Social Sensing

Social Sensing
Author: Dong Wang,Tarek Abdelzaher,Lance Kaplan
Publsiher: Morgan Kaufmann
Total Pages: 232
Release: 2015-04-17
Genre: Computers
ISBN: 9780128011317

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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. Offers a unique interdisciplinary perspective bridging social networks, big data, cyber-physical systems, and reliability Presents novel theoretical foundations for assured social sensing and modeling humans as sensors Includes case studies and application examples based on real data sets Supplemental material includes sample datasets and fact-finding software that implements the main algorithms described in the book

Social Sensing and Big Data Computing for Disaster Management

Social Sensing and Big Data Computing for Disaster Management
Author: Zhenlong Li,Qunying Huang,Christopher T. Emrich
Publsiher: Routledge
Total Pages: 192
Release: 2020-12-17
Genre: Social Science
ISBN: 9781000261493

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Social Sensing and Big Data Computing for Disaster Management captures recent advancements in leveraging social sensing and big data computing for supporting disaster management. Specifically, analysed within this book are some of the promises and pitfalls of social sensing data for disaster relevant information extraction, impact area assessment, population mapping, occurrence patterns, geographical disparities in social media use, and inclusion in larger decision support systems. Traditional data collection methods such as remote sensing and field surveying often fail to offer timely information during or immediately following disaster events. Social sensing enables all citizens to become part of a large sensor network which is low cost, more comprehensive, and always broadcasting situational awareness information. However, data collected with social sensing is often massive, heterogeneous, noisy, and unreliable in some aspects. It comes in continuous streams, and often lacks geospatial reference information. Together, these issues represent a grand challenge toward fully leveraging social sensing for emergency management decision making under extreme duress. Meanwhile, big data computing methods and technologies such as high-performance computing, deep learning, and multi-source data fusion become critical components of using social sensing to understand the impact of and response to the disaster events in a timely fashion. This book was originally published as a special issue of the International Journal of Digital Earth.

Social Sensing and Big Data Computing for Disaster Management

Social Sensing and Big Data Computing for Disaster Management
Author: Zhenlong Li,Qunying Huang,Christopher T. Emrich
Publsiher: Routledge
Total Pages: 233
Release: 2020-12-17
Genre: Social Science
ISBN: 9781000261530

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Social Sensing and Big Data Computing for Disaster Management captures recent advancements in leveraging social sensing and big data computing for supporting disaster management. Specifically, analysed within this book are some of the promises and pitfalls of social sensing data for disaster relevant information extraction, impact area assessment, population mapping, occurrence patterns, geographical disparities in social media use, and inclusion in larger decision support systems. Traditional data collection methods such as remote sensing and field surveying often fail to offer timely information during or immediately following disaster events. Social sensing enables all citizens to become part of a large sensor network which is low cost, more comprehensive, and always broadcasting situational awareness information. However, data collected with social sensing is often massive, heterogeneous, noisy, and unreliable in some aspects. It comes in continuous streams, and often lacks geospatial reference information. Together, these issues represent a grand challenge toward fully leveraging social sensing for emergency management decision making under extreme duress. Meanwhile, big data computing methods and technologies such as high-performance computing, deep learning, and multi-source data fusion become critical components of using social sensing to understand the impact of and response to the disaster events in a timely fashion. This book was originally published as a special issue of the International Journal of Digital Earth.

People Analytics

People Analytics
Author: Ben Waber
Publsiher: FT Press
Total Pages: 303
Release: 2013-04-24
Genre: Business & Economics
ISBN: 9780133158335

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Discover powerful hidden social "levers" and networks within your company... then, use that knowledge to make slight "tweaks" that dramatically improve both business performance and employee fulfillment! In People Analytics, MIT Media Lab innovator Ben Waber shows how sensors and analytics can give you an unprecedented understanding of how your people work and collaborate, and actionable insights for building a more effective, productive, and positive organization. Through cutting-edge case studies, Waber shows how: Changing the way call center employees spent their breaks increased performance by 25% while significantly reducing stress Quantifying the failure of marketing and customer service to communicate led to a more cohesive and profitable organization Tweaking the balance of in-person and electronic communication can enhance the value of both Sensor data can help you discover who your internal experts really are Identifying employees involved in "creative" behaviors can help you promote innovation throughout your business Sensors and simulations can help you optimize your sick-day policies Measuring informal interactions can improve the chances that a merger, acquisition, or "mega-project" will succeed Drawing on his cutting-edge work at MIT and Harvard, Waber addresses crucial issues ranging from technology to privacy, revealing what will be possible in a few years, and what you can achieve right now. In bringing the power of analytics to organizational development, he offers immense new opportunities to everyone with responsibility for workplace performance.

