As smartphones and wearables are packed with sensors and computing power, they introduce a new type of data: sensor data that contains realtime and accurate observations of the world around a mobile user.
With the Internet of Everything booming, our homes, cars and phones are increasingly interconnected, as they become valuable channels to interact with the world around us in new and more intelligent ways.
Our increasingly sensor equipped world brings us the opportunity of a growing level of ambient intelligence that is capable of understanding and predicting human behavior, emotions and context, so that mobile applications can engage with us in a proactive and hyperpersonalized manner.
3. US$ 19
Trillion in global GDP
due to the Internet of
Everything by 2020
Cisco & GE
US$ 300
Billion incremental
revenue by 2020
Gartner
40.9
billion
connected devices
by 2020
155
million
connected cars by
2020
100
million
connected light bulbs
by 2020
+1
trillion
connected
sensors
by 2020
2.5
billion
smartphones
by 2020
$12
billion
wearable market size
by 2020
4. about smart devices and dumb experiences
how smart devices struggle to bridge the intelligence expectation gap
5. Machines will need to be cognitive if
consumers want personalized experiences
Gartner, Nov 2013; Four Phases of Cognizant Computing
Sync Me See Me Know Me Be Me
6. Your smartphone as a first generation sensor
hub and smart agent
CPU
Growing processing
power
Sensor
Pervasive sensing
capabilities
Connectivity
Interconnected edge
computing capability
7. Two sides to the data story
Declared
Observed
Content
Structured, explicit,
self-declared, and static
Context
Unstructured, time-series,
observed, and dynamic
8. 2000 - verbal 2010 - nonverbal
explicit sending of content implicit sensing of context
9. sensor data: source for context-awareness
with this new source of data, new levels of intelligence are presented
10. situational
awareness goes beyond
simple geo-fencing. In the
background, pervasive sensing,
learning and classifying the
situation a user is in.
behavioral
profiling is based on real and
observed behavior, not on
snapshots of declared data, e.g.
Likes or Search queries. These
personas are the most accurate.
Sleeping Alone Driving Stress …
Arriving at Home About to go to Work …
EVENTS
MOMENTS
Pet Owner AthletePROFILES Workaholic
Aggressive Driver Unique User
…
…
11. A user accepting sensor data is defined by
the expected valueExpected
Value
User
Acceptance
Accelerometer
Gyroscope
In-App Usage
Wi-Fi
GPS/Location
Light Sensor
Browsing
History
Calendar
Messages
GSR/HR
Microphone
Camera
12. Tomorrow, everything becomes a channel
Relevant
Engaging only at the
right moment
Glanceable
Delivering value in
milliseconds
Personal
Approaching on the
right channel
13. The channel defines tolerance for mistakes
Tolerance
Channel
Wearabl
e
Push
E-Mail
Social
Network
Implants
SMS
Car
Media
recommendations
14. some practical examples of context awareness
Start delivering a more convenient life through context aware intelligence
18. Online advertising: based on explicit
signals, expressed by humans
Mobile advertising: based on implicit
signals, learned by machines
CLICKS SENSORS
Richer, real-time and fluid
personas
Clicks, page views, and
audience segments
Turning advertising in a meaningful and
helpful experience on mobile
19. the road ahead to the ultimate personalization
We’re only at the beginning of this huge evolutionary step. Many challenges ahead.
20. The evolution of personalization
Transactional
experiences
Social
experiences
Context-aware
experiences
Sentient
experiences
Data Manual Social Contextual Behavioral
Sourcing Static Explicit (crowd) Implicit (sensed) Pervasive
Style Broadcast Conversational Adaptive Cognitive
Intelligence Expert systems Deterministic Probabilistic AGI
Timing Responsive Real time Semantic time Predictive
Challenge Easy to use
interface
Keep a high user
engagement
Identify the right
moment
Cross-channel &
non linear
Awareness Role Profile Situation Self
1980+ 2000+ 2015+ 2025+
21. Artificial Intelligence Affective Computing
Rethinking the ambient intelligence paradigm
a pervasive computing principle that is sensitive and responsive