Manju Khari – författare

Internet of Things in Biomedical Engineering presents the most current research in Internet of Things (IoT) applications for clinical patient monitoring and treatment. The book takes a systems-level approach for both human-factors and the technical aspects of networking, databases and privacy. Sections delve into the latest advances and cutting-edge technologies, starting with an overview of the Internet of Things and biomedical engineering, as well as a focus on 'daily life.' Contributors from various experts then discuss 'computer assisted anthropology,' CLOUDFALL, and image guided surgery, as well as bio-informatics and data mining.

This comprehensive coverage of the industry and technology is a perfect resource for students and researchers interested in the topic.

Presents recent advances in IoT for biomedical engineering, covering biometrics, bioinformatics, artificial intelligence, computer vision and various network applications Discusses big data and data mining in healthcare and other IoT based biomedical data analysis Includes discussions on a variety of IoT applications and medical information systems Includes case studies and applications, as well as examples on how to automate data analysis with Perl R in IoT

Handbook of Data Science Approaches for Biomedical Engineering covers the research issues and concepts of biomedical engineering progress and the ways they are aligning with the latest technologies in IoT and big data. In addition, the book includes various real-time/offline medical applications that directly or indirectly rely on medical and information technology. Case studies in the field of medical science, i.e., biomedical engineering, computer science, information security, and interdisciplinary tools, along with modern tools and the technologies used are also included to enhance understanding.

Today, the role of Big Data and IoT proves that ninety percent of data currently available has been generated in the last couple of years, with rapid increases happening every day. The reason for this growth is increasing in communication through electronic devices, sensors, web logs, global positioning system (GPS) data, mobile data, IoT, etc.

Provides in-depth information about Biomedical Engineering with Big Data and Internet of Things Includes technical approaches for solving real-time healthcare problems and practical solutions through case studies in Big Data and Internet of Things Discusses big data applications for healthcare management, such as predictive analytics and forecasting, big data integration for medical data, algorithms and techniques to speed up the analysis of big medical data, and more

The Web of Things (WoT) is a concept that describes approaches, programming tools and software architectural systems, which interface networks of real-world objects with the World Wide Web. The book is organized into 11 chapters, each focusing on a unique wireless technological aspect of the Web of Things, and it aims to comprehensively cover each of its various applications, including: A strong emphasis on WoT problems and solutions, identifying the main open issues, innovations and latest technologies behind WoT A blend of theoretical and simulation-based problems for better understanding of the concepts behind WoT Various exemplifying applications in which the use of WoT is very attractive and an inspiration for future applicationsThe book will be useful to researchers, software developers and undergraduate and postgraduate students, as well as 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.

The Web of Things (WoT) is a concept that describes approaches, programming tools and software architectural systems, which interface networks of real-world objects with the World Wide Web. The book is organized into 11 chapters, each focusing on a unique wireless technological aspect of the Web of Things, and it aims to comprehensively cover each of its various applications, including: A strong emphasis on WoT problems and solutions, identifying the main open issues, innovations and latest technologies behind WoT A blend of theoretical and simulation-based problems for better understanding of the concepts behind WoT Various exemplifying applications in which the use of WoT is very attractive and an inspiration for future applicationsThe book will be useful to researchers, software developers and undergraduate and postgraduate students, as well as practitioners.

This handbook provides a computational perspective on green computing and blockchain technologies. It presents not only how to identify challenges using a practical approach but also how to develop strategies for addressing industry challenges.Handbook of Green Computing and Blockchain Technologies takes a practical-oriented approach, including solved examples and highlights standardization, industry bodies, and initiatives. Case studies provide a deeper understanding of blockchain and are related to real-time scenarios. The handbook analyzes current research and development in green computing and blockchain analytics, studies existing related standards and technologies, and provides results on implementation, challenges, and issues in today’s society.FEATURES Analyzes current research developments in green computing and blockchain analytics Provides an analysis of implementation challenges and solutions Offers innovations in the decentralization process for the application of blockchain in areas such as healthcare, government services, agriculture, supply chain, financial, ecommerce, and more Discusses the impact of this technology on people’s lives, the way they work and learn, and highlights standardization, industry bodies, and initiativesThis handbook will benefit researchers, software developers, and undergraduate and postgraduate students in industrial systems, manufacturing, information technology, computer science, manufacturing, communications, and electrical engineering.

