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This book comprehensively conveys the theoretical and practical aspects of IoT and big data analytics with the solid contributions from practitioners as well as academicians. This book examines and expounds the unique capabilities of the big data analytics platforms in capturing, cleansing and crunching IoT device/sensor data in order to extricate actionable insights. A number of experimental case studies and real-world scenarios are incorporated in this book in order to instigate our book readers. This book Analyzes current research and development in the domains of IoT and big data analytics Gives an overview of latest trends and transitions happening in the IoT data analytics space Illustrates the various platforms, processes, patterns, and practices for simplifying and streamlining IoT data analytics The Internet of Things and Big Data Analytics: Integrated Platforms and Industry Use Cases examines and accentuates how the multiple challenges at the cusp of IoT and big data can be fully met. The device ecosystem is growing steadily. It is forecast that there will be billions of connected devices in the years to come. When these IoT devices, resource-constrained as well as resource-intensive, interact with one another locally and remotely, the amount of multi-structured data generated, collected, and stored is bound to grow exponentially. Another prominent trend is the integration of IoT devices with cloud-based applications, services, infrastructures, middleware solutions, and databases. This book examines the pioneering technologies and tools emerging and evolving in order to collect, pre-process, store, process and analyze data heaps in order to disentangle actionable insights.

Blockchain, Internet of Things, and Artificial Intelligence provides an integrated overview and technical description of the fundamental concepts of blockchain, IoT, and AI technologies. State-of-the-art techniques are explored in depth to discuss the challenges in each domain. The convergence of these revolutionized technologies has leveraged several areas that receive attention from academicians and industry professionals, which in turn promotes the book's accessibility more extensively.Discussions about an integrated perspective on the influence of blockchain, IoT, and AI for smart cities, healthcare, and other business sectors illuminate the benefits and opportunities in the ecosystems worldwide. The contributors have focused on real-world examples and applications and highlighted the significance of the strengths of blockchain to transform the readers’ thinking toward finding potential solutions.The faster maturity and stability of blockchain is the key differentiator in artificial intelligence and the Internet of Things. This book discusses their potent combination in realizing intelligent systems, services, and environments. The contributors present their technical evaluations and comparisons with existing technologies. Theoretical explanations and experimental case studies related to real-time scenarios are also discussed.FEATURES Discusses the potential of blockchain to significantly increase data while boosting accuracy and integrity in IoT-generated data and AI-processed information Elucidates definitions, concepts, theories, and assumptions involved in smart contracts and distributed ledgers related to IoT systems and AI approaches Offers real-world uses of blockchain technologies in different IoT systems and further studies its influence in supply chains and logistics, the automotive industry, smart homes, the pharmaceutical industry, agriculture, and other areas Presents readers with ways of employing blockchain in IoT and AI, helping them to understand what they can and cannot do with blockchain Provides readers with an awareness of how industry can avoid some of the pitfalls of traditional data-sharing strategiesThis book is suitable for graduates, academics, researchers, IT professionals, and industry experts.

This book covers IoT and Big Data from a technical and business point of view. The book explains the design principles, algorithms, technical knowledge, and marketing for IoT systems. It emphasizes applications of big data and IoT. It includes scientific algorithms and key techniques for fusion of both areas. Real case applications from different industries are offering to facilitate ease of understanding the approach. The book goes on to address the significance of security algorithms in combing IoT and big data which is currently evolving in communication technologies. The book is written for researchers, professionals, and academicians from interdisciplinary and transdisciplinary areas. The readers will get an opportunity to know the conceptual ideas with step-by-step pragmatic examples which makes ease of understanding no matter the level of the reader.

This book provides applications of machine learning in healthcare systems and seeks to close the gap between engineering and medicine. It will combine the design and problem-solving skills of engineering with health sciences, in order to advance healthcare treatment. The book will include areas such as diagnosis, monitoring, and therapy. The book will provide real-world case studies, gives a detailed exploration of applications in healthcare systems, offers multiple perspectives on a variety of disciplines, while also letting the reader know how to avoid some of the consequences of old methods with data sharing. The book can be used as a reference for practitioners, researchers and for students at basic and intermediary levels in Computer Science, Electronics and Communications.

