Social Sensing: Building Reliable Systems on Unreliable Data - Softcover

Wang, Dong; Abdelzaher, Tarek; Kaplan, Lance

Softcover

ISBN 10: 0128008679 ISBN 13: 9780128008676

Publisher: Morgan Kaufmann, 2015

Synopsis

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.

About this title

Review:

"...recommended both to cyber-physical systems researchers and sensor network researchers, but also to people involved in business analytics. After finishing this book, readers will better understand the fundamental concepts related to the subject and also receive new interpretations of, and solutions to, the problems encountered." --Computing Reviews

From the Back Cover:

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 data sources are often unknown to the collector, making it hard 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 collected and shared by average individuals; data which can be noisy, unreliable, and possibly erroneous. The book offers theoretical foundations to support emerging data-driven cyber-physical applications, and touches on key issues such as privacy 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.

About this edition

• Publisher: Morgan Kaufmann
• Publication date: 2015
• ISBN 10: 0128008679
• ISBN 13: 9780128008676
• Binding: Paperback
• Number of pages: 232