMM Solutions GmbH Vor dem Lauch 4 70567 Stuttgart Geschäftsführer Martin Allmendinger Malte Horstmann Olaf Horstmann Kontakt Telefon: +49 711 6747 051-0 E-Mail: info@omm-solutions.de Umsatzsteuer-ID: DE295716572 Sitz der Gesellschaft: Stuttgart Amtsgericht Stuttgart, HRB 749562 Impressum

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