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Introduction to Sensors in IoT and Cloud Computing Applications provides information about sensors and their applications. Readers are first introduced to the concept of small instruments and their application as sensors. The chapters which follow explain Internet of Things (IoT) architecture while providing notes on the implementation, demonstration and related issues of IoT systems. The book continues to explore the topic by providing information about sensor-cloud infrastructure, mobile cloud, fog computing (an extension of cloud computing that takes cloud computing to the cutting-edge of networking where data is produced) and integration of IoT devices with cloud computing. The book also presents notes on the taxonomy of fog-computing systems. The six chapters in this book provide essential information for general readers, and students of computer science to understand the basics of cloud computing networks, related concepts and applications.
CLOUD AND IOT-BASED VEHICULAR AD HOC NETWORKS This book details the architecture behind smart cars being fitted and connected with vehicular cloud computing, IoT and VANET as part of the intelligent transport system (ITS). As technology continues to weave itself more tightly into everyday life, socioeconomic development has become intricately tied to ever-evolving innovations. An example of this is the technology being developed to address the massive increase in the number of vehicles on the road, which has resulted in more traffic congestion and road accidents. This challenge is being addressed by developing new technologies to optimize traffic management operations. This book describes the state-of-the-art of the recent developments of Internet of Things (IoT) and cloud computing-based concepts that have been introduced to improve Vehicular Ad-Hoc Networks (VANET) with advanced cellular networks such as 5G networks and vehicular cloud concepts. 5G cellular networks provide consistent, faster and more reliable connections within the vehicular mobile nodes. By 2030, 5G networks will deliver the virtual reality content in VANET which will support vehicle navigation with real time communications capabilities, improving road safety and enhanced passenger comfort. In particular, the reader will learn: A range of new concepts in VANETs, integration with cloud computing and IoT, emerging wireless networking and computing models New VANET architecture, technology gap, business opportunities, future applications, worldwide applicability, challenges and drawbacks Details of the significance of 5G Networks in VANET, vehicular cloud computing, edge (fog) computing based on VANET. Audience The book will be widely used by researchers, automotive industry engineers, technology developers, system architects, IT specialists, policymakers and students.
This book explores the dynamic intersection of three cutting-edge technologies—Artificial Intelligence (AI), Internet of Things (IoT), and Cloud Computing—and their profound impact on diverse domains. Beginning with an introduction to AI and its challenges, it delves into IoT applications in fields like transportation, industry 4.0, healthcare, and agriculture. The subsequent chapter explores AI in the cloud, covering areas such as banking, e-commerce, smart cities, healthcare, and robotics. Another section investigates the integration of AI and IoT-Cloud, discussing applications like smart meters, smart cities, smart agriculture, smart healthcare, and smart industry. Challenges like data privacy and security are examined, and the future direction of these technologies, including fog computing and quantum computing, is explored. The book concludes with use cases that highlight the real-world applications of these transformative technologies across various sectors. Each chapter is also supplemented with a list of scholarly references for advanced readers. The book is intended primarily as a resource for students in information technology and technology courses. And as a secondary resource for industry professionals who want to learn about these technologies in the context of digital transform
This new volume explores the computational intelligence techniques necessary to carry out different software engineering tasks. Software undergoes various stages before deployment, such as requirements elicitation, software designing, software project planning, software coding, and software testing and maintenance. Every stage is bundled with a number of tasks or activities to be performed. Due to the large and complex nature of software, these tasks can become costly and error prone. This volume aims to help meet these challenges by presenting new research and practical applications in intelligent techniques in the field of software engineering. Computational Intelligence Applications for Software Engineering Problems discusses techniques and presents case studies to solve engineering challenges using machine learning, deep learning, fuzzy-logic-based computation, statistical modeling, invasive weed meta-heuristic algorithms, artificial intelligence, the DevOps model, time series forecasting models, and more.
The book Security of Internet of Things Nodes: Challenges, Attacks, and Countermeasures® covers a wide range of research topics on the security of the Internet of Things nodes along with the latest research development in the domain of Internet of Things. It also covers various algorithms, techniques, and schemes in the field of computer science with state-of-the-art tools and technologies. This book mainly focuses on the security challenges of the Internet of Things devices and the countermeasures to overcome security vulnerabilities. Also, it highlights trust management issues on the Internet of Things nodes to build secured Internet of Things systems. The book also covers the necessity of a system model for the Internet of Things devices to ensure security at the hardware level.
