An introduction of what The Internet of Things is based on an overview of our society, how an implementation of The Internet of Things looks like from a bird eye view and some pitfalls and challenges that come with IoT. This presentation was given on several occasions to C-Level management, lawyers, students, techies,...

1. Internet of Things
Myths, Pitfalls & Challenges
Sven Beauprez - IoTBE

2. • Co-Founder & Vice-Chairman of IoT BE (2013 - … )
- http://www.iotbe.org
- http://www.meetup.com/iot_be/
• Enterprise Solution Architect & IoT Architect
• Entrepreneur & Evangelist of cutting edge internet technologies
• Steering member of JavaPolis/Devoxx
(2002 – 2009)
• Keep in touch
- sven.beauprez@iotbe.org
- https://www.linkedin.com/in/svenbeauprez
- @SvenBeauprez and @iot_be
Who am I?

3. IoTBE vzw
IoT Belgium
vzw
Industry &
Government
Technology &
Community
Education &
Training
Research &
Development

4. IoTBE vzw
IoT Belgium
vzw
Industry &
Government
Technology &
Community
Education &
Training
Research &
Development
Smart Factories Smart Infrastructure Smart Buildings Smart Retail

5. IoT: 50 Bilion connected devices by 2020

6. IoT: 50 Bilion connected devices by 2020

7. IoT: 50 Bilion connected devices by 2020
But what is IoT?

8. Based on the excellent infographic of “Libelium Smart World”
http://images.libelium.es/content/applications/libelium_smart_world_infographic_big.png

9. Wearables
• Track activity such as
steps taken, stairs
taken, distance
walked or run,…
• Heart rate monitoring
with feedback about
averages, time in
hearth rate zones, …
• Location monitoring

10. Wearables are not
a recent development
https://hbr.org/2013/09/wearables-in-the-workplace

13. Quantified Self
• Input monitoring, such as
food consumption, air
quality,…
• Monitor personal state, such
as mood, blood pressure,
blood oxygen levels,…
• Measure mental and
physical performance, such
as activity, calorie
consumption,…
• Get the right help at the
right time, eg. drone with
on board defibrillator

16. Smart Building
(home & office)
• Control (domestic) activities
such as houseplant/yard
watering, pet feeding, changing
ambience scenes (lighting,
audio,…), use of domestic robots
(eg. to clean)
• Intelligent HVAC (Heating,
Ventilation and Air
Conditioning) triggered based
on presence or from over the
internet
• Intelligent security system that
detects type of presence (home
owner vs intruder) and that can
interact with domotica systems
and medical alarm systems

17. The Edge - Amsterdam
• Lighting and HVAC is connected to
the IT system
• Employees get local control
• Facility managers get real time usage
information to optimise lighting,
cleaning, heating, airconditioning,…
• Extendible with other sensors

20. Smart Cities
• Smart Lighting: adapt strength
of lights to actual needs
• Smart Roads: show signs
depending on weather condition
or events such as accidents
• Monitor traffic to avoid
congestion and redirect traffic
• Check air quality and reroute
traffic depending on air
pollution
• Monitor available parking
spaces and direct traffic towards
free space
• Detect levels of trash in bins to
optimise collection routes

24. Smart Retail
• Inform about products
based on customer health
(eg. allergies), preferences,
habits,… cfr. quantified
self
• Locate desired products
within the store/warehouse
• Self service shopping
(Digital Mall) without
presence of staff
• Monitor available parking
spaces and direct traffic
towards free space

28. Smart Farms
• Remotely monitor cattle
temperature to detect illnesses
sooner
• Cough monitor for pigs to detect
and treat respiratory problems
quickly and efficiently, resulting
in decreased antibiotic use
• Monitor cows to detect calving
process starts
• Monitor soil conditions via mesh
network to report on soil mosture,
temperature and conductivity
• Use drones for visual inspections
of crops and plantations to detect
drought and/or anomalies and
map them

29. Complete aerial
imaging solution
specifically designed
for surveyors and
geospatial
professionals

32. IoT Architecture : World Forum Reference Model

33. Actuators and sensors
send and receive data via
1. Physical devices
(the “Edge”)
IoT Architecture : World Forum Reference Model

34. Actuators and sensors
send and receive data via
a network towards
1. Physical devices
(the “Edge”)
2. Connectivity
IoT Architecture : World Forum Reference Model

35. Actuators and sensors
send and receive data via
a network towards
gateways which filters and
aggregates it before
1. Physical devices
(the “Edge”)
2. Connectivity
3. Edge Computing
(in the “Fog”)
IoT Architecture : World Forum Reference Model

36. Actuators and sensors
send and receive data via
a network towards
gateways which filters and
aggregates it before
sending or receiving
it via the internet to/from
1. Physical devices
(the “Edge”)
2. Connectivity
3. Edge Computing
(in the “Fog”)
IoT Architecture : World Forum Reference Model

37. Actuators and sensors
send and receive data via
a network towards
gateways which filters and
aggregates it before
sending or receiving
it via the internet to/from
(big) data stores from which
data can be retrieved or stored
1. Physical devices
(the “Edge”)
2. Connectivity
3. Edge Computing
(in the “Fog”)
4. Data Accumulation
5. Data Abstraction
(in the “Cloud”)
IoT Architecture : World Forum Reference Model

