This book gathers a selection of peer-reviewed papers presented at the third Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2021) conference, held in Shanghai, China, on Nov. 27, 2021. The contributions, prepared by an international team of scientists and engineers, cover the latest advances made in the field of machine learning, and big data analytics methods and approaches for the data-driven co-design of communication, computing, and control for smart cities. Given its scope, it offers a valuable resource for all researchers and professionals interested in big data, smart cities, and cyber-physical systems.
This book considers the challenges related to the effective implementation of artificial intelligence (AI) and machine learning (ML) technologies to the cultural heritage digitization process. Particular focus is placed on improvements to the data acquisition stage, as well as the data enrichment and curation stages, using advanced artificial intelligence techniques and tools. An emphasis is placed on recent applications related to deep learning for visual recognition, generative models, natural language processing, and super resolution. The book is a valuable reference for researchers working in the multidisciplinary field of cultural heritage and AI, as well as professional experts in the art and culture domains, such as museums, libraries, and historic sites and buildings. Reports on techniques and methods that leverage AI and machine learning and their impact on the digitization of cultural heritage; Addresses challenges of improving data acquisition, enrichment and management processes; Highlights contributions from international researchers from diverse fields and subject areas.
Advances in the knowledge of the tangible components (position, size, shape) and intangible components (identity, habits) of an historic building or site involves fundamental and complex tasks in any project related to the conservation of cultural heritage (CH). In recent years, new geotechnologies have proven their usefulness and added value to the field of cultural heritage (CH) in the tasks of recording, modeling, conserving, and visualizing. In addition, current developments in building information modeling (HBIM), allow integration and simulation of different sources of information, generating a digital twin of any complex CH construction. As a result, experts in the area have increased the number of available sensors and methodologies. However, the quick evolution of geospatial technologies makes it necessary to revise their use, integration, and application in CH. This process is difficult to adopt, due to the new options which are opened for the study, analysis, management, and valorization of CH. Therefore, the aim of the present Special Issue is to cover the latest relevant topics, trends, and best practices in geospatial technologies and processing methodologies for CH sites and scenarios as well as to introduce the new tendencies. This book originates from the Special Issue “Data Acquisition and Processing in Cultural Heritage”, focusing primarily on data and sensor integration for CH; documentation/restoration in CH; heritage 3D documentation and modeling of complex CH sites; drone inspections in CH; software development in CH; and augmented reality in CH. It is hoped that this book will provide the advice and guidance required for any CH professional, making the best possible use of these sensors and methods in CH.
This book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), held in Shanghai, China, on November 6, 2020. Due to the COVID-19 outbreak problem, SPIoT-2020 conference was held online by Tencent Meeting. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.
This book presents the proceedings of the 2020 2nd International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2021), online conference, on 30 October 2021. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.
To introduce the concepts of Big data Analytics for business intelligence and predictive modeling for SMART tourism product design in the Indian tourism industry. Quantitative literature survey of the contemporary research topics and application of technologies in SMART tourism analytics. To apply the Big Data analytics and Business Intelligence concepts in the Indian tourism industry and discuss the related case studies covering various subtopics of exclusive destination branding and Market intelligence for knowledge discovery. To evolve Big Data strategy for the specific tourism product design and respective data extraction, transformation, and loading data in the Business Intelligence and data mining tools. To create attractive dashboards for SMART tourism application using storyboarding and Human-Computer Interaction techniques. Visualization techniques for descriptive data analytics and business insights. Intelligent Decision support system for Tourism destination choice.
Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.
As digital technologies occupy a more central role in working and everyday human life, individual and social realities are increasingly constructed and communicated through digital objects, which are progressively replacing and representing physical objects. They are even shaping new forms of virtual reality. This growing digital transformation coupled with technological evolution and the development of computer computation is shaping a cyber society whose working mechanisms are grounded upon the production, deployment, and exploitation of big data. In the arts and humanities, however, the notion of big data is still in its embryonic stage, and only in the last few years, have arts and cultural organizations and institutions, artists, and humanists started to investigate, explore, and experiment with the deployment and exploitation of big data as well as understand the possible forms of collaborations based on it. Big Data in the Arts and Humanities: Theory and Practice explores the meaning, properties, and applications of big data. This book examines therelevance of big data to the arts and humanities, digital humanities, and management of big data with and for the arts and humanities. It explores the reasons and opportunities for the arts and humanities to embrace the big data revolution. The book also delineates managerial implications to successfully shape a mutually beneficial partnership between the arts and humanities and the big data- and computational digital-based sciences. Big data and arts and humanities can be likened to the rational and emotional aspects of the human mind. This book attempts to integrate these two aspects of human thought to advance decision-making and to enhance the expression of the best of human life.
This is an open access book.Amidst the advancement of modern science and technology, especially the development of information technology, our society has entered a stage of highly developed information technology. We should do our utmost to utilize the achievements yielded by scientific and technological innovation, vigorously promote the informatization of education management, and provide quality services for education and teaching. The importance of information technology education in educational management simply cannot be overstated. Educational management is closely related to college education and teaching. Only through good educational management can education and teaching proceed smoothly. The realization of education management information is conducive to the propulsion of high efficiency in school management, as well as to the smooth implementation of teaching objectives and better participation of students and parents in school management. Informationization is the mainstream of the world's economic development, while informationization of teaching management is the product of adapting to the demand of time development. We educational management workers should learn from the excellent educational managers at home and abroad, strive to improve their information level, and synchronize with the Times. In order to provide a more convenient and efficient communication platform for relevant academic researchers, we organized the 2023 3rd International Conference on Education, Information Management and Service Science (EIMSS 2023). 2023 3rd International Conference on Education, Information Management and Service Science (EIMSS 2023) will be held on July 21–23, 2023 in Qingdao, China. EIMSS 2023 aims to bring together innovative academics and industrial experts in the field of Education, Information Management and Service Science to a common forum. The primary goal of the conference is to stimulate research and developmental activities in Education, Information Management and Service Science, and another goal is to facilitate the scientific exchange of information between researchers, developers, engineers, students, and practitioners working all around the world. As an ideal platform for individuals to exchange views and experiences in Education, Information Management, Service Science, and related domains, the conference will convene annually. We warmly invite you to participate in EIMSS 2023 and look forward to seeing you in Qingdao!
Produced by The University of South Carolina’s School of Library and Information Science, this volume of the Annual Review of Cultural Heritage Informatics (ARCHI)is the polestar publication for cultural heritage scholars, professionals, and students. Featuring original works selected by the distinguished editorial board of international scholars, ARCHI presents a broad spectrum of the cultural heritage informatics field. New to this edition is a Perspectives chapter in which scholars, practitioners, and leaders delve into a current issue facing the field, voicing their thoughts based on research and personal experience. Some topics covered include: How the transactions and reflections of collections work influences the workplace, community, and nation An in-depth look at the work and how theoretical and professional obstacles hinder convergence. The debate over technology and big data addressed through two articles offering opposing viewpoints on the benefits and disadvantages With a focus on the way our cultural heritage is accessed, stored, and preserved, this volume looks forward to the future and the insight brought forth through technological innovation and research.
