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.

1. Shaping the future of traffic
Big Data Expo
September 20th, 2018
Robbin Blokpoel
Lead researcher
Steven Nooijen
Data Science Consultant

3. Dynniq cooperative research involvement
Initial Research phase
Cooperative and
Connected Architecture
COOP/CAD research
Deployment

6. Intelligent Control Systems..

7. 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

8. Validation of the model..
8

9. 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

10. Data Science capability
10

11. 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

12. 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

13. And fire up the recruitment process
13

14. Flow as a Service
14
Rapid prototyping

15. Rapidly build MVPs to test value
15

16. The use case: Flow as a Service
16
Goals
• Measuring real-time network performance
• Monitoring KPIs and detecting of anomalies
• Fully scalable

17. 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

18. What a traffic controller sends us…
18
Signal statuses
Sensors

19. Leading to the first insights
19
2de Paasdag Koningsdag
Hemelvaart

20. More interesting to link sensors and signals
20

21. To calculate KPIs: red light negation
21

22. And model traffic flow: queueing theory
22

23. Apply data science for anomaly detection
23

24. Top off with visualization
24

25. Design Cloud agnostic
25

26. 26
FlowSense Service Architecture
Presentation
Data Analytics
Application
services
IoT Data Management
Equipment, Sensors and
Actuators
Slice it!

27. We are hiring!
recruitment.nl@dynniq.com
Vacancy Data Scientist: https://goo.gl/zL7Bry
signal@godatadriven.com