Balamurugan Balusamy – författare

Smart Energy and Electric Power Systems: Current Trends and New Intelligent Perspectives�reviews key applications of intelligent algorithms and machine learning techniques to increasingly complex and data-driven power systems with distributed energy resources to enable evidence-driven decision-making and mitigate catastrophic power shortages. The book reviews foundations towards the integration of machine learning and smart power systems before addressing key challenges and issues. The work then explores AI- and ML-informed techniques to rebalancing of supply and demand. Methods discussed include distributed energy resources and prosumer markets, electricity demand prediction, component fault detection, and load balancing.

Security solutions are introduced, along with potential solutions to cyberattacks, security data detection and critical loads in power systems. The work closes with a lengthy discussion, informed by case studies, on integrating AI and ML into the modern energy sector.

Helps improve the prediction capability of AI algorithms to make evidence-based decisions in the smart supply of electricity, including load shedding Focuses on how to integrate AI and ML into the energy sector in the real-world, with many chapters accompanied by case studies Addresses a number of proven AI and ML- informed techniques in rebalancing supply and demand

Blockchain-Based Systems for a Paradigm Shift in the Energy Grid explores the technologies and tools to utilize blockchain for energy grids and assists professionals and researchers to find alternative solutions for the future of the energy sector.

The focus of this globally edited book is on the application of blockchain technology and the balance between supply and demand for energy and where it is achievable. Looking at the integration of blockchain and how it will make the network resistant to any failure in sub-components, this book has very clearly explores the areas of energy sector that need in-depth study of Blockchain for expanding energy markets. Meeting the demands of energy by local trading, verifying use of green energy certificates and providing a greater understanding of smart energy grids and Blockchain use cases.

Exhaustively exploring the use of Blockchain for energy, this reference useful for all those in the energy industry looking to avoid disruption in the grid and sustain and control successful flow of electricity.

Methods and techniques of Blockchain-based trading and payments are included Provides process diagrams in techniques and balancing demand and supply Internet of Energy and its architecture for the future energy sector is explained

Digital Twin for Smart Manufacturing: Emerging Approaches and Applications provides detailed descriptions on how to integrate and optimize novel digital technologies for smart manufacturing. The book discusses digital twins, which combine the industrial internet of things, artificial intelligence, machine learning and software analytics with spatial network graphs to create living digital simulation models that update and change as their physical counterparts change. In addition, they provide an effective way to integrate technologies like cyber-physical systems into a smart manufacturing system, potentially optimizing the entire business process and operating procedure of the manufacturing firm.

Drawing on the latest research, the book addresses the topics and technologies key to successful implementation of a smart manufacturing system, including augmented and virtual reality, big data and energy management. Broader subjects such as additive manufacturing and robotics are also covered in this context, covering every aspect of production.

Includes detailed case studies that show how digital twins have been successfully implemented Shows how digital twins can be used to improve sustainability through superior energy usage management Outlines potential future uses of the digital twin, thus pointing the way for future research directions

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 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.

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.

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.

Metaverse Technologies in Healthcare focuses on data analysis, utilizing the possibilities of data to increase the effectiveness of healthcare organizations. As healthcare services aim to maintain the physical, mental, social and emotional well-being of human lives while the Metaverse is a blend of technological trends- Artificial Intelligence (AI), Augmented Reality (AR) and Virtual Reality (VR), collectively, they can deliver treatments and medicines, lower costs, and substantially enhance patient outcomes. The book redefines the digital health experience and describes the advantages of the Metaverse-based NFT technology in the healthcare sector, facilitating NFT avatars to interact with targeted audiences, and more.

