Innovatie | De geheimen van een succesvolle IoT implementatie Internet of Things raakt ons allemaal. Elk bedrijf in iedere branche en alle personen. De voorspelling is dat in 2020 meer dan 30 miljard apparaten (de ‘Things’) zijn aangesloten op het internet. Dat biedt volop kansen voor bedrijven en gaat bedrijven verder transformeren. Vroeg of laat krijgt elke organisatie te maken met een IoT implementatie, vandaag de dag weten veel bedrijven echter nog niet wat ze met IoT aan moeten. Hoe kom je tot een succesvolle IoT strategie? Wat komt allemaal kijken bij een IoT implementatie? Is mijn organisatie voorbereid op IoT? Welke valkuilen zijn er? Allemaal relevante vragen. Tijdens deze bijeenkomst wordt ingegaan op aspecten die van belang zijn bij een IoT implementatie, en voor welke uitdagingen bedrijven staan die met IoT aan de slag gaan. Tevens kijken we naar de relatie tussen IoT en artifical intelligence. Een interactieve bijeenkomst waar ruimte is voor discussie en het delen van ervaringen.

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The secrets of a successful
IoT implementation
Johan van Rooij + Sam Straube
7 May 2019
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• Introduction
• Trends and developments
(setting the scene)
• Case: Boon Edam
• The secrets of a successful IoT
implementation
• IoT and Data Science
• Q&A
Agenda
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Introduction
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Sam Straube
Data Architect @ Valid
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• A long long time ago I started working within
the data domain.
• From applications, to databases to data
warehouses
• In the last 10 years also privacy and security
Channelinx Inc
Acquion
https://www.linkedin.com/in/sam-straube-365b4612

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Dr. Johan van Rooij
Senior Data Scientist @ Valid
• PhD + MSc in computer science, MSc mathematics
• 7 year senior consultant ‘quantitative methods’ in
transportation and manufacturing
− ProRail, NS, ASML, Oceaneering, VolkerRail, many more…
− Planning optimisation, machine learning/deep learning,
building a search engine, teaching data science
− Many ‘innovative/risky’ projects
• Winner ‘Hendrik Lorentz Nederlandse Data Science
Prijs’ (2018)
• Assistant Professor @ Utrecht University
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Trends and developments
(setting the scene)
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Data-gedreven wereld
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Data-gedreven bedrijf
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OPERATIONS
PEOPLE
PRODUCTSCUSTOMERS
INTELLIGENCE
DATA

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• Privacy regulations
• Security
• Persistent silo thinking
• Lack of data integrity
• Having the right skills
• Lack of capacity to build custom solutions
• Identifying the right technology
Uitdagingen om data-gedreven te worden
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Data Platform
Moderne Data Platform
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Case: Boon Edam
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Praktijkimplementatie

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De context
Powered by Boon Edam
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Waar zijn devices?
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Dashboard: inzichten en acties
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Lessons Learned
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• Minimal Viable product
• Data Quality
• Data History
• Legacy Software
• User Experience
• APIs

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Microsoft is simplifying IoT
The secrets of a successful IoT implementation 7-5-2019
• Easier to build secure, scalable solutions from device to cloud
• Easier to provision devices at scale
• Easier to secure devices at scale
• Easier to manage devices at scale
• Easier to find insights from your IoT devices
• Easier to run cloud services on devices
• Easier to benefit from IoT

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Intelligent Cloud
Azure IoT Central
Azure IoT Solution Accelerators
Azure IoT Platform Services
Azure Digital Twin
Intelligent Edge
Azure IoT Edge
Device Catalog
Azure Sphere
Microsoft is simplifying IoT

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Microsoft is simplifying IoT
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Predictive Maintenance
Azure IoT Solution Accelerators

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Microsoft is simplifying IoT
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Azure IoT Solution Accelerators
Predictive Maintenance

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Microsoft is simplifying IoT
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Azure IoT Solution Accelerators
Predictive Maintenance

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The secrets of a successful IoT implementation
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Strategy
Your primary concern
IoT
Hardware & Infrastructure
Data platform
Insights
& Actions
Scalable Solutions Experiment/Pilot
New Business Models Applications (ideas)