38. Actuators and sensors
send and receive data via
a network towards
gateways which filters and
aggregates it before
sending or receiving
it via the internet to/from
(big) data stores from which
data can be retrieved or stored
via the internet
1. Physical devices
(the “Edge”)
2. Connectivity
3. Edge Computing
(in the “Fog”)
4. Data Accumulation
5. Data Abstraction
(in the “Cloud”)
IoT Architecture : World Forum Reference Model

39. Actuators and sensors
send and receive data via
a network towards
gateways which filters and
aggregates it before
sending or receiving
it via the internet to/from
(big) data stores from which
data can be retrieved or stored
via the internet
by devices where it is
processed and visualised
1. Physical devices
(the “Edge”)
2. Connectivity
3. Edge Computing
(in the “Fog”)
4. Data Accumulation
5. Data Abstraction
(in the “Cloud”)
6. Application
IoT Architecture : World Forum Reference Model

40. Actuators and sensors
send and receive data via
a network towards
gateways which filters and
aggregates it before
sending or receiving
it via the internet to/from
(big) data stores from which
data can be retrieved or stored
via the internet
by devices where it is
processed and visualised
so people can act upon it
1. Physical devices
(the “Edge”)
2. Connectivity
3. Edge Computing
(in the “Fog”)
4. Data Accumulation
5. Data Abstraction
(in the “Cloud”)
6. Application
7. Collaboration
and Processes
IoT Architecture : World Forum Reference Model

41. Internet of Things vs Internet of Everything

42. Social Media
Linked Open Data
Processes
Internet of Things vs Internet of Everything

44. Social Media
Linked Open Data
Processes
Internet of Things vs Internet of Everything

45. Ethics
Pitfalls & Challenges
Standards Complexity
SecurityPrivacy
Big Data

46. Physical devices
(the “Edge”)
• Challenge
- Huge amount of sensor data
- Latency towards the cloud
- Bandwith
- Always ‘on’
Big Data Challenge

47. Physical devices
(the “Edge”)
Edge Computing
(in the “Fog”)
• Challenge
- Huge amount of sensor data
- Latency towards the cloud
- Bandwith
- Always ‘on’
• Solution
- Aggregate and filter data before
sending to the cloud
- Localise computing as close as
possible to physical devices
Big Data Challenge

48. Standardisation Challenge
• Challenge
- Each vendors has his own ‘standards’
- No ‘one size fits all’ solution
(eg. range vs power consumption)
- Closed APIs
Physical devices
(the “Edge”)
Edge Computing
(in the “Fog”)

49. Standardisation Challenge
• Challenge
- Each vendors has his own ‘standards’
- No ‘one size fits all’ solution
(eg. range vs power consumption)
- Closed APIs
• Solution
- Minimise different type of
connections on the edge/fog
- Use IEEE 802.15.x standards
(eg. zigbee)
- Use Bluetooth (Low Energy)
- Use Open APIs as much as possible
(may become de facto standards)
Physical devices
(the “Edge”)
Edge Computing
(in the “Fog”)

50. Complexity Challenge
• Challenge
- Hundreds to millions of devices
- Many different type of integrations
- Different kind of expertise needed
(HW, Networking, SW, Security, Big
Data, Data Science,… )
- Maintainability
Social
Linked Open
Data
Process

51. Complexity Challenge
• Challenge
- Hundreds to millions of devices
- Many different type of integrations
- Different kind of expertise needed
(HW, Networking, SW, Security, Big
Data, Data Science,… )
- Maintainability
• Solution
- Focus on part of the problem
- Coöperate and seek the right
partners
(this is not like building a website!)
Social
Linked Open
Data
Process

52. Privacy Challenge
• Challenge
- Who owns ‘personal’ data?
- Can you remove your own data?
- ‘If the product is for free,
then you are the product’
Sensor Data
Tracking Data
Social Media
User Interfaces

53. Privacy Challenge
• Challenge
- Who owns ‘personal’ data?
- Can you remove your own data?
- ‘If the product is for free,
then you are the product’
• Solution
- International regulations are
needed, not only in Europe
- If data is important for revenue
stream, it should be anonymised as
much as possible
(eg. by using segmentation)
Sensor Data
Tracking Data
Social Media
User Interfaces

54. Security Challenge
• Challenge
- More connections to the internet
mean more opportunities to hack
(eg. zero-day exploits)
- In the field HW and SW (edge & fog)
protection
- Difficult to upgrade the edge and the
fog
Social
Linked Open
Data
Process

55. Security Challenge
• Challenge
- More connections to the internet
mean more opportunities to hack
(eg. zero-day exploits)
- In the field HW and SW (edge & fog)
protection
- Difficult to upgrade the edge and the
fog
• Solution
- Closely follow up latest research on
security
- Build HW & SW with security in
mind (not added afterwards)
- Monitor the IoT infrastructure E2E
Social
Linked Open
Data
Process

56. • Challenge
- What happens when devices make
the decisions instead of humans?
Ethical Dilemma’s

57. • Challenge
- What happens when devices make
the decisions instead of humans?
• Example
- Who will get injured/killed by the
self driving car?
Ethical Dilemma’s

58. • Challenge
- What happens when devices make
the decisions instead of humans?
• Example
- Who will get injured/killed by the
self driving car?
• Solution
- The car must be programmed to
kill
Ethical Dilemma’s

59. Ethical Dilemma’s
A B
C
• Challenge
- What happens when devices make
the decisions instead of humans?
• Example
- Who will get injured/killed by the
self driving car?
- Will the owner accept the fact that
the car ‘chooses’ to kill him?
• Solution
- The car must be programmed to
kill
- But who?

60. IoT: 50 Bilion connected devices by 2020

61. Q&A