Convergence of Blockchain, AI and IoT: A Digital Platform discusses the convergence of three powerful technologies that play into the digital revolution and blur the lines between biological, digital, and physical objects. This book covers novel algorithms, solutions for addressing issues in applications, security, authentication, and privacy.Discusses innovative technological upgradation and significant challenges in the current eraGives an overview of clinical scientific research that enables smart diagnosis through artificial intelligence Provides an insight into how disruptive technology enabled with the self-running devices and protection mechanism is involved in an augmented reality with blockchain mechanismTalks about neural science being capable of enhancing deep brain waves to predict an overall improvement in human thoughts and behavioursCovers the digital currency mechanism in detailEnhances the knowledge of readers about smart contract and ledger mechanism with artificial intelligence and blockchain mechanismTargeted audiences range from those interested in the technical revolution of blockchain, big data and the Internet of Things, to research scholars and the professional market.

Convergence of Blockchain, AI and IoT: A Digital Platform discusses the convergence of three powerful technologies that play into the digital revolution and blur the lines between biological, digital, and physical objects. This book covers novel algorithms, solutions for addressing issues in applications, security, authentication, and privacy.Discusses innovative technological upgradation and significant challenges in the current eraGives an overview of clinical scientific research that enables smart diagnosis through artificial intelligence Provides an insight into how disruptive technology enabled with the self-running devices and protection mechanism is involved in an augmented reality with blockchain mechanismTalks about neural science being capable of enhancing deep brain waves to predict an overall improvement in human thoughts and behavioursCovers the digital currency mechanism in detailEnhances the knowledge of readers about smart contract and ledger mechanism with artificial intelligence and blockchain mechanismTargeted audiences range from those interested in the technical revolution of blockchain, big data and the Internet of Things, to research scholars and the professional market.

The purpose of this edited book is to provide the relevant technologies and case studies in a concise format that will simplify and streamline the processing of blockchain. The goal is for the contents of this book to change the way business transformations are conducting in economic and social systems. The book examines blockchain technology, the transaction attributes, and its footprint in various fields. It offers fundamentals and terminologies used in blockchain, architecture, and various consensus mechanisms that can be deployed in areas such as healthcare, smart cities, and supply chain management. The book provides a widespread knowledge into the deployment of security countermeasures that can be implemented for a blockchain network and enables the reader to consider the management of business processes and the implementation process in detail. The book highlights the challenges and provides various e-business case studies of security countermeasures. The book serves researchers and businesses by providing a thorough understanding of the transformation process using blockchain technology.

The purpose of this edited book is to provide the relevant technologies and case studies in a concise format that will simplify and streamline the processing of blockchain. The goal is for the contents of this book to change the way business transformations are conducting in economic and social systems. The book examines blockchain technology, the transaction attributes, and its footprint in various fields. It offers fundamentals and terminologies used in blockchain, architecture, and various consensus mechanisms that can be deployed in areas such as healthcare, smart cities, and supply chain management. The book provides a widespread knowledge into the deployment of security countermeasures that can be implemented for a blockchain network and enables the reader to consider the management of business processes and the implementation process in detail. The book highlights the challenges and provides various e-business case studies of security countermeasures. The book serves researchers and businesses by providing a thorough understanding of the transformation process using blockchain technology.

This book provides applications of machine learning in healthcare systems and seeks to close the gap between engineering and medicine. It will combine the design and problem-solving skills of engineering with health sciences, in order to advance healthcare treatment. The book will include areas such as diagnosis, monitoring, and therapy. The book will provide real-world case studies, gives a detailed exploration of applications in healthcare systems, offers multiple perspectives on a variety of disciplines, while also letting the reader know how to avoid some of the consequences of old methods with data sharing. The book can be used as a reference for practitioners, researchers and for students at basic and intermediary levels in Computer Science, Electronics and Communications.

