Database Reference
In-Depth Information
Chapter 9
SOCIAL SENSING
Charu C. Aggarwal
IBMT.J.WatsonResearchCenter
Yorktown Heights, NY
charu@us.ibm.com
Tarek Abdelzaher
University of Illinois at Urbana Champaign
Urbana, IL
zaher@cs.uiuc.edu
Abstract
A number of sensor applications in recent years collect data which can
be directly associated with human interactions. Some examples of such
applications include GPS applications on mobile devices, accelerome-
ters, or location sensors designed to track human and vehicular trac.
Such data lends itself to a variety of rich applications in which one can
use the sensor data in order to model the underlying relationships and
interactions. This requires the development of trajectory mining tech-
niques, which can mine the GPS data for interesting social patterns.
It also leads to a number of challenges, since such data may often be
private, and it is important to be able to perform the mining process
without violating the privacy of the users. Given the open nature of
the information contributed by users in social sensing applications, this
also leads to issues of trust in making inferences from the underlying
data. In this chapter, we provide a broad survey of the work in this
important and rapidly emerging field. We also discuss the key problems
which arise in the context of this important field and the corresponding
solutions.
Keywords:
Sensor Networks, Social Sensors, Cyber-physical Networks