PRIVACY PRESERVATION of GENOMIC and MEDICAL DATA Discusses topics concerning the privacy preservation of genomic data in the digital era, including data security, data standards, and privacy laws so that researchers in biomedical informatics, computer privacy and ELSI can assess the latest advances in privacy-preserving techniques for the protection of human genomic data. Privacy Preservation of Genomic and Medical Data focuses on genomic data sources, analytical tools, and the importance of privacy preservation. Topics discussed include tensor flow and Bio-Weka, privacy laws, HIPAA, and other emerging technologies like Internet of Things, IoT-based cloud environments, cloud computing, edge computing, and blockchain technology for smart applications. The book starts with an introduction to genomes, genomics, genetics, transcriptomes, proteomes, and other basic concepts of modern molecular biology. DNA sequencing methodology, DNA-binding proteins, and other related terms concerning genomes and genetics, and the privacy issues are discussed in detail. The book also focuses on genomic data sources, analyzing tools, and the importance of privacy preservation. It concludes with future predictions for genomic and genomic privacy, emerging technologies, and applications. Audience Researchers in information technology, data mining, health informatics and health technologies, clinical informatics, bioinformatics, security and privacy in healthcare, as well as health policy developers in public and private health departments and public health.
This book provides in depth knowledge about critical factors involved in the success of pervasive healthcare. The book first presents critical components and importance of pervasive healthcare. The authors then give insight into the pervasive healthcare information systems and key consideration related to remote patient monitoring and safety. The book provides in-depth discussion about the security issues and protocols for pervasive healthcare. This book explores concepts and techniques behind the successive pervasive healthcare systems by providing in-depth knowledge about patient empowerment, remote patient monitoring, network establishment and protocols for effective pervasive healthcare. The book also provides case studies in the field. It is an ideal resource for researchers, students and healthcare organizations to get insight about the state of the art in pervasive healthcare systems. Provides current research, developments, and applications in pervasive healthcare; Includes technologies such as machine learning, cryptography, fog computing, and big data in the advancement of e-healthcare; Pertinent for researchers, students, practitioners and healthcare decision makers.
Dr.B.CHITRADEVI, Assistant Professor, Department of Computer Applications, Faculty of Science and Humanities, SRM Institute of Science and Technology, Trichy Campus, Tiruchirapalli, Tamil Nadu, India. Mrs.V.YASODHA, Assistant Professor, Department of Computer Applications, Cauvery College for Women (Autonomous), Tiruchirapalli, Tamil Nadu, India. Mr.M.DINESH, Assistant Professor, Department of Computer Science Engineering, Sasurie College of Engineering, Vijayamangalam, Tiruppur, Tamil Nadu, India. Mrs.K.PRADEEPA, Associate Professor, Department of Computer Science, Cauvery college for women (Autonomous), Tiruchirapalli, Tamil Nadu, India. Mrs.A.ANANDHAVALLI, Assistant Professor, Department of Computer Applications, Cauvery College for Women (Autonomous) Trichy, Tamil Nadu, India.
This exciting book explores the past, present and future of IoT, presenting the most prominent technologies that comprise IoT applications, including cloud computing, edge computing, embedded computing, Big Data, Artificial Intelligence (AI), blockchain and cybersecurity. A comprehensive description of the full range of the building blocks that comprise emerging IoT systems and applications is provided, while illustrating the evolution of IoT systems from the legacy small scale sensor systems and wireless sensor networks, to today’s large scale IoT deployments that comprise millions of connected devices in the cloud and smart objects with (semi)autonomous behavior. It also provides an outlook for the future evolution of IoT systems, based on their blending with AI and the use of emerging technologies like blockchain for massively decentralized applications. The full spectrum of technologies that are closely associated with the term IoT since its introduction are explored. The book also highlights the main challenges that are associated with the development and deployment of IoT applications at scale, including network connectivity, security, and interoperability challenges. First tech sensors, wireless sensor networks and radio-frequency identification (RFID) tags are covered. Machine learning, big data and security issues are also explored.
The field of computational intelligence has grown tremendously over that past five years, thanks to evolving soft computing and artificial intelligent methodologies, tools and techniques for envisaging the essence of intelligence embedded in real life observations. Consequently, scientists have been able to explain and understand real life processes and practices which previously often remain unexplored by virtue of their underlying imprecision, uncertainties and redundancies, and the unavailability of appropriate methods for describing the incompleteness and vagueness of information represented. With the advent of the field of computational intelligence, researchers are now able to explore and unearth the intelligence, otherwise insurmountable, embedded in the systems under consideration. Computational Intelligence is now not limited to only specific computational fields, it has made inroads in signal processing, smart manufacturing, predictive control, robot navigation, smart cities, and sensor design to name a few. Recent Trends in Computational Intelligence Enabled Research: Theoretical Foundations and Applications explores the use of this computational paradigm across a wide range of applied domains which handle meaningful information. Chapters investigate a broad spectrum of the applications of computational intelligence across different platforms and disciplines, expanding our knowledge base of various research initiatives in this direction. This volume aims to bring together researchers, engineers, developers and practitioners from academia and industry working in all major areas and interdisciplinary areas of computational intelligence, communication systems, computer networks, and soft computing. - Provides insights into the theory, algorithms, implementation, and application of computational intelligence techniques - Covers a wide range of applications of deep learning across various domains which are researching the applications of computational intelligence - Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques