Increasingly, human beings are sensors engaging directly with the
mobile Internet. Individuals can now share real-time experiences at
an unprecedented scale. Social Sensing: Building Reliable Systems
on Unreliable Data looks at recent advances in the emerging field
of social sensing, emphasizing the key problem faced by application
designers: how to extract reliable information from data collected
from largely unknown and possibly unreliable sources. The book
explains how a myriad of societal applications can be derived from
this massive amount of data collected and shared by average
individuals. The title offers theoretical foundations to support
emerging data-driven cyber-physical applications and touches on key
issues such as privacy. The authors present solutions based on
recent research and novel ideas that leverage techniques from
cyber-physical systems, sensor networks, machine learning, data
mining, and information fusion.
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