Transcript PresentationPackage

UbiPhone:Human-Centered
Ubiquitous Phone System
SCENE
2011.04.27
JS Lee
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Contents
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Introduction
A human-centered personal assistant service must discover how best to
reach a contact at any given moment, rather than simply asking users to
choose from a list of phone numbers.
It studies smart phones’ potential to become intelligent personal digital
assistants.
UbiPhone automatically connects using the most appropriate phone system
based on current context information, such as caller and contact’s location,
presence status, network status, available phone systems, calendars, and
social relationships.
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UbiPhone Features
Ubiphone adopts context and social models to develop intelligent humancentered services.
Ubiphone’s special features are
UbiCall, AnyCall,
and an
emergency contact service.
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UbiPhone Features - UbiCall
UbiCall provides a novel human-centered phone call service. Users who want
to call a friend from their contact list simply click on their friend’s name.
UbiCall automatically selects the most appropriate phone number
(home, office, or cell phone, VoIP, or IM) and network interface to use, either
cellular (UMTS/HSDPA or GPRS/EDGE/GSM) or wireless (WiFi, Bluetooth, or
WiMax), based on context information such as reachability, call rate, and
user preference.
Additionally, the service provides intelligent feedback when contacts
aren’t available, such as when to call back according to their calendars, or
whether to re-dial automatically when contacts become available.
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UbiPhone Features - AnyCall
AnyCall is similar to the anycast service in IP networks, enabling users to
call the most appropriate friend within a group.
Consider an emergency scenario in which a user must call his family to
inform them about an accident. In this situation, anyone from the caller’s
family list can help him. AnyCall will connect the caller to the first available
family member on the list with a single click on the family group’s name.
AnyCall also considers other context based on the caller’s configuration.
For example, the system could call the available friend with the cheapest
call rate.
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UbiPhone Features – An Emergency Contact Service
In emergency cases, an emergency contact service could connect the caller
to a third party from the contact’s phone number list, or to a phone at a
location where the contact can be reached immediately.
The service uses social, calendar, and location information to determine the
most appropriate third party.
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Architecture
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Context Digest Model
The context digest model adopts an ontology as the underlying technique
to manage context.
The context digest model acquires context using a context-acquisition
module from various agents and smart devices.
The context-management server classifies, transforms, and stores this data,
which it classifies as static, dynamic, statistical, or social.
The static context, such as users’ profiles and preferences, rarely, if ever, changes.
The dynamic context, such as users’ presence status and locations, updates the
context-management server frequently, and responds to the smart phone immediately.
The statistical context, such as phone call logs, location logs and event logs, is derived
from statistics of historic logs.
The social context provides a social relationship model generated from social activities
between two individuals, such as phone calls, emails, or instant messages.
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Social Network Model
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Implemetation
It comprised several servers and four users using Dopod PDA phones
equipped with WiFi, GSM, GPS, and RFID modules. We installed RFID readers
in rooms to collect each user’s location log.
The users (Septhiorth, Hushpuppy, Lunsrot, and Zqq) were members of the
E-learn 2.0 project. Each user also joined one or more research groups,
including UbiCom, Web 2.0, and e-learning groups.
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Implementation
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Experiments
We performed the experiment for five weeks and derived log statistics
from each hour on a weekly cycle. We collected and stored users’ location
logs and phone call logs in the context management server during the
experimental period. After the fourth week, we use the data from the fifth
week to evaluate the emergency contact service’s accuracy. Specifically, we
selected a random user, Masa, to be the unreachable target contact.
Masa’s contacts, location log, and phone records are shown elsewhere.
If Masa and the suggested contact were at the same location, then we
deemed the trial successful; otherwise, we considered it unsuccessful.
In this experiment, we set the weighting parameters as follows:
a location = 0.65, a relation = 0.35, Bw = 0.3.
Thus, we considered the location context as more important than
the social context.
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Results
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Results
The emergency contact service’s overall accuracy was 77.38 percent for
this experiment.
In most cases, Masa was performing a routine activity, and so the trial was
successful.
The emergency contact service generally failed to recommend the
appropriate third party when Masa encountered a special event or activity
which he didn’t place in his calendar, such as donating blood or a special
party. Intuitively, the accuracy of the emergency contact depends strongly
on whether the activity’s location is predictable and whether the acquired
context is sufficient to reason out the correct answer.
Finally, the emergency contact service could consider suggesting more than
one candidate to contact if the calculated highest possibility of all contacts
is less than a threshold.
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Q & A Session
Feel free to ask any question
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