This book highlights state-of-the-art research on big data and the Internet of Things (IoT), along with related areas to ensure efficient and Internet-compatible IoT systems. It not only discusses big data security and privacy challenges, but also energy-efficient approaches to improving virtual machine placement in cloud computing environments. Big data and the Internet of Things (IoT) are ultimately two sides of the same coin, yet extracting, analyzing and managing IoT data poses a serious challenge. Accordingly, proper analytics infrastructures/platforms should be used to analyze IoT data. Information technology (IT) allows people to upload, retrieve, store and collect information, which ultimately forms big data. The use of big data analytics has grown tremendously in just the past few years. At the same time, the IoT has entered the public consciousness, sparking people’s imaginations as to what a fully connected world can offer. Further, the book discusses the analysis of real-time big data to derive actionable intelligence in enterprise applications in several domains, such as in industry and agriculture. It explores possible automated solutions in daily life, including structures for smart cities and automated home systems based on IoT technology, as well as health care systems that manage large amounts of data (big data) to improve clinical decisions. The book addresses the security and privacy of the IoT and big data technologies, while also revealing the impact of IoT technologies on several scenarios in smart cities design. Intended as a comprehensive introduction, it offers in-depth analysis and provides scientists, engineers and professionals the latest techniques, frameworks and strategies used in IoT and big data technologies.

Intelligent transport systems, from basic management systems to more application-oriented systems, vary in the technologies they apply. Information technologies, including wireless communication, are important in intelligent transportation systems, as are computational technologies: floating car data/floating cellular data, sensing technologies, and video vehicle detection. Theoretical and application technologies, such as emergency vehicle notification systems, automatic road enforcement and collision avoidance systems, as well as some cooperative systems are also used in intelligent transportation systems. This book presents papers selected from the 128 submissions in the field of information technology and intelligent transportation systems received from 5 countries. In December 2019 Chang’an University organized a round-table meeting to discuss and score the technical merits of each selected paper, of which 23 are included in this book. Providing a current overview of the subject, the book will be of interest to all those working in the field of intelligent transportation systems and traffic management.

This book presents research and applications on arrival estimation and localization in speech processing to ensure that the broad vision of the direction of arrival estimation (DOAE) / localization of speech sources is well-established. The book first provides a brief overview of the most classical direction of arrival estimation and localization techniques. It then introduces the concept and model of acoustics sources and then highlights the most contemporary studies on this pervasive problem. In addition, the authors explore employing the optimization algorithms to improve the DOAE techniques. The book then highlights the concept and principles of the multi-DOAE approaches. Using a microphone array, the book introduces the localization and tracking problem of multiple speech/acoustic sources. It includes several applications and real-life speech sources localization based on the DOAE approaches. The book reports the challenges facing the DOAE techniques in speech-sources localization. The book pertains to researchers, designers, and engineers in speech processing fields.

This volume offers readers various perspectives and visions for cutting-edge research in ubiquitous healthcare. The topics emphasize large-scale architectures and high performance solutions for smart healthcare, healthcare monitoring using large-scale computing techniques, Internet of Things (IoT) and big data analytics for healthcare, Fog Computing, mobile health, large-scale medical data mining, advanced machine learning methods for mining multidimensional sensor data, smart homes, and resource allocation methods for the BANs. The book contains high quality chapters contributed by leading international researchers working in domains, such as e-Health, pervasive and context-aware computing, cloud, grid, cluster, and big-data computing. We are optimistic that the topics included in this book will provide a multidisciplinary research platform to the researchers, practitioners, and students from biomedical engineering, health informatics, computer science, and computer engineering.

Hybrid computational intelligent techniques are efficient in dealing with the real-world problems encountered in engineering fields. The primary objective of this book is to provide an exhaustive introduction as well as review of the hybrid computational intelligent paradigm, with supportive case studies. In addition, it aims to provide a gallery of engineering applications where this computing paradigm can be effectively use. Finally, it focuses on the recent quantum inspired hybrid intelligence to develop intelligent solutions for the future. The book also incorporates video demonstrations of each application for better understanding of the subject matter.

There are a number of books on computational intelligence (CI), but they tend to cover a broad range of CI paradigms and algorithms rather than provide an in-depth exploration in learning and adaptive mechanisms. This book sets its focus on CI based architectures, modeling, case studies and applications in big data analytics, and business intelligence. The intended audiences of this book are scientists, professionals, researchers, and academicians who deal with the new challenges and advances in the specific areas mentioned above. Designers and developers of applications in these areas can learn from other experts and colleagues through this book.

This book focuses primarily on the nature-inspired approach for designing smart applications. It includes several implementation paradigms such as design and path planning of wireless network, security mechanism and implementation for dynamic as well as static nodes, learning method of cloud computing, data exploration and management, data analysis and optimization, decision taking in conflicting environment, etc. The book fundamentally highlights the recent research advancements in the field of engineering and science.

Organizations are showing a remarkable interest in realizing knowledge management technologies and processes to adopt knowledge management as part of their overall strategy. However, even with the current advancement in technology, few organizations are entirely capable of developing critical organizational knowledge to achieve improved performance. Technological Innovations in Knowledge Management and Decision Support is a vital research publication that examines different knowledge management areas for organizational competitiveness, survival, and effectiveness. It also provides cutting-edge research techniques in related optimization methods and other automated techniques in real-world processes. Featuring a broad range of topics such as enterprise resource planning, neural networks, and image segmentation, this book is a critical resource for managers, IT specialists, healthcare and social sciences professionals, engineers, academicians, and researchers seeking research on effective knowledge management systems.

This book discusses in-depth role of optimization to optimize the controller parameters with reference to bio-inspired algorithms. Comparative studies to evaluate the performance of different optimization techniques in terms of the settling time, overshoot and undershoot responses of the frequency deviations, tie-line power flow deviations, and the area control error are included, supported by examples. The book also includes different scenarios of the load frequency controller for single area as well as multi-area thermal power generating unit considering different algorithms. Key Features: Highlights the importance of tuning the power system controller parameters with emphasis on bio-inspiration algorithms Provides some applied applications/examples of the thermal power system Focusses on power system applications based on the optimization algorithms with different single area and multi-area thermal power systems Reports different cases on the interconnected power systems with providing optimal performance by optimizing the controller’s parameters