This book covers IoT and Big Data from a technical and business point of view. The book explains the design principles, algorithms, technical knowledge, and marketing for IoT systems. It emphasizes applications of big data and IoT. It includes scientific algorithms and key techniques for fusion of both areas. Real case applications from different industries are offering to facilitate ease of understanding the approach. The book goes on to address the significance of security algorithms in combing IoT and big data which is currently evolving in communication technologies. The book is written for researchers, professionals, and academicians from interdisciplinary and transdisciplinary areas. The readers will get an opportunity to know the conceptual ideas with step-by-step pragmatic examples which makes ease of understanding no matter the level of the reader.

Blockchain, Internet of Things, and Artificial Intelligence provides an integrated overview and technical description of the fundamental concepts of blockchain, IoT, and AI technologies. State-of-the-art techniques are explored in depth to discuss the challenges in each domain. The convergence of these revolutionized technologies has leveraged several areas that receive attention from academicians and industry professionals, which in turn promotes the book's accessibility more extensively.Discussions about an integrated perspective on the influence of blockchain, IoT, and AI for smart cities, healthcare, and other business sectors illuminate the benefits and opportunities in the ecosystems worldwide. The contributors have focused on real-world examples and applications and highlighted the significance of the strengths of blockchain to transform the readers’ thinking toward finding potential solutions.The faster maturity and stability of blockchain is the key differentiator in artificial intelligence and the Internet of Things. This book discusses their potent combination in realizing intelligent systems, services, and environments. The contributors present their technical evaluations and comparisons with existing technologies. Theoretical explanations and experimental case studies related to real-time scenarios are also discussed.FEATURES Discusses the potential of blockchain to significantly increase data while boosting accuracy and integrity in IoT-generated data and AI-processed information Elucidates definitions, concepts, theories, and assumptions involved in smart contracts and distributed ledgers related to IoT systems and AI approaches Offers real-world uses of blockchain technologies in different IoT systems and further studies its influence in supply chains and logistics, the automotive industry, smart homes, the pharmaceutical industry, agriculture, and other areas Presents readers with ways of employing blockchain in IoT and AI, helping them to understand what they can and cannot do with blockchain Provides readers with an awareness of how industry can avoid some of the pitfalls of traditional data-sharing strategiesThis book is suitable for graduates, academics, researchers, IT professionals, and industry experts.

The significant objective of this edited book is to bridge the gap between smart manufacturing and big data by exploring the challenges and limitations. Companies employ big data technology in the manufacturing field to acquire data about the products. Manufacturing companies could gain a deep business insight by tracking customer details, monitoring fuel consumption, detecting product defects, and supply chain management. Moreover, the convergence of smart manufacturing and big data analytics currently suffers due to data privacy concern, short of qualified personnel, inadequate investment, long-term storage management of high-quality data. The technological advancement makes the data storage more accessible, cheaper and the convergence of these technologies seems to be more promising in the recent era. This book identified the innovative challenges in the industrial domains by integrating heterogeneous data sources such as structured data, semi-structures data, geo-spatial data, textual information, multimedia data, social networking data, etc. It promotes data-driven business modelling processes by adopting big data technologies in the manufacturing industry. Big data analytics is emerging as a promising discipline in the manufacturing industry to build the rigid industrial data platforms. Moreover, big data facilitates process automation in the complete lifecycle of product design and tracking. This book is an essential guide and reference since it synthesizes interdisciplinary theoretical concepts, definitions, and models, involved in smart manufacturing domain. It also provides real-world scenarios and applications, making it accessible to a wider interdisciplinary audience.FeaturesThe readers will get an overview about the smart manufacturing system which enables optimized manufacturing processes and benefits the users by increasing overall profitThe researchers will get insight about how the big data technology leverages in finding new associations, factors and patterns through data stream observations in real time smart manufacturing systemsThe industrialist can get an overview about the detection of defects in design, rapid response to market, innovative products to meet the customer requirement which can benefit their per capita income in better wayDiscusses technical viewpoints, concepts, theories, and underlying assumptions that are used in smart manufacturingInformation delivered in a user-friendly manner for students, researchers, industrial experts, and business innovators, as well as for professionals and practitioners

