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This book includes original, unpublished contributions presented at the Sixth International Conference on Emerging Applications of Information Technology (EAIT 2020), held at the University of Kalyani, Kalyani, West Bengal, India, on November 2020. The book covers the topics such as image processing, computer vision, pattern recognition, machine learning, data mining, big data and analytics, information security and privacy, wireless and sensor networks, and IoT. It will also include IoT application-related papers in pattern recognition, artificial intelligence, expert systems, natural language understanding, image processing, computer vision, applications in biomedical engineering, artificial neural networks, fuzzy logic, evolutionary optimization, data mining, Web intelligence, intelligent agent technology, virtual reality, and visualization.
This book plays a significant role in improvising human life to a great extent. The new applications of soft computing can be regarded as an emerging field in computer science, automatic control engineering, medicine, biology application, natural environmental engineering, and pattern recognition. Now, the exemplar model for soft computing is human brain. The use of various techniques of soft computing is nowadays successfully implemented in many domestic, commercial, and industrial applications due to the low-cost and very high-performance digital processors and also the decline price of the memory chips. This is the main reason behind the wider expansion of soft computing techniques and its application areas. These computing methods also play a significant role in the design and optimization in diverse engineering disciplines. With the influence and the development of the Internet of things (IoT) concept, the need for using soft computing techniques has become more significant than ever. In general, soft computing methods are closely similar to biological processes than traditional techniques, which are mostly based on formal logical systems, such as sentential logic and predicate logic, or rely heavily on computer-aided numerical analysis. Soft computing techniques are anticipated to complement each other. The aim of these techniques is to accept imprecision, uncertainties, and approximations to get a rapid solution. However, recent advancements in representation soft computing algorithms (fuzzy logic,evolutionary computation, machine learning, and probabilistic reasoning) generate a more intelligent and robust system providing a human interpretable, low-cost, approximate solution. Soft computing-based algorithms have demonstrated great performance to a variety of areas including multimedia retrieval, fault tolerance, system modelling, network architecture, Web semantics, big data analytics, time series, biomedical and health informatics, etc. Soft computing approaches such as genetic programming (GP), support vector machine–firefly algorithm (SVM-FFA), artificial neural network (ANN), and support vector machine–wavelet (SVM–Wavelet) have emerged as powerful computational models. These have also shown significant success in dealing with massive data analysis for large number of applications. All the researchers and practitioners will be highly benefited those who are working in field of computer engineering, medicine, biology application, signal processing, and mechanical engineering. This book is a good collection of state-of-the-art approaches for soft computing-based applications to various engineering fields. It is very beneficial for the new researchers and practitioners working in the field to quickly know the best performing methods. They would be able to compare different approaches and can carry forward their research in the most important area of research which has direct impact on betterment of the human life and health. This book is very useful because there is no book in the market which provides a good collection of state-of-the-art methods of soft computing-based models for multimedia retrieval, fault tolerance, system modelling, network architecture, Web semantics, big data analytics, time series, and biomedical and health informatics.
This book explores recent advances in the Internet of things (IoT) via advanced technologies and provides an overview of most aspects which are relevant for advance secure, distributed, decentralized blockchain technology in the Internet of things, their applications, and industry IoT. The book provides an in-depth analysis of the step-by-step evolution of IoT to create a change by enhancing the productivity of industries. It introduces how connected things, data, and their communication (data sharing) environment build a transparent, reliable, secure environment for people, processes, systems, and services with the help of blockchain technology.
This contributed volume discusses diverse topics to demystify the rapidly emerging and evolving blockchain technology, the emergence of integrated platforms and hosted third-party tools, and the development of decentralized applications for various business domains. It presents various applications that are helpful for research scholars and scientists who are working toward identifying and pinpointing the potential of as well as the hindrances to this technology.