This handbook provides a computational perspective on green computing and blockchain technologies. It presents not only how to identify challenges using a practical approach but also how to develop strategies for addressing industry challenges.Handbook of Green Computing and Blockchain Technologies takes a practical-oriented approach, including solved examples and highlights standardization, industry bodies, and initiatives. Case studies provide a deeper understanding of blockchain and are related to real-time scenarios. The handbook analyzes current research and development in green computing and blockchain analytics, studies existing related standards and technologies, and provides results on implementation, challenges, and issues in today’s society.FEATURES Analyzes current research developments in green computing and blockchain analytics Provides an analysis of implementation challenges and solutions Offers innovations in the decentralization process for the application of blockchain in areas such as healthcare, government services, agriculture, supply chain, financial, ecommerce, and more Discusses the impact of this technology on people’s lives, the way they work and learn, and highlights standardization, industry bodies, and initiativesThis handbook will benefit researchers, software developers, and undergraduate and postgraduate students in industrial systems, manufacturing, information technology, computer science, manufacturing, communications, and electrical engineering.

There are a lot of e-business security concerns. Knowing about e-business security issues will likely help overcome them. Keep in mind, companies that have control over their e-business are likely to prosper most. In other words, setting up and maintaining a secure e-business is essential and important to business growth. This book covers state-of-the art practices in e-business security, including privacy, trust, security of transactions, big data, cloud computing, social network, and distributed systems.

Most of the business sectors consider the Digital Twin concept as the next big thing in the industry. A current state analysis of their digital counterparts helps in the prediction of the future of physical assets. Organizations obtain better insights on their product performance through the implementation of Digital Twins, and the applications of the technology are frequently in sectors such as manufacturing, automobile, retail, health care, smart cities, industrial IoT, etc. This book explores the latest developments and covers the significant challenges, issues, and advances in Digital Twin Technology. It will be an essential resource for anybody involved in related industries, as well as anybody interested in learning more about this nascent technology.This book includes:The future, present, and past of Digital Twin Technology. Digital twin technologies across the Internet of Drones, which developed various perceptive and autonomous capabilities, towards different control strategies such as object detection, navigation, security, collision avoidance, and backup. These approaches help to deal with the expansive growth of big data solutions. The recent digital twin concept in agriculture, which offers the vertical framing by IoT installation development to enhance the problematic food supply situation. It also allows for significant energy savings practices. It is highly required to overcome those challenges in developing advanced imaging methods of disease detection & prediction to achieve more accuracy in large land areas of crops.The welfare of upcoming archetypes such as digitalization in forensic analysis. The ideas of digital twin have arisen to style the corporeal entity and associated facts reachable software and customers over digital platforms.Wind catchers as earth building: Digital Twins vs. green sustainable architecture.

Most of the business sectors consider the Digital Twin concept as the next big thing in the industry. A current state analysis of their digital counterparts helps in the prediction of the future of physical assets. Organizations obtain better insights on their product performance through the implementation of Digital Twins, and the applications of the technology are frequently in sectors such as manufacturing, automobile, retail, health care, smart cities, industrial IoT, etc. This book explores the latest developments and covers the significant challenges, issues, and advances in Digital Twin Technology. It will be an essential resource for anybody involved in related industries, as well as anybody interested in learning more about this nascent technology.This book includes:The future, present, and past of Digital Twin Technology. Digital twin technologies across the Internet of Drones, which developed various perceptive and autonomous capabilities, towards different control strategies such as object detection, navigation, security, collision avoidance, and backup. These approaches help to deal with the expansive growth of big data solutions. The recent digital twin concept in agriculture, which offers the vertical framing by IoT installation development to enhance the problematic food supply situation. It also allows for significant energy savings practices. It is highly required to overcome those challenges in developing advanced imaging methods of disease detection & prediction to achieve more accuracy in large land areas of crops.The welfare of upcoming archetypes such as digitalization in forensic analysis. The ideas of digital twin have arisen to style the corporeal entity and associated facts reachable software and customers over digital platforms.Wind catchers as earth building: Digital Twins vs. green sustainable architecture.

Many governments around the world are calling for the use of biometric systems to provide crucial societal functions, consequently making it an urgent area for action. The current performance of some biometric systems in terms of their error rates, robustness, and system security may prove to be inadequate for large-scale applications to process millions of users at a high rate of throughput.This book focuses on fusion in biometric systems. It discusses the present level, the limitations, and proposed methods to improve performance. It describes the fundamental concepts, current research, and security-related issues. The book will present a computational perspective, identify challenges, and cover new problem-solving strategies, offering solved problems and case studies to help with reader comprehension and deep understanding. This book is written for researchers, practitioners, both undergraduate and post-graduate students, and those working in various engineering fields such as Systems Engineering, Computer Science, Information Technology, Electronics, and Communications.

Many governments around the world are calling for the use of biometric systems to provide crucial societal functions, consequently making it an urgent area for action. The current performance of some biometric systems in terms of their error rates, robustness, and system security may prove to be inadequate for large-scale applications to process millions of users at a high rate of throughput.This book focuses on fusion in biometric systems. It discusses the present level, the limitations, and proposed methods to improve performance. It describes the fundamental concepts, current research, and security-related issues. The book will present a computational perspective, identify challenges, and cover new problem-solving strategies, offering solved problems and case studies to help with reader comprehension and deep understanding. This book is written for researchers, practitioners, both undergraduate and post-graduate students, and those working in various engineering fields such as Systems Engineering, Computer Science, Information Technology, Electronics, and Communications.

