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social networks are a hot research topic as they combine elements from two huge
markets: mobile devices/phones and social networks.
Mobile settings offer opportunities for new services on social networks as
changes in user contexts (location and activities) can be used to provide the user
with context-aware services relevant to that moment and situation [
59
]. There also
exist specific situations where social networks must be really connected with
mobile phones, such as healthcare-oriented social networks/services where the
mobile phone can be used to monitor the health status of the patient [
76
].
In all these, and other similar situations, mobile databases may be used as P2P
mobile databases, where each mobile phone shares certain information with other
mobile phones. Mobile P2P databases is a recent research topic that shows some
interesting work [
42
,
50
,
56
,
68
,
73
], but must be developed in order to suit the
industry needs.
11.6 Future Scenarios
We would like to introduce a couple of near future scenarios where mobile phones
have a relevant role in community-built databases, which may exemplify the use of
several technologies and ideas expressed previously.
11.6.1 MobiTag: A Mobile Interface to the Real World
MobiTag (not an actual product) would be a mix of Layar and Google Shopper.
With this application, users could capture any product, person, or place with their
camera-phones and then tag, review, or comment on it, sharing these contents with
others and being able to access other people's contents. MobiTag would be an
interface to a general community-built database empowered by augmented reality,
object/face recognition, and several other technologies such as Opinion Mining/
Sentiment Analysis [
55
], in order to process all the user-generated content appro-
priately so that it is condensed and displayed on a small screen. Figure
11.6
shows
an example of the use of MobiTag or a similar product.
One of the most important challenges that should be addressed for this future
scenario would be the object/face recognition software, but products such as
Google Shopper show that actual state of the art should be enough for recognizing
products. Applications such as Recognizr
7
are working on the face detection
problem from a mobile phone and retrieving the information from Social Media
such as LinkedIn or Facebook (see Fig.
11.7
).
7
Recognizer is a prototype developed by The Tribe
http://www.tat.se/site/showroom/latest_
design.html
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