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Dong Wang Authors a New Book, Social Sensing-Building Reliable Systems on Unreliable Data

Virginia Watterson • DATE: June 24, 2015

Increasingly, human beings are sensors engaging directly with the mobile internet. Individuals can now share real-time experiences at an unprecedented scale, with GPS devices and camera phones, mobile Internet connectivity, and social media. Social Sensing: Building Reliable Systems on Unreliable Data offers a look into 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? Unlike traditional sensor networks, where sensor reliability and fault models are clearly understood, a big challenge in social sensing stems from the fact that the data can be noisy, unreliable, and possibly erroneous and the data sources are often unknown to the collector, making it very difficult to ascertain not only correctness of observations but also reliability of sources. The book explains how a myriad of societal applications can be derived from this massive amount of data of questionable quality that is collected and shared by average individuals. The book offers theoretical foundations to support emerging data-driven cyber-physical applications, and touches on key issues such as data reliability in a highly interconnected and instrumented world. The authors share the latest research and novel ideas that leverage techniques from cyber-physical systems, sensor networks, machine learning, data mining, and information fusion to present solutions to this problem.