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 provides an in-depth exploration of the integration of cloud and edge computing in artificial intelligence, addressing critical topics such as hybrid architectures, real-time data processing, security, and practical artificial intelligence applications.Offers a detailed exploration of foundational concepts and practical applications of edge artificial intelligence, making it a comprehensive resource for understanding this emerging technology.Featuring real-world case studies from various sectors such as smart cities, industrial applications, healthcare, and agriculture, it provides practical insights into how edge artificial intelligence is being applied.Discusses the latest trends and future directions in edge artificial intelligence, including advancements in edge hardware and software, federated learning, and the potential impact of blockchain technology.Addresses critical issues like security threats, privacy-preserving techniques, and the importance of explainable artificial intelligence.Highlights case studies and real-world examples to illustrate the tangible benefits of edge artificial intelligence.This book is primarily written for senior undergraduate students, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.

The book contains several new concepts, techniques, applications and case studies for cyber securities in parallel and distributed computingThe main objective of this book is to explore the concept of cybersecurity in parallel and distributed computing along with recent research developments in the field. Also included are various real-time/offline applications and case studies in the fields of engineering and computer science and the modern tools and technologies used. Information concerning various topics relating to cybersecurity technologies is organized within the sixteen chapters of this book.Some of the important topics covered include: Research and solutions for the problem of hidden image detectionSecurity aspects of data mining and possible solution techniquesA comparative analysis of various methods used in e-commerce security and how to perform secure payment transactions in an efficient mannerBlockchain technology and how it is crucial to the security industrySecurity for the Internet of ThingsSecurity issues and challenges in distributed computing security such as heterogeneous computing, cloud computing, fog computing, etc.Demonstrates the administration task issue in unified cloud situations as a multi-target enhancement issue in light of securityExplores the concepts of cybercrime and cybersecurity and presents the statistical impact it is having on organizationsSecurity policies and mechanisms, various categories of attacks (e.g., denial-of-service), global security architecture, along with distribution of security mechanismsSecurity issues in the healthcare sector with existing solutions and emerging threats.

WIRELESS COMMUNICATION SECURITY Presenting the concepts and advances of wireless communication security, this volume, written and edited by a global team of experts, also goes into the practical applications for the engineer, student, and other industry professionals. Covering a broad range of topics in wireless communication security and its solutions, this outstanding new volume is of great interest to engineers, scientists, and students from a variety of backgrounds and interests. Focusing on providing the theory of wireless communication within the framework of its practical applications, the contributors take on a wealth of topics, integrating seemingly diverse areas under one cover. Wireless Communication Security has been divided into five units. The first unit presents the different protocols and standards for developing a real-time wireless communication security. The second unit presents different widely accepted networks, which are the core of wireless communication security. Unit three presents the various device and network controlling methodologies. Unit four presents the various high performance and computationally efficient algorithms for efficient and scalable implementation of network protocols, and the last unit presents the leading innovations and variety of usage of wireless communication security. Valuable as a learning tool for beginners in this area as well as a daily reference for engineers and scientists working in these areas, this is a must-have for any library.

There are a lot of e-business security concerns. Knowing about e-business security issues will likely help overcome them. Keep in mind, companies that have control over their e-business are likely to prosper most. In other words, setting up and maintaining a secure e-business is essential and important to business growth. This book covers state-of-the art practices in e-business security, including privacy, trust, security of transactions, big data, cloud computing, social network, and distributed systems.

This new volume provides an abundance of information on new biomedical applications being used today. The book covers a wide range of concepts and technologies, discussing such modern technological methods as the Internet of Things, e-pills, biomedical sensors, support vector machines, wireless devices, image and signal processing in e-health, and machine learning. It also includes a discussion on software implementation for the devices used in biomedical applications. The different types of antennas, including antennas using RF energy harvesting for biomedical applications, are covered as well.

This new volume provides an abundance of information on new biomedical applications being used today. The book covers a wide range of concepts and technologies, discussing such modern technological methods as the Internet of Things, e-pills, biomedical sensors, support vector machines, wireless devices, image and signal processing in e-health, and machine learning. It also includes a discussion on software implementation for the devices used in biomedical applications. The different types of antennas, including antennas using RF energy harvesting for biomedical applications, are covered as well.