The agriculture industry is facing significant challenges in meeting the increasing demand for food while also ensuring sustainable development. Traditional agricultural methods are not equipped to meet the demands of the modern world. To overcome these challenges, Advanced Technologies and AI-Equipped IoT Applications in High-Tech Agriculture provides an in-depth analysis of the opportunities and challenges for AI-powered management tools and IoT-equipped techniques for the high-tech agricultural ecosystem. The Handbook of Research on AI-Equipped IoT Applications in High-Tech Agriculture explores advanced methodologies, models, techniques, technologies, and applications along with the concepts of real-time supporting systems to help agricultural producers adjust plans or schedules for taking care of their farms. Additionally, it discusses the role of IoT technologies and AI applications in agricultural ecosystems and their potential to improve product quality and market competitiveness. The book includes discussions on the application of blockchain, biotechnology, drones, robotics, data analytics, and visualization in high-tech agriculture. It is an essential reference for anyone interested in the future of high-tech agriculture, including agricultural analysts, investment analysts, scholars, researchers, academics, professionals, engineers, and students.
The application of internet of things (IoT) technologies and artificial intelligence (AI)-enabled IoT solutions has gradually become accepted by business and production organizations as an effective tool for automating several activities effectively and efficiently and developing and distributing products to the global market. Within this book, the reader will learn how to implement IoT devices, IoT-equipped machines, and AI-equipped IoT applications using models and methodologies along with an array of case studies. Advanced IoT Technologies and Applications in the Industry 4.0 Digital Economy covers the basics of IoT-equipped machines in developing and managing various activities in many industries. It discusses all of the key points of an AI-enabled IoT solution, which includes predictive analytics, robotic process automation, predictive maintenance, automated processes, IoT technologies and IoT-equipped sensors related to machines and processes, production testing systems, and product assessment processes in the production environment. The book presents the concepts and interactive methods using datasets, processing workflow charts, and architectural diagrams along with additional real-time systems for easy and fast understanding of the application of IoT-equipped machines and AI-enabled solutions in organizations and includes many case studies throughout the book to enforce reader comprehension. This book is an ideal read for industry specialists, practitioners, researchers, scientists, and engineers working or involved in the fields of Robotics, IT, Computer Science, Soft Computing, IoT, AL/ML/DL, Data Science, the Semantic Web, Knowledge Engineering, and other related fields.
The volume of data that is generated, stored, and communicated across different industrial sections, business units, and scientific research communities has been rapidly expanding. The recent developments in cellular telecommunications and distributed/parallel computation technology have enabled real-time collection and processing of the generated data across different sections. On the one hand, the internet of things (IoT) enabled by cellular telecommunication industry connects various types of sensors that can collect heterogeneous data. On the other hand, the recent advances in computational capabilities such as parallel processing in graphical processing units (GPUs) and distributed processing over cloud computing clusters enabled the processing of a vast amount of data. There has been a vital need to discover important patterns and infer trends from a large volume of data (so-called Big Data) to empower data-driven decision-making processes. Tools and techniques have been developed in machine learning to draw insightful conclusions from available data in a structured and automated fashion. Machine learning algorithms are based on concepts and tools developed in several fields including statistics, artificial intelligence, information theory, cognitive science, and control theory. The recent advances in machine learning have had a broad range of applications in different scientific disciplines. This book covers recent advances of machine learning techniques in a broad range of applications in smart cities, automated industry, and emerging businesses.