The significant objective of this edited book is to bridge the gap between smart manufacturing and big data by exploring the challenges and limitations. Companies employ big data technology in the manufacturing field to acquire data about the products. Manufacturing companies could gain a deep business insight by tracking customer details, monitoring fuel consumption, detecting product defects, and supply chain management. Moreover, the convergence of smart manufacturing and big data analytics currently suffers due to data privacy concern, short of qualified personnel, inadequate investment, long-term storage management of high-quality data. The technological advancement makes the data storage more accessible, cheaper and the convergence of these technologies seems to be more promising in the recent era. This book identified the innovative challenges in the industrial domains by integrating heterogeneous data sources such as structured data, semi-structures data, geo-spatial data, textual information, multimedia data, social networking data, etc. It promotes data-driven business modelling processes by adopting big data technologies in the manufacturing industry. Big data analytics is emerging as a promising discipline in the manufacturing industry to build the rigid industrial data platforms. Moreover, big data facilitates process automation in the complete lifecycle of product design and tracking. This book is an essential guide and reference since it synthesizes interdisciplinary theoretical concepts, definitions, and models, involved in smart manufacturing domain. It also provides real-world scenarios and applications, making it accessible to a wider interdisciplinary audience.FeaturesThe readers will get an overview about the smart manufacturing system which enables optimized manufacturing processes and benefits the users by increasing overall profitThe researchers will get insight about how the big data technology leverages in finding new associations, factors and patterns through data stream observations in real time smart manufacturing systemsThe industrialist can get an overview about the detection of defects in design, rapid response to market, innovative products to meet the customer requirement which can benefit their per capita income in better wayDiscusses technical viewpoints, concepts, theories, and underlying assumptions that are used in smart manufacturingInformation delivered in a user-friendly manner for students, researchers, industrial experts, and business innovators, as well as for professionals and practitioners

This book comprehensively conveys the theoretical and practical aspects of IoT and big data analytics with the solid contributions from practitioners as well as academicians. This book examines and expounds the unique capabilities of the big data analytics platforms in capturing, cleansing and crunching IoT device/sensor data in order to extricate actionable insights. A number of experimental case studies and real-world scenarios are incorporated in this book in order to instigate our book readers. This book Analyzes current research and development in the domains of IoT and big data analytics Gives an overview of latest trends and transitions happening in the IoT data analytics space Illustrates the various platforms, processes, patterns, and practices for simplifying and streamlining IoT data analytics The Internet of Things and Big Data Analytics: Integrated Platforms and Industry Use Cases examines and accentuates how the multiple challenges at the cusp of IoT and big data can be fully met. The device ecosystem is growing steadily. It is forecast that there will be billions of connected devices in the years to come. When these IoT devices, resource-constrained as well as resource-intensive, interact with one another locally and remotely, the amount of multi-structured data generated, collected, and stored is bound to grow exponentially. Another prominent trend is the integration of IoT devices with cloud-based applications, services, infrastructures, middleware solutions, and databases. This book examines the pioneering technologies and tools emerging and evolving in order to collect, pre-process, store, process and analyze data heaps in order to disentangle actionable insights.

This book presents the research into and application of machine learning in quantum computation, known as quantum machine learning (QML). It presents a comparison of quantum machine learning, classical machine learning, and traditional programming, along with the usage of quantum computing, toward improving traditional machine learning algorithms through case studies.In summary, the book: Covers the core and fundamental aspects of statistics, quantum learning, and quantum machines. Discusses the basics of machine learning, regression, supervised and unsupervised machine learning algorithms, and artificial neural networks. Elaborates upon quantum machine learning models, quantum machine learning approaches and quantum classification, and boosting. Introduces quantum evaluation models, deep quantum learning, ensembles, and QBoost. Presents case studies to demonstrate the efficiency of quantum mechanics in industrial aspects.This reference text is primarily written for scholars and researchers working in the fields of computer science and engineering, information technology, electrical engineering, and electronics and communication engineering.