Health Informatics: Technologies and applications covers technological advances in healthcare that contribute to precision medicine and early detection of diseases. The editors explore the evolution of medical devices with attention to data management, patient safety and cost effectiveness.Discussing health data and big data analytics for healthcare information, the editors also look at the application of artificial intelligence in the healthcare arena, examining the concepts of machine learning for image sensing and the importance of feature selection, class imbalance, model robustness, and scalability.With the advancement of telemedicine, the book will also examine cloud computing systems and the internet of medical things (IoMT), with particular reference to cybersecurity concerns and the reliable management of electronic medical records.The editors look at deploying these technologies for improved detection and therapeutic considerations for neurological and physiological conditions.The book will be suitable for an audience of computer scientists and engineers particularly researchers working in healthcare technologies, AI/ML, computer science, data analysis or IoMT.

This book discusses emerging technologies in the field of the Internet of Things and big data, an area that will be scaled in next two decades. Written by a team of leading experts, it is the only book focusing on the broad areas of both the Internet of things and big data. The thirteen chapters present real-time experimental methods and theoretical explanations, as well as the implementation of these technologies through various applications.Offering a blend of theory and hands-on practices, the book enables graduate, postgraduate and research students who are involved in real-time project scaling techniques to understand projects and their execution. It is also useful for senior computer students, researchers and industry workers who are involved in experimenting with the Internet of Things and big data technologies, helping them to solve the real-time problem. Moreover, the chapters covering cutting-edge technologies help multidisciplinary researchers who are bridging the gap of two different outset real-time problems.

This book provides readers with a comprehensive and recent exposition in deep learning and its multidisciplinary applications, with a concentration on advances of deep learning architectures. The book discusses various artificial intelligence (AI) techniques based on deep learning architecture with applications in natural language processing, semantic knowledge, forecasting and many more.  The authors shed light on various applications that can benefit from the use of deep learning in pattern recognition, person re-identification in surveillance videos, action recognition in videos, image and video captioning. The book also highlights how deep learning concepts can be interwoven with more modern concepts to yield applications in multidisciplinary fields.Presents a comprehensive look at deep learning and its multidisciplinary applications, concentrating on advances of deep learning architectures;Includes a survey of deep learning problems and solutions, identifying the main open issues, innovations and latest technologies;Shows industrial deep learning in practice with examples/cases, efforts, challenges, and strategic approaches.

This book provides readers with a comprehensive and recent exposition in deep learning and its multidisciplinary applications, with a concentration on advances of deep learning architectures. The book discusses various artificial intelligence (AI) techniques based on deep learning architecture with applications in natural language processing, semantic knowledge, forecasting and many more.  The authors shed light on various applications that can benefit from the use of deep learning in pattern recognition, person re-identification in surveillance videos, action recognition in videos, image and video captioning. The book also highlights how deep learning concepts can be interwoven with more modern concepts to yield applications in multidisciplinary fields.Presents a comprehensive look at deep learning and its multidisciplinary applications, concentrating on advances of deep learning architectures;Includes a survey of deep learning problems and solutions, identifying the main open issues, innovations and latest technologies;Shows industrial deep learning in practice with examples/cases, efforts, challenges, and strategic approaches.

This book provides awareness of different evolutionary methods used for automatic generation and optimization of test data in the field of software testing. While the book highlights on the foundations of software testing techniques, it also focuses on contemporary topics for research and development. This book covers the automated process of testing in different levels like unit level, integration level, performance level, evaluation of testing strategies, testing in security level, optimizing test cases using various algorithms, and controlling and monitoring the testing process etc. This book aids young researchers in the field of optimization of automated software testing, provides academics with knowledge on the emerging field of AI in software development, and supports universities, research centers, and industries in new projects using AI in software testing.​Supports the advancement in the artificial intelligence used in software development;Advances knowledge on artificial intelligence based metaheuristic approach in software testing;Encourages innovation in traditional software testing field using recent artificial intelligence.·

This book provides awareness of different evolutionary methods used for automatic generation and optimization of test data in the field of software testing. While the book highlights on the foundations of software testing techniques, it also focuses on contemporary topics for research and development. This book covers the automated process of testing in different levels like unit level, integration level, performance level, evaluation of testing strategies, testing in security level, optimizing test cases using various algorithms, and controlling and monitoring the testing process etc. This book aids young researchers in the field of optimization of automated software testing, provides academics with knowledge on the emerging field of AI in software development, and supports universities, research centers, and industries in new projects using AI in software testing.​Supports the advancement in the artificial intelligence used in software development;Advances knowledge on artificial intelligence based metaheuristic approach in software testing;Encourages innovation in traditional software testing field using recent artificial intelligence.·

This book constitutes the refereed proceedings of the First International Conference on Next-Gen Computing and Communication Systems, ICNCS 2025, held in Jaipur, India, during April 18-19, 2025.The 8 full papers presented in this volume were carefully reviewed and selected from 134 submissions.They are organized into the following topical sections: Next-Gen Computing; Next-Gen Networking and Communication Systems; and Emerging Applications and Use Cases.