Internet of Things: Technologies and Applications for a New Age of Intelligence outlines the background and overall vision for the Internet of Things (IoT) and Cyber-Physical Systems (CPS), as well as associated emerging technologies. Key technologies are described including device communication and interactions, connectivity of devices to cloud-based infrastructures, distributed and edge computing, data collection, and methods to derive information and knowledge from connected devices and systems using artificial intelligence and machine learning. Also included are system architectures and ways to integrate these with enterprise architectures, and considerations on potential business impacts and regulatory requirements. New to this edition: • Updated material on current market situation and outlook.• A description of the latest developments of standards, alliances, and consortia. More specifically the creation of the Industrial Internet Consortium (IIC) and its architecture and reference documents, the creation of the Reference Architectural Model for Industrie 4.0 (RAMI 4.0), the exponential growth of the number of working groups in the Internet Engineering Task Force (IETF), the transformation of the Open Mobile Alliance (OMA) to OMA SpecWorks and the introduction of OMA LightweightM2M device management and service enablement protocol, the initial steps in the specification of the architecture of Web of Things (WoT) by World Wide Consortium (W3C), the GS1 architecture and standards, the transformation of ETSI-M2M to oneM2M, and a few key facts about the Open Connectivity Forum (OCF), IEEE, IEC/ISO, AIOTI, and NIST CPS.• The emergence of new technologies such as distributed ledgers, distributed cloud and edge computing, and the use of machine learning and artificial intelligence for IoT.• A chapter on security, outlining the basic principles for secure IoT installations.• New use case description material on Logistics, Autonomous Vehicles, and Systems of CPS - Standards organizations covered: IEEE, 3GPP, IETF, IEC/ISO, Industrial Internet Consortium (IIC), ITU-T, GS1, Open Geospatial Consortium (OGC), Open Mobile Alliance (OMA, e.g. LightweightM2M), Object Management Group (OMG, e.g. Business Process Modelling Notation (BPMN)), oneM2M, Open Connectivity Forum (OCF), W3C - Key technologies for IoT covered: Embedded systems hardware and software, devices and gateways, capillary networks, local and wide area networking, IoT data management and data warehousing, data analytics and big data, complex event processing and stream analytics, control systems, machine learning and artificial intelligence, distributed cloud and edge computing, and business process and enterprise integration - In-depth security solutions for IoT systems - Technical explanations combined with design features of IoT and use cases, which help the development of real-world solutions - Detailed descriptions of the architectures and technologies that form the basis of IoT - Clear examples of IoT use cases from real-world implementations such as Smart Grid, Smart Buildings, Smart Cities, Logistics and Participatory Sensing, Industrial Automation, and Systems of CPS - Market perspectives, IoT evolution, and future outlook
A practical guide to the design, implementation, evaluation, and deployment of emerging technologies for intelligent IoT applications With the rapid development in artificially intelligent and hybrid technologies, IoT, edge, fog-driven, and pervasive computing techniques are becoming important parts of our daily lives. This book focuses on recent advances, roles, and benefits of these technologies, describing the latest intelligent systems from a practical point of view. Fog, Edge, and Pervasive Computing in Intelligent IoT Driven Applications is also valuable for engineers and professionals trying to solve practical, economic, or technical problems. With a uniquely practical approach spanning multiple fields of interest, contributors cover theory, applications, and design methodologies for intelligent systems. These technologies are rapidly transforming engineering, industry, and agriculture by enabling real-time processing of data via computational, resource-oriented metaheuristics and machine learning algorithms. As edge/fog computing and associated technologies are implemented far and wide, we are now able to solve previously intractable problems. With chapters contributed by experts in the field, this book: Describes Machine Learning frameworks and algorithms for edge, fog, and pervasive computing Considers probabilistic storage systems and proven optimization techniques for intelligent IoT Covers 5G edge network slicing and virtual network systems that utilize new networking capacity Explores resource provisioning and bandwidth allocation for edge, fog, and pervasive mobile applications Presents emerging applications of intelligent IoT, including smart farming, factory automation, marketing automation, medical diagnosis, and more Researchers, graduate students, and practitioners working in the intelligent systems domain will appreciate this book’s practical orientation and comprehensive coverage. Intelligent IoT is revolutionizing every industry and field today, and Fog, Edge, and Pervasive Computing in Intelligent IoT Driven Applications provides the background, orientation, and inspiration needed to begin.
"This book presents the advances and applications in the area of image processing with IoT and medical image processing and analysis techniques. It spotlights image processing and analysis techniques for IoT applications in CT images of COVID-19, remote sensing and medical engineering fields"--