This document discusses Internet of Things (IOT) and big data. It outlines key topics including why big data is important, reference architectures for IOT, relevant technologies, and use cases. Example use cases described are applying real-time analytics to traffic data to predict congestion and sensor data from a football game to analyze player statistics and activity in real-time. The document also discusses technologies involved in complex event processing and architectures for IOT systems that integrate data collection and analytics.

2. Outline
• IOT
• Why Bigdata?
• A reference
Architecture
• Technologies
• Usecases
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http://www.flickr.com/photos/trainor/2902023575/, Licensed under CC

3. Internet of Things
• Currently physical world
and software worlds are
detached
• Internet of things
promises to bridge this
– It is about sensors and
actuators everywhere
– In your fridge, in your
blanket, in your chair, in
your carpet.. Yes even in
your socks
– Google IO pressure mats

4. If a tree falls in a
forest and no one
is around to hear
it, does it make a
sound?

5. A day in your life
 Think about a day in your life?
– What is the best road to take?
– Would there be any bad weather?
– How to invest my money?
– How is my health?
 There are many decisions that
you can do better if only you can
access the data and process
them.
http://www.flickr.com/photos/kcolwell/5
512461652/ CC licence

6. Analytics
• Useful information
about your
organization/
system
• E.g. Min, Max,
mean, historical
trends, grouping
etc.
• Technical term is
KPIs (Key
performance
Indicators )

7. Real Time Analytics
• Most first usecases were of
batch processing, which take
minutes if not hours to run
• Many insights you rather have
sooner
–
–
–
–
–
Tomorrows weather
Heart condition
Traffic congestion
Natural disaster
Stockmarket Crash

8. Making Sense of Data
• To know (what happened?)
– Basic analytics +
visualizations
(min, max, average, histogra
m, distributions … )
– Interactive drill down
• To explain (why)
– Data
mining, classifications, buildi
ng models, clustering
• To forecast
– Neural networks, decision

9. Data Processing Landscape

10. Complex Event Processing

11. Internet of Things Architecture

12. Usecase 1: Travel
• Collect traffic data +
transportation data from
sensors
• Build a model (e.g. Car
Following Models)
• Predict the traffic ..
Possibilities on congestion
• E.g. divert traffic, adjust
troll, adjust traffic lights

13. Usecase 2: Football Game
• Event Processing
challenge
• Real football
game, sensors in
player shoes + ball
• Events in 15k Hz
• Event format
– Sensor
ID, TS, x, y, z, v, a
• Queries
–
–
–
–
Running Stats
Ball Possession
Heat Map of Activity
Shots at Goal

14. Conclusions
•
•
•
•
•
IOT and Bigdata
Case for analytics
Data processing architecture
Overall architecture
Conclusion

15. Questions?