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Dynniq & GoDataDriven - Shaping the future of traffic with IoT and AI

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Dynniq & GoDataDriven - Shaping the future of traffic with IoT and AI

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Dynniq is a high-tech, innovative company offering smart mobility solutions and services internationally. We will present advanced IoT use cases Dynniq is working on, and share how GoDataDriven helps set up an AI capability. We will share our learnings, and show what makes data science in the mobility domain unique.

Dynniq is a high-tech, innovative company offering smart mobility solutions and services internationally. We will present advanced IoT use cases Dynniq is working on, and share how GoDataDriven helps set up an AI capability. We will share our learnings, and show what makes data science in the mobility domain unique.

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Dynniq & GoDataDriven - Shaping the future of traffic with IoT and AI

  1. 1. Shaping the future of traffic Big Data Expo September 20th, 2018 Robbin Blokpoel Lead researcher Steven Nooijen Data Science Consultant
  2. 2. Dynniq cooperative research involvement Initial Research phase Cooperative and Connected Architecture COOP/CAD research Deployment
  3. 3. Intelligent Control Systems..
  4. 4. Virtual Emission Monitoring 7 Emissions Algorithms Fleet Flow Speed Data sources currently include: • MIDAS • SCOOT • Automatic Traffic Counters • Bluetooth Sensors • Google • DATEX II • ImCity • Department for Transport Fleet Statistics
  5. 5. Validation of the model.. 8
  6. 6. Setting up a Data Lab with GoDataDriven: 9 Rapid prototyping brings ideas and business cases to live A solid technical foundation is required to grow a data science and engineering capability
  7. 7. Data Science capability 10
  8. 8. 11 Start small with a Data Lab Business DataLab Data Platform Business Liaison Lead Data Scientist Lead Data Engineer Core Team Data Team 1 Product Owner Business Analyst Data Scientist Data Engineer Product Champion Data Team 2 Product Owner Business Analyst Data Scientist Data Engineer Product Champion Data Team 3 Product Owner Business Analyst Data Scientist Data Engineer Product Champion
  9. 9. Collect and prioritize use cases 12 Design & Explore Activities to execute for every idea Pilot Deploy & Maintain SelectCollect & Refine € Proof of Concept Activity to execute ongoing Idea phase Experiment phase Industrialize phase
  10. 10. And fire up the recruitment process 13
  11. 11. Flow as a Service 14 Rapid prototyping
  12. 12. Rapidly build MVPs to test value 15
  13. 13. The use case: Flow as a Service 16 Goals • Measuring real-time network performance • Monitoring KPIs and detecting of anomalies • Fully scalable
  14. 14. Choosing sides: which cloud fits best? 17 ü More optimized for advanced machine learning ü Pretty advanced in ‘serverless’ offerings. Focus on coding instead of hardware and configuration. ü Considered the more ‘sexy’ in the data science community. This could help attract talent. - Doesn’t work well with existing Microsoft services - Contract negation not done yet ü Already used within Dynniq ü Integrates well with other Microsoft services used: Active Directory, Navision, PowerBI ü Microsoft is more accepted or feels more reliable than Google amongst Dynniq clients - Microsoft’s HDInsight not the best Spark offering Solution
  15. 15. What a traffic controller sends us… 18 Signal statuses Sensors
  16. 16. Leading to the first insights 19 2de Paasdag Koningsdag Hemelvaart
  17. 17. More interesting to link sensors and signals 20
  18. 18. To calculate KPIs: red light negation 21
  19. 19. And model traffic flow: queueing theory 22
  20. 20. Apply data science for anomaly detection 23
  21. 21. Top off with visualization 24
  22. 22. Design Cloud agnostic 25
  23. 23. 26 FlowSense Service Architecture Presentation Data Analytics Application services IoT Data Management Equipment, Sensors and Actuators Slice it!
  24. 24. We are hiring! recruitment.nl@dynniq.com Vacancy Data Scientist: https://goo.gl/zL7Bry signal@godatadriven.com

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