Programma 16.30 Ontvangst 17.00 Robbrecht van Amerongen - Head of IoT, Conclusion Connect • Welkom en opvallendste zaken van het congres • Stand van zaken PaaS/SaaS, Digital Twin, Context IoT, Big Data en Machine Learning • IoT en Security • IoT-projecten: stand van zaken, opvallende voorbeelden en best practices • Waar staan de vendors/ platformleveranciers 18.00 Diner 18.45 Gertjan van het Hof - IoT Solutions Architect, Conclusion Connect • Platformen: Microsoft Azure IoT Reference Architecture en Google Cloud IoT • CrateDB • EdgeX Foundry en NetFoundry • Intel Video processing • Beacons • Security Maturity Model • Industrial Internet Consortium (IIC) 19:45 Pauze 20:00 Henk Jan van Wijk - IoT Solution Engineer, Conclusion Connect • Microsoft Azure Sphere (connected devices) • Low Power Connectivity (Thingstream) • Digital Twin • Anomaly detection at Intel (predict robots failure) 21.00 Afsluiting en borrel

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Who am I?
Gertjan van het Hof
IoT Solution Architect/Developer
IoT Enthusiast
Linkedin: linkedin.com/in/gertjanvanhethof
Twitter: @GertjanvhHof
Email: gertjan.van.het.hof@conclusion.nl
Phone: +31 (0)6 29540619
Internet of Things – HU event

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5. IoT Enables the Digital Feedback Loop
IoT enables the digital feedback loop that
connects:
• Customers
• Operations
• Products/Assets
• Employees
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6. BIG DATA
Data Lake (data at rest)
Streaming Data (data in transit)

7. IoT database workload
• Ingest many data points (millions) per seconde
• Structured or unstructured data (JSON sensor readings, metrics, logs, GPS,
etc.)
• Indexed by timestamp
• Queried in real-time
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9. CrateDB Comparison
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10. Comparison CrateDB vs InfluxDB
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11. Comparison
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12. CrateDB full managed and integrated in Azure
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13. Edge Solutions
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15. Time value curves for Edge information
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16. Benefits of Edge Computing
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EdgeX Foundry is an open source project that is building a common open platform
for IoT edge computing. The interoperable platform enables an ecosystem of plug-
and-play components that unifies the marketplace and accelerates the deployment
of IoT solutions across a wide variety of industrial and enterprise use cases.

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21. NetFoundry
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23. IoT Pattern
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31. iiconsortium best practices
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32. II Reference Architecture
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 Identification of stakeholders and their
business vision, values and objectives.
 How an IIoT system realizes the key
capabilities.
 Functional components of the IIoT system,
their structure and interrelation.
 technical representation of an IIoT system
and the technologies and system
components.

33. https://hub.iiconsortium.org
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34. Outcome of quick assessment
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Case: Container tracker indoor and outdoor
Complexity & Risks

35. Security Maturity Model (SMM)
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https://www.iiconsortium.org/pdf/SMM_Description_and_Intended_Use_2018-04-09.pdf

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Traditional Deep Learning
VS
Bound to pre-programmed detection
models.
Vision applications built with the
OpenCV library or OpenVX API.
Bound to pretrained deep
learning models.

39. Intel Deep Learning Toolkit
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https://software.intel.com/en-us/openvino-toolkit

41. CPU, GPU, FPGA, VPU, IPU
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Harness the performance of Intel®-based accelerators:
CPUs, GPUs, FPGAs, VPUs, and IPUs.

42. FPGA for AI / Deep Learning
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Field Programmable Gate Arrays
• No processor to run the software on
• Configure with Hardware Description Language (HDL)
• Configure it as multi-core processor

43. Video Processing Unit (VPU) - Neural Compute Engine
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45. Google IoT Architecture
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46. Google IoT Analytics
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48. Google Edge TPU development kit
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50. Recap
• IoT solution space is:
• changing continuously
• new players and leavers
• very heterogeneous
• no standardization, but some efforts arise (iiconsortium, edgexfoundry)
• lots of silo solutions
• dedicated, optimized solutions for a specific goal
• Azure, Amazon are prominent IoT solution building platforms
• Google IoT is raising
• Edge computing importance is understood
• Edge computing dedicated appliances arise
• Manageability and scaling of edges is still challenging
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Thanks for your
attention.