Why we do not want to build intelligent mobile applications

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Why we do not want to build intelligent mobile
applications
Szymon Bobek
Institute of Applied Computer Science
AGH University of Science and Technology
http://geist.agh.edu.pl
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Szymon Bobek (AGH-UST)
Mobile Trends 2014
17 January 2014
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Outline I
1
Introduction
2
General issues
3
Engineering issues
4
Social and philosophical issues
5
Summary
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Presentation Outline
1
Introduction
What is (Artificial) Intelligence
What are CAS
How to build CAS
2
General issues
3
Engineering issues
4
5
Summary
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What is intelligence
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Can submarine swim?
Artificial Intelligence
A question ”Can machine
think?” is similar to a
question ”Can submarine
swim?”.
Artificial intelligence is just a
simulation of real intelligence,
hence it requires appropriate
model.
Every model requires
constraints. The looser
constraints, the more difficult
the ”simulation”.
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Outline
1
Introduction
What are CAS
How to build CAS
2
General issues
3
Engineering issues
Gathering context
Modelling context
Processing context
4
Semantics vs. context
Usability, intelligibility
Privacy
5
Summary
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17 January 2014
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In Theory
Context
Aware
Systems
• Where you are, who you are with, what resources are nearby
(Schillit)
• Any informaiton that can be used to characterize the situation
of an entity (Dey)
• Individuality, activity, location, time, relations (Zimmerman)
• Set of variables that may be of interest for an agent and that
influence its actions (Bolchini)
• Artificial intelligence methods
• Intelligent homes, intelligent cars, robotics
• Ambient intelligence, pervasive environments, ubiquitous
computing
• Mobile computing (location aware mobile applicaitons)
• Intelligent software (contextual advertising, etc.)
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In Practice
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In Practice
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In Practice
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In Practice
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In Practice
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In Practice
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Context is not only a location
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Context is not only a location
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Outline
1
Introduction
What are CAS
How to build CAS
2
General issues
3
Engineering issues
Gathering context
Modelling context
Processing context
4
Privacy
5
Summary
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Acquire, represent, use
Collect
Interpret,
Represent,
Model
Process,
Use
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1
Introduction
2
General issues
3
Engineering issues
4
5
Summary
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applications?
Because…
However…
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applications?
Because…
However…
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applications?
Because…
However…
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applications?
Because…
However…
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applications?
Because…
However…
No tools
Well… 
No skills
EIS @ AGH
Not possible
Jakdojade.pl, Google
now, Google car
No point
We create the
„point”
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1
Introduction
2
General issues
3
Engineering issues
Gathering context
Modelling context
Processing context
4
5
Summary
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17 January 2014
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Android API and SensorManager
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AWARE
All in one solution
24 context providers implemented
Open source http://www.awareframework.com client and server solution
Plug-ins philosophy (so far about 15 plug-ins)
Service oriented architecture
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17 January 2014
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AWARE
All in one solution
24 context providers implemented
Open source http://www.awareframework.com client and server solution
Plug-ins philosophy (so far about 15 plug-ins)
Service oriented architecture
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17 January 2014
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Estimote and Gimbal
Microlocation with beacons
Based on Bluetooth Low
Energy (BLE technology)
Opposite to GPS it allows
detecting device position
within a building or a room
Android and iOS API
Preorder for 99$
Mobile Trends 2014
17 January 2014
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Estimote and Gimbal
Microlocation with beacons
Based on Bluetooth Low
Energy (BLE technology)
Opposite to GPS it allows
detecting device position
within a building or a room
Android and iOS API
Preorder for 99$
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It looks awesome, but...
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Outline
1
Introduction
What are CAS
How to build CAS
2
General issues
3
Engineering issues
Gathering context
Modelling context
Processing context
4
Privacy
5
Summary
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17 January 2014
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Why bother with models
For the same reason we...
...put data into database,
...use UML,
...design and plan things.
So we are able to...
...add structure to data
...add semantics to meaningless data
...enhance/allow/prepare data for processing
...allow data exchange and system interoperability
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Available modelling approaches
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Outline
1
Introduction
What are CAS
How to build CAS
2
General issues
3
Engineering issues
Gathering context
Modelling context
Processing context
4
Privacy
5
Summary
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Mobile Trends 2014
17 January 2014
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Android API
Geolocation
Entering the geofence
Entering and dwelling for
some period of time
Exiting the geofence
ActivityRecognition
The device is in a vehicle
The device is on a bicycle
The device is on a user who
is walking or running.
The device is still.
The device angle relative to
gravity changed significantly.
Unable to detect the current
activity.
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Machine Learning
(Not) a rocket science
BigData ;)
Weka, Matlab, Python for rapid
prototyping
JavaML for development
Examples
Clustering - for discovering
patterns, groups
Probabilistic graphical models for handling uncertainty,
predicting
Regression - for discovering
trends, patterns
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AWARE Framework
Framework support
Sensing
Processing (offline via
Context Providers, or on
the server side)
Sharing and
communicating (via
MQTT messages)
Binding with other
applications (via Context
Observers and Context
Broadcasters)
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1
Introduction
2
General issues
3
Engineering issues
4
Privacy
5
Summary
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Context vs. semantics
Fall detection
The context is that a person is laying on the floor
The semantic explains what does it mean
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Context vs. semantics
Fall detection
The context is that a person is laying on the floor
The semantic explains what does it mean
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Outline
1
Introduction
What are CAS
How to build CAS
2
General issues
3
Engineering issues
Gathering context
Modelling context
Processing context
4
Privacy
5
Summary
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Mobile Trends 2014
17 January 2014
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Should user understand how system works?
Intelligibility
Ability of the system to explain how it works. Capability of being understood.
The Clippy Microsoft Agent has mostly been
abandoned because it made erroneous suggestions
with no explanation of why these suggestions were
being made
Amazon.com added a link under a user’s
recommendations: ”Why is this recommended for
you?”
Intelligibility improves usability, however only
when a system is certain its decisions
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Outline
1
Introduction
What are CAS
How to build CAS
2
General issues
3
Engineering issues
Gathering context
Modelling context
Processing context
4
Privacy
5
Summary
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17 January 2014
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Mind the... user
Locally or in a cloud
People do not feel comfortable sharing their location, and other personal
data.
Cloud sounds good only to developers – users prefer Dropbox, GoogleDrive.
Processing large amounts of information locally costs energy
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1
Introduction
2
General issues
3
Engineering issues
4
5
Summary
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In one word
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In one word
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In one word
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In one word
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Challenges
Under research
Energy consumption
Intelligibility and usability
Processing context, adaptability
Methodologies for building CAS, modelling techniques and procedures
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Thank you!
Szymon Bobek
Institute of Applied Computer Science
AGH University of Science and Technology
17 January 2014
http://geist.agh.edu.pl
http://wownow.pl
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17 January 2014
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Why we do not want to build intelligent mobile applications

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