This book presents the research into and application of machine learning in quantum computation, known as quantum machine learning (QML). It presents a comparison of quantum machine learning, classical machine learning, and traditional programming, along with the usage of quantum computing, toward improving traditional machine learning algorithms through case studies.In summary, the book: Covers the core and fundamental aspects of statistics, quantum learning, and quantum machines. Discusses the basics of machine learning, regression, supervised and unsupervised machine learning algorithms, and artificial neural networks. Elaborates upon quantum machine learning models, quantum machine learning approaches and quantum classification, and boosting. Introduces quantum evaluation models, deep quantum learning, ensembles, and QBoost. Presents case studies to demonstrate the efficiency of quantum mechanics in industrial aspects.This reference text is primarily written for scholars and researchers working in the fields of computer science and engineering, information technology, electrical engineering, and electronics and communication engineering.

The transformative impact of emerging technologies such as AI, blockchain, and machine learning on industries and societies, particularly in Africa, can drive sustainable development, improve governance, and address global challenges like climate change, economic inequality, and data privacy. Knowledge Graph and Semantic Web Technology based XAI offers readers a comprehensive study of these developments. Through real-world examples and practical insights, it demonstrates how AI and blockchain can solve pressing issues in such sectors as education, agriculture, and finance. This book emphasizes the potential of these technologies in fostering economic growth, improving transparency, and advancing social development in Africa. • Explores AI, blockchain, and machine learning in the context of Africa’s development • Highlights the role of emerging technologies in addressing global challenges • Discusses the applications of these technologies in various sectors • Provides practical examples and real‑world insights • Examines the risks, including cybersecurity and data privacy • Offers a balanced combination of technical depth and accessibility Knowledge Graph and Semantic Web Technology based XAI is for scholars, professionals, and policymakers interested in the role of emerging technologies in sustainable development, especially in Africa.

The transformative impact of emerging technologies such as AI, blockchain, and machine learning on industries and societies, particularly in Africa, can drive sustainable development, improve governance, and address global challenges like climate change, economic inequality, and data privacy. Knowledge Graph and Semantic Web Technology based XAI offers readers a comprehensive study of these developments. Through real-world examples and practical insights, it demonstrates how AI and blockchain can solve pressing issues in such sectors as education, agriculture, and finance. This book emphasizes the potential of these technologies in fostering economic growth, improving transparency, and advancing social development in Africa. • Explores AI, blockchain, and machine learning in the context of Africa’s development • Highlights the role of emerging technologies in addressing global challenges • Discusses the applications of these technologies in various sectors • Provides practical examples and real‑world insights • Examines the risks, including cybersecurity and data privacy • Offers a balanced combination of technical depth and accessibility Knowledge Graph and Semantic Web Technology based XAI is for scholars, professionals, and policymakers interested in the role of emerging technologies in sustainable development, especially in Africa.

COGNITIVE INTELLIGENCE AND BIG DATA IN HEALTHCARE Applications of cognitive intelligence, advanced communication, and computational methods can drive healthcare research and enhance existing traditional methods in disease detection and management and prevention. As health is the foremost factor affecting the quality of human life, it is necessary to understand how the human body is functioning by processing health data obtained from various sources more quickly. Since an enormous amount of data is generated during data processing, a cognitive computing system could be applied to respond to queries, thereby assisting in customizing intelligent recommendations. This decision-making process could be improved by the deployment of cognitive computing techniques in healthcare, allowing for cutting-edge techniques to be integrated into healthcare to provide intelligent services in various healthcare applications. This book tackles all these issues and provides insight into these diversified topics in the healthcare sector and shows the range of recent innovative research, in addition to shedding light on future directions in this area. Audience The book will be very useful to a wide range of specialists including researchers, engineers, and postgraduate students in artificial intelligence, bioinformatics, information technology, as well as those in biomedicine.