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It all starts with the right strategy
This is the hardest part, because it needs to fit your business exactly
Components of an IoT application:
1. What to measure?
2. Connectivity
3. Data & Insights
4. Actions
5. Security
6. Monitoring & Support
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Questions:
• Where in your business can
measurements result in added value?
• Alternative: where is additional insight
useful?
• Guiding principles: efficiency, quality,
user experience.
• Most do not start from new business
models. Let them be your point on the
horizon.
strongly
connected
‘Why’ and
‘What?’
Technical
‘How?’
Strategy
Your primary concern

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What to measure?
What sensors are there?
1. Temperature
2. Weight
3. Pressure
4. Level sensors (lasers)
5. Speed / acceleration
6. Location (GPS)
7. Gas/Chemical sensors
8. Infrared sensors
9. Camera’s
10. Other optical sensors
11. Acoustic sensors
12. Vibration sensors
13. Humidity sensors
14. Proximity sensors
15. Gyroscope
16. …
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IoT
Hardware & Infrastructure

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Where do others start?
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Scalable Solutions Experiment/Pilot
New Business Models Applications (ideas)
Strategy
Components of an IoT application:
1. What to measure?
2. Connectivity
3. Data & Insights
4. Actions
5. Security
6. Monitoring & Support

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Security
Vital part of any IoT solution and strategy
This is where things can go painfully wrong
• Devices
− Hardware tampering/spoofing
− Remote hacking – your device in a botnet?
− Others tapping into your sensors?
− Security updates?
• Connections
• Data storage & access control
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How to do things right:
• Use standardised ‘secure by design’
solution elements.
• Adhere to reference architectures.

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Security
Standardised solutions are emerging: security by design
• Azure Sphere
• Azure IoT Hub
• Azure IoT Edge
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Security a problem?
What do first movers use?
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IoT and Data Science
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Let us focus on one part for a moment…
36 Titel presentatie 4-7-2018
Insights
& Actions

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Data Science….. Or Advanced Analytics?
Turning data into actions…
First four IoT
strategy
components:
1. What to
measure?
2. Connectivity
3. Data &
Insights
4. Actions

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Data Science…..
38 Titel presentatie 4-7-2018
Computing
skills
Math &
Statistical
knowledge
Domain
expertise

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Data Science and AI
39 Titel presentatie 4-7-2018
Data Science
Computing
skills
Math &
Statistical
knowledge
Domain
expertise
The math & statistics is what
is added to our conversation

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Descriptive/Diagnostic Analytics For IoT
What happened, and why? Or with IoT: what is going on?
• Remote Monitoring
− GPS in transportation/delivery: who is where?
− Smart soccer stadium: current noise levels.
• Usage Statistics.
− Garbage containers: current fill level?
− Connected vending machines: inventory?
− Do my delivery vehicles follow smart routes?
And why too late? Traffic, or late departure?
• Process Mining.
− How do people/consumers use my device?
− Where are process bottlenecks?
• Process Quality Properties?
− Find statistical correlations between sensor measurements and quality.
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Predictive Analytics for IoT
What will happen?
• Predictive Maintenace
− Airplane engines (rolls royce).
• Demand forecasting.
− Connected containers.
− Connected vending machines.
• Delay forecasting.
− Will my delivery be late?
• Diagnostics
− Connected healthcare.
− Semi-automated quality control.
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0%
20%
40%
60%
80%
100%
120%
140%
ma di wo do vr za zo
Fill level container
Volume Full!

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Prescriptive Analytics for IoT
What should I do?
• Prescriptive analytics is about optimising a (planning) puzzle.
− IoT can provide data inputs here.
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• What taxi should go to the new customer?
• Planning of maintenance, using predictive
maintenance.
• Resupply planning, using demand
forecasting.
• Automatic replanning, using delay
forecasting.

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Data Science/AI beyond analytics and IoT
Prebuild or Custom Data Science/AI models
• IoT often an enabler for AI or an alternative interface.
• Valid Hello
− Face recognition on automated BHV board.
• Full backend in the cloud.
− Smart speakers
− Smart thermostat
− Baby monitor / Al
− Talking dolls
− Etc…
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Strategy
Your primary concern
IoT
Hardware & Infrastructure
Data platform
Insights
& Actions
Scalable Solutions Experiment/Pilot
New Business Models Applications (ideas)

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Q & A
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