Slides from "Hacking Health" workshop: HIP613: IBM Bluemix For Healthcare (Part 1) Feb 23rd, 2017

1. Internet of Things
And other interesting technology trends
Jim Boland
Software Architect
Cognos Analytics
IBM Canada Ltd
@neoslimjimhttps://www.slideshare.net/JimBoland3/hacking-health-iot-analytics-and-other-trends

2. Trends in computing
• Wearable technology
• iBeacons and micro-location context
• Contextual and anticipatory computing
• IoT, big data and analytics
• Wrap up: how all this is about plugging us into the IoT!
Mainframe Desktop PC Laptop Mobile
(smartPhone/tablet)
Trends: Moore's law, computing distribution, personal/specialized, mobility
...

3. Wearables

4. vandrico.com/wearables
• Head: 63. 84
• Neck: 12 12
• Chest: 10 21
• Torso: 19 27
• Arm: 8 11
• Wrist: 119 213
• Hand: 5 8
• Fingers: 10 11
• Legs: 9 13
• Feet: 9 12
2014 2017

5. Wearables
• Wearables complement (rather than replace) smartPhones
• Wearable technology is about the more seamless integration of tech:
• Notifications - SmartWatches, SmartGlasses
• Sensors - Fitness/health devices
• Remotes and Identification
• Virtual Assistants

6. SmartWatch & Glasses
• While much of the hype is with these, not the early
success...

7. Fitness/Health
• Fitness/health devices the early leader
in wearables
• Sensors to monitor heart rate, activity,
sleep, etc.
• Nike abandoned the Fuelband

8. Remotes
• Want an interface like Minority Report and Tony
Stark?
• Map physical gestures to intent, from:
• Fingers - Fin ring
• Arm - Myo ( Thalmic Labs)
• Wrist - Glance (kiwi wearables)

9. Identification
Wearables represent your identity for:
• Payment systems - Apple Watch and ApplePay
• Application/device - vivalnk tatoos
• Physical security - Kevo locks
• Contextual/anticipatory computing
As well, wearable biometric sensors create ways for establishing identity:
• Touch ID - Fingerprint scanners
• Nymi - heartbeat signature

10. Smart Shoes?
• Vibration in respective shoe to indicate right/left turn

11. Summary on wearables
• Overall themes:
• Collect sensor data to gain context of the user
• Unobtrusive means to feed information back to the user
• Represent the user remotely (intent and identity)
• There are DYI prototyping kits out there (e.g. MbientLab’s Metawear)
• There are technical challenges still: security and power

12. iBeacon
• Conceptually similar to a GPS satellite, but at a micro-location (and often indoors) scale
• In a store with a beacon in each department, the phone app knows where it is, by which
beacon(s) it sees
• iBeacons don't track/collect data from phones. Without an installed app, there is no interaction
with the phone/beacon
iBeacons
"I'm
beacon
#53"

13. Micro-location
• Emergency ward patient tracking
• Contextual retail assistance
• Indoor mapping/directions
• Home automation
• Tealeaf/Google Analytics style analytics of in-store foot traffic
• Micro-location based geo-fencing/context

14. Contextual Computing
Better understand the context of a user request, in terms of:
• Context from device sensors
• Context from user interaction history
• Context from user profile/social graph
Providing context of who, where, when and the previous
conversation

15. Siri example
Next request in context
of first

16. Affective Computing
• Special case: using context of a user, to understand
how people feel and emotions (and adapting
responses as a result)
• With the pervasive sensors of smartphones and
wearables, there is a new source of information

17. Anticipatory Computing
• Contextual computing: context is used to
interpret a user request
• Anticipatory computing: monitors context and
anticipates user's need without an explicit
request

18. "Invisible buttons"
• Amber Case [ESRI/Geoloqi] coined the term "invisible buttons"
• Concept: instead of touching a button on a smartphone as the
trigger for an action, the user becomes the trigger by entering a
geofenced area
• Ultimate example of the User Interface getting out of the way
• Example: my house! (Kevo lock, 21 iBeacons, Hue lights, airPlay
speakers)

19. IoT and Big Data
• IoT = devices sending and receiving data
• IoT = LOTS of devices, sending LOTS of data, ALL the time
• IoT = Big Data!
1001010
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20. Making sense of big data
• How do you get value from all that data?
• Analytics can help!

21. Data in motion
• Streaming analytics
• Scalable solutions to tame the firehose
• Latency sensitive response
• Realtime feedback
• Moving averages
• Identify out of range values
• Smooth out jittery sensor data

22. Data at Rest
• Batch analytics
• Historical analysis
• Trends
• Outliers
• Correlations in the data
• Predictive analytics
• Stream analytics, batch analytics - both have a role in IoT!
Database

23. Example IoT Architecture
Local Hub/
IoT Gateway
Device
Sensor
Sensor
Device
Bluemix
- Streaming Analytics
- Batch Analytics
- Other business logic
MQTT
BLE
WIFI
ZigBee

24. Analytics in bluemix
• Trying analytics out!
• Freemium account:
https://console.ng.bluemix.net

25. Watson Analytics
• Cognitive computing - machines doing the analysis
• Freemium account:
www.ibm.com/analytics/watson-analytics/

26. Node-Red
• https://nodered.org/
• Run locally (e.g. Rpi) or cloud (e.g Bluemix)