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Author: Zhenlong Li
Publisher: Routledge
ISBN: 1000261530
Category : Social Science
Languages : en
Pages : 235
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Book Description
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.
Author: Zhenlong Li
Publisher: Routledge
ISBN: 1000261530
Category : Social Science
Languages : en
Pages : 235
Get Book Here
Book Description
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.
Author: Zhenlong Li
Publisher: Routledge
ISBN: 1000261492
Category : Social Science
Languages : en
Pages : 205
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Book Description
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.
Author: James J. Jong Hyuk Park
Publisher: Springer
ISBN: 9783662454015
Category : Technology & Engineering
Languages : en
Pages : 720
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Book Description
The 6th FTRA International Conference on Computer Science and its Applications (CSA-14) will be held in Guam, USA, Dec. 17 - 19, 2014. CSA-14 presents a comprehensive conference focused on the various aspects of advances in engineering systems in computer science, and applications, including ubiquitous computing, U-Health care system, Big Data, UI/UX for human-centric computing, Computing Service, Bioinformatics and Bio-Inspired Computing and will show recent advances on various aspects of computing technology, Ubiquitous Computing Services and its application.
Author: Dong Wang
Publisher: Morgan Kaufmann
ISBN: 0128011319
Category : Computers
Languages : en
Pages : 232
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Book Description
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
Author: Carlos Castillo
Publisher: Cambridge University Press
ISBN: 1107135761
Category : Computers
Languages : en
Pages : 225
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Book Description
Social media is invaluable during crises like natural disasters, but difficult to analyze. This book shows how computer science can help.
Author: Siyal, Saeed
Publisher: IGI Global
ISBN: 1668495236
Category : Social Science
Languages : en
Pages : 344
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Book Description
The COVID-19 pandemic has presented unprecedented challenges for individuals, societies, and economies around the world. But it has also presented opportunities for growth and improvement in various domains. In this book, Dr. Saeed Siyal, an expert in management science, provides a comprehensive explanation for why pandemics and similar crises are both detrimental and simultaneously prompt long-needed change. Through a thorough analysis of the impacts of the COVID-19 pandemic, Dr. Saeed Siyal explores the ways in which it has forced individuals, organizations, and governments to adapt and find new solutions to the problems we face, many of which were exacerbated by the crisis. Using Crises and Disasters as Opportunities for Innovation and Improvement covers a range of topics, including healthcare, remote work, education, environment, and social connections, and provides evidence-based insights and practical solutions for adapting to the challenges and opportunities of COVID-19. This book is a must-read for anyone interested in advancing the standards of their organizations and making a positive impact on society. It is designed for managers, leaders, corporate sectors, MNCs, SMEs, academicians, and policymakers.
Author: Zhenlong Li
Publisher: MDPI
ISBN: 3039432443
Category : Science
Languages : en
Pages : 222
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Book Description
The convergence of big data and geospatial computing has brought forth challenges and opportunities to Geographic Information Science with regard to geospatial data management, processing, analysis, modeling, and visualization. This book highlights recent advancements in integrating new computing approaches, spatial methods, and data management strategies to tackle geospatial big data challenges and meanwhile demonstrates opportunities for using big data for geospatial applications. Crucial to the advancements highlighted in this book is the integration of computational thinking and spatial thinking and the transformation of abstract ideas and models to concrete data structures and algorithms.
Author: Tahmeena Khan
Publisher: Bentham Science Publishers
ISBN: 9815305190
Category : Education
Languages : en
Pages : 317
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Book Description
Artificial Intelligence: A Multidisciplinary Approach towards Teaching and Learning explores the evolving role of AI in education, covering applications in fields such as bioinformatics, environmental science, physics, chemistry, economics, and language learning. Written by experts, this book provides a comprehensive overview of AI's integration into diverse subjects, offering insights into the future of AI in education and its potential to enhance academic research and pedagogy. Targeted at faculty, students, and professionals, the book addresses AI's role in blended learning environments and offers practical tools for educators seeking to incorporate AI into their teaching practices. Key Features: - Multidisciplinary exploration of AI in teaching and learning. - Practical tools and methodologies for educators. - Insights into AI-driven innovations in research. - Relevant to a broad audience, from students to professionals.
Author: Duane A. Gill
Publisher: Edward Elgar Publishing
ISBN: 1800882203
Category : Social Science
Languages : en
Pages : 769
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Book Description
The Encyclopedia of Technological Hazards and Disasters in the Social Sciences brings together an array of global experts to investigate, explore and analyse human-caused disaster events. Providing insights into both the origins and aftermaths of disaster events, it offers advanced understanding of a broad range of disaster events facing society during the Anthropocene.
Author: Mayank Dave
Publisher: Springer Nature
ISBN: 9811575339
Category : Technology & Engineering
Languages : en
Pages : 972
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Book Description
This book presents best selected papers presented at the International Conference on Paradigms of Computing, Communication and Data Sciences (PCCDS 2020), organized by National Institute of Technology, Kurukshetra, India, during 1–3 May 2020. It discusses high-quality and cutting-edge research in the areas of advanced computing, communications and data science techniques. The book is a collection of latest research articles in computation algorithm, communication and data sciences, intertwined with each other for efficiency.