DIGITIZATION OF HEALTHCARE DATA USING BLOCKCHAINThe book gives a detailed description of the integration of blockchain technology for Electronic Health Records and provides the research challenges to consider in various disciplines such as supply chain, drug discovery, and data management.The aim of the book is to investigate the concepts of blockchain technology and its association with the recent development and advancements in the medical field. Moreover, it focuses on the integration of workflow strategies like NLP, and AI which could be adopted for boosting the clinical documentation and electronic healthcare records (EHR) usage by bringing down the physician EHR data entry. Also, the book covers the usage of smart contracts for securing patient records. Digitization of Healthcare Data Using Blockchain presents the practical implementations that deal with developing a web framework for building highly usable healthcare applications, a simple blockchain-powered EHR system.AudienceResearchers in information technology, artificial intelligence, electronics engineering, medical informatics, as well as policymakers and healthcare providers and management systems.

This book is essential for understanding the transformative integration of cyber-physical systems in smart grids, providing valuable insights that will shape the future of sustainable energy production and distribution. A novel modeling methodology that blends cyber and physical components is a significant advancement for future energy systems. A Cyber-Physical System (CPS) is an integrated component of physical microgrids that combines computers, wireless connections, and controls to create a holistic solution. As a result of cyber-physical systems, a new generation of engineering systems incorporating wireless communication has begun to emerge. Despite that there are various major CPS systems in use today, one of the most challenging sectors for implementation is the smart grid which aims to distribute dependable and efficient electric energy while maintaining a high level of global environmental sustainability. Smart grids incorporate advanced monitoring to ensure a secure, efficient energy supply, enhancing generator and distributor performance while offering consumers more choices. These systems aim to boost the capacity and responsiveness of energy production, transmission, distribution, and consumption. As renewable energy sources grow, traditional methods are being challenged, requiring cross-domain integration of energy systems and data. This book explores architectures and methods for integrating cutting-edge technology into the power grid for more sustainable energy production and distribution.

This new volume considers the use of smart technologies in commercial and hazardous vehicles, looking at the challenges and solutions to transportation issues that can be solved with such intelligent applications as artificial intelligence, Internet of Things, neural networks, blockchain, machine learning, big data, etc. The book illustrates the use these smart technologies for vehicle pedestrian detection, in the planning of smart cities for traffic patterns, for the improvement of transportation power stations, for smart railway cargo management systems, and more.

Blockchain and machine learning technologies can mitigate healthcare issues such as slow access to medical data, poor system interoperability, lack of patient agency, and data quality and quantity for medical research. Blockchain technology facilitates and secures the storage of information in such a way that doctors can see a patient's entire medical history, but researchers see only statistical data instead of any personal information. Machine learning can make use of this data to notice patterns and give accurate predictions, providing more support for the patients and also in research related fields where there is a need for accurate data to predict credible results.This book examines the application of blockchain technology and machine learning algorithms in various healthcare settings, covering the basics of the technologies and exploring how they can be used to improve clinical outcomes and improving the patient's experience. These topics are illustrated with reference to issues around the supply chain, drug verification, reimbursement, control access and clinical trials. Case studies are given for applications in the analysis of breast cancer, hepatitis C, and COVID-19.

The specific highlight of this book is focused on the application of integrated technologies in enhancing data models, better insights and discovery, intelligent predictions, smarter finance, smart retail, global verification, transparent governance, and innovative audit systems.

The specific highlight of this book is focused on the application of integrated technologies in enhancing data models, better insights and discovery, intelligent predictions, smarter finance, smart retail, global verification, transparent governance, and innovative audit systems.

The book discusses how Unmanned Aerial Vehicles (UAVs) can leverage the sub-6 GHz massive MIMO to address cell selection and interference issues in future wireless networks.