Urban Remote Sensing

Urban Remote Sensing
Author: Xiaojun X. Yang
Publsiher: John Wiley & Sons
Total Pages: 532
Release: 2021-10-11
Genre: Technology & Engineering
ISBN: 9781119625841

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Urban Remote Sensing The second edition of Urban Remote Sensing is a state-of-the-art review of the latest progress in the subject. The text examines how evolving innovations in remote sensing allow to deliver the critical information on cities in a timely and cost-effective way to support various urban management activities and the scientific research on urban morphology, socio-environmental dynamics, and sustainability. Chapters are written by leading scholars from a variety of disciplines including remote sensing, GIS, geography, urban planning, environmental science, and sustainability science, with case studies predominately drawn from North America and Europe. A review of the essential and emerging research areas in urban remote sensing including sensors, techniques, and applications, especially some critical issues that are shifting the ­directions in urban remote sensing research. Illustrated in full color throughout, including numerous relevant case studies and extensive discussions of important concepts and cutting-edge technologies to enable clearer understanding for non-technical audiences. Urban Remote Sensing, Second Edition will be of particular interest to upper-division undergraduate and graduate students, researchers and professionals working in the fields of remote sensing, geospatial information, and urban & environmental planning.

People and Pixels

People and Pixels
Author: National Research Council,Division of Behavioral and Social Sciences and Education,Board on Environmental Change and Society,Committee on the Human Dimensions of Global Change
Publsiher: National Academies Press
Total Pages: 267
Release: 1998-06-21
Genre: Science
ISBN: 9780309064088

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Space-based sensors are giving us an ever-closer and more comprehensive look at the earth's surface; they also have the potential to tell us about human activity. This volume examines the possibilities for using remote sensing technology to improve understanding of social processes and human-environment interactions. Examples include deforestation and regrowth in Brazil, population-environment interactions in Thailand, ancient and modern rural development in Guatemala, and urbanization in the United States, as well as early warnings of famine and disease outbreaks. The book also provides information on current sources of remotely sensed data and metadata and discusses what is involved in establishing effective collaborative efforts between scientists working with remote sensing technology and those working on social and environmental issues.

Managing and Mining Sensor Data

Managing and Mining Sensor Data
Author: Charu C. Aggarwal
Publsiher: Springer Science & Business Media
Total Pages: 534
Release: 2013-01-15
Genre: Computers
ISBN: 9781461463092

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Advances in hardware technology have lead to an ability to collect data with the use of a variety of sensor technologies. In particular sensor notes have become cheaper and more efficient, and have even been integrated into day-to-day devices of use, such as mobile phones. This has lead to a much larger scale of applicability and mining of sensor data sets. The human-centric aspect of sensor data has created tremendous opportunities in integrating social aspects of sensor data collection into the mining process. Managing and Mining Sensor Data is a contributed volume by prominent leaders in this field, targeting advanced-level students in computer science as a secondary text book or reference. Practitioners and researchers working in this field will also find this book useful.

Sensing in Social Interaction

Sensing in Social Interaction
Author: Lorenza Mondada
Publsiher: Cambridge University Press
Total Pages: 632
Release: 2021-11-04
Genre: Psychology
ISBN: 9781108657655

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This book offers a novel perspective on how people engage in sensing the materiality of the world as a way of social interaction. It proposes a conceptual and analytical advance in how to approach sensing as an intersubjective and interactional phenomenon within the framework of conversation analysis and ethnomethodology. Based on a uniquely rich set of video-recorded data, the author shows how people reacting to cheese in gourmet shops across Europe highlights the part the senses play in human behaviour and communication. The multimodal analysis of the case studies reveals the systematic features of looking, touching, smelling, and tasting in situated activities. By blending interdisciplinary research with real life, the volume puts together a theoretical and methodological framework for studying the embodied and linguistic dimensions of sensing in interaction.