Mobility Patterns, Big Data and Transport Analytics provides a guide to the new analytical framework and its relation to big data, focusing on capturing, predicting, visualizing and controlling mobility patterns - a key aspect of transportation modeling. The book features prominent international experts who provide overviews on new analytical frameworks, applications and concepts in mobility analysis and transportation systems. Users will find a detailed, mobility 'structural' analysis and a look at the extensive behavioral characteristics of transport, observability requirements and limitations for realistic transportation applications and transportation systems analysis that are related to complex processes and phenomena. This book bridges the gap between big data, data science, and transportation systems analysis with a study of big data's impact on mobility and an introduction to the tools necessary to apply new techniques. The book covers in detail, mobility 'structural' analysis (and its dynamics), the extensive behavioral characteristics of transport, observability requirements and limitations for realistic transportation applications, and transportation systems analysis related to complex processes and phenomena. The book bridges the gap between big data, data science, and Transportation Systems Analysis with a study of big data's impact on mobility, and an introduction to the tools necessary to apply new techniques.

The proposed book talks about the participation of human in Big Data.How human as a component of system can help in making the decision process easier and vibrant.It studies the basic build structure for big data and also includes advanced research topics.In the field of Biological sciences, it comprises genomic and proteomic data also. The book swaps traditional data management techniques with more robust and vibrant methodologies that focus on current requirement and demand through human computer interfacing in order to cope up with present business demand. Overall, the book is divided in to five parts where each part contains 4-5 chapters on versatile domain with human side of Big Data.

Big Data and Smart Service Systems presents the theories and applications regarding Big Data and smart service systems, data acquisition, smart cities, business decision-making support, and smart service design. The rapid development of computer and Internet technologies has led the world to the era of Big Data. Big Data technologies are widely used, which has brought unprecedented impacts on traditional industries and lifestyle. More and more governments, business sectors, and institutions begin to realize data is becoming the most valuable asset and its analysis is becoming the core competitiveness. - Describes the frontier of service science and motivates a discussion among readers on a multidisciplinary subject areas that explores the design of smart service - Illustrates the concepts, framework, and application of big data and smart service systems - Demonstrates the crucial role of smart service to promote the transformation of the regional and global economy

A smart city utilizes ICT technologies to improve the working effectiveness, share various data with the citizens, and enhance political assistance and societal wellbeing. The fundamental needs of a smart and sustainable city are utilizing smart technology for enhancing municipal activities, expanding monetary development, and improving citizens’ standards of living. The Handbook of Research on Data-Driven Mathematical Modeling in Smart Cities discusses new mathematical models in smart and sustainable cities using big data, visualization tools in mathematical modeling, machine learning-based mathematical modeling, and more. It further delves into privacy and ethics in data analysis. Covering topics such as deep learning, optimization-based data science, and smart city automation, this premier reference source is an excellent resource for mathematicians, statisticians, computer scientists, civil engineers, government officials, students and educators of higher education, librarians, researchers, and academicians.

This book discusses fundamentals of Blockchain technology and Industry 4.0. It discusses many applications of Blockchain technology in Industry 4.0, including integration of AI, IoT, and big data with Blockchain for Industry 4.0. It provides cutting-edge research content from researchers, academicians, and other professionals from different background areas to show their state-of-the-art knowledge to use Blockchain in Industry 4.0. The book discusses advantages of Industry 4.0, such as improved productivity, improved efficiency, flexibility, agility, better user experience, and many more, and also entails some challenges too, such as trust, traceability, security, reliability, transparency, etc., for creating an application of Industry 4.0. The book helps graduate, postgraduate, doctoral students, and industrial professionals to implement Blockchain in Industry 4.0.

Now in its second edition, Geographic Information Systems (GIS) for Disaster Management has been completely updated to take account of new developments in the field. Using a hands-on approach grounded in relevant GIS and disaster management theory and practice, this textbook continues the tradition of the benchmark first edition, providing coverage of GIS fundamentals applied to disaster management. Real-life case studies demonstrate GIS concepts and their applicability to the full disaster management cycle. The learning-by-example approach helps readers see how GIS for disaster management operates at local, state, national, and international scales through government, the private sector, non‐governmental organizations, and volunteer groups. New in the second edition: a chapter on allied technologies that includes remote sensing, Global Positioning Systems (GPS), indoor navigation, and Unmanned Aerial Systems (UAS); thirteen new technical exercises that supplement theoretical and practical chapter discussions and fully reinforce concepts learned; enhanced boxed text and other pedagogical features to give readers even more practical advice; examination of new forms of world‐wide disaster faced by society; discussion of new commercial and open-source GIS technology and techniques such as machine learning and the Internet of Things; new interviews with subject-matter and industry experts on GIS for disaster management in the US and abroad; new career advice on getting a first job in the industry. Learned yet accessible, Geographic Information Systems (GIS) for Disaster Management continues to be a valuable teaching tool for undergraduate and graduate instructors in the disaster management and GIS fields, as well as disaster management and humanitarian professionals. Please visit http://gisfordisastermanagement.com to view supplemental material such as slides and hands-on exercise video walkthroughs. This companion website offers valuable hands-on experience applying concepts to practice.