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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