Shows the potential of digital experiences on the healthcare sectorFocuses on the leading channels fueling the digital health space, such as Telemedicine, Digital Twins, Block chain, Internet of Things, and Robotics, providing new directions in this sectorProvides guidance to healthcare companies on how to augment their Digital Roadmaps with personalized care

Self-powered Sensors: A Path to Wearable Electronics features recent developments in chemical, photonic, pharmaceutical, microbiological, biomimetic, and bio-inspired approaches for MEMS/NEMS and medicinal self-powered sensors. Unconventional nanomaterial sensors driven by self-sufficient energy are given a contemporary review, with a focus on the categorization of energy sources and comparisons of research involving self-powered solar, piezoresistive, triboelectric, and thermodynamic technologies. This book also focuses on the different techniques, materials, comparisons of fabrication of self-powered sensors as well as thermoelectric self-powered sensors and its implantable applications.Presents state-of-the-art technologies and advancements in the design and application of self-powered sensorsExamines the advantages and disadvantages of self-powered nanomaterial sensors in terms of energy collecting techniques and sensing applicationsReviews the incorporation of self-operating devices and novel uses for neuromorphic sensors

Computational Intelligence in Sustainable Computing and Optimization: Trends and Applications focuses on developing and evolving advanced computational intelligence algorithms for the analysis of data involved in applications, such as agriculture, biomedical systems, bioinformatics, business intelligence, economics, disaster management, e-learning, education management, financial management, and environmental policies. The book presents research in sustainable computing and optimization, combining methods from engineering, mathematics, artificial intelligence, and computer science to optimize environmental resourcesComputational intelligence in the field of sustainable computing combines computer science and engineering in applications ranging from Internet of Things (IoT), information security systems, smart storage, cloud computing, intelligent transport management, cognitive and bio-inspired computing, and management science. In addition, data intelligence techniques play a critical role in sustainable computing. Recent advances in data management, data modeling, data analysis, and artificial intelligence are finding applications in energy networks and thus making our environment more sustainable.Presents computational, intelligence-based data analysis for sustainable computing applications such as pattern recognition, biomedical imaging, sustainable cities, sustainable transport, sustainable agriculture, and sustainable financial managementDevelops research in sustainable computing and optimization, combining methods from engineering, mathematics, and computer science to optimize environmental resourcesIncludes three foundational chapters dedicated to providing an overview of computational intelligence and optimization techniques and their applications for sustainable computing

Emerging Trends and Applications of Deep Learning for Biomedical Data Analysis introduces the latest emerging trends and applications of deep learning in biomedical data analysis. This book delves into various use cases where deep learning is applied in industrial, social, and personal contexts within the biomedical domain. By gaining a comprehensive understanding of deep learning in biomedical data analysis, readers will develop the skills to critically evaluate research papers, methodologies, and emerging trends. In 11 chapters, this book provides insights into the fundamentals of the latest research trends in the applications of deep learning in biosciences. With several case studies and use cases, it familiarizes the reader with a comprehensive understanding of deep learning algorithms, architectures, and methodologies speci cally applicable to biomedical data analysis. This title is an ideal reference for researchers across the biomedical sciences.Provides a succinct overview of the cutting-edge technologies that are altering disease diagnosis, patient monitoring, and medical researchBridges the gap between biomedical engineering and deep learning by providing a comprehensive resource for comprehending the intersection of these disciplinesInvestigates how deep learning may change healthcare by providing new insights, diagnostics, and treatments via intelligent biomedical systems

AI-Driven Cybersecurity for Intelligent Healthcare Systems explores the intersection between AI, cybersecurity, and healthcare. The book offers detailed insights into the unique cybersecurity challenges faced by the healthcare sector and the role of AI in addressing these challenges. It presents case studies and real-world applications to illustrate the effectiveness of these solutions and highlights the significance of data privacy in healthcare and methods to ensure secure data sharing and storage. Topics such as federated learning, homomorphic encryption, and blockchain technology are covered to demonstrate how AI can enhance data security without compromising patient privacy.This book will be an essential resource for anyone involved in the healthcare industry, offering practical solutions and fostering a more in-depth understanding of how AI can revolutionize cybersecurity in healthcare.Includes case studies and real-world applications to illustrate the effectiveness of intelligent cybersecurity solutionsDiscusses the increasing integration of artificial intelligence (AI) in healthcare systems, highlighting its role in enhancing medical diagnosis, treatment planning, and patient careFocuses on advanced techniques for enhancing data security while maintaining patient privacy

Multilevel Quantum Metaheuristics: Applications in Data Exploration explores the most recent advances in hybrid quantum-inspired algorithms. Combining principles of quantum mechanics with metaheuristic techniques for efficient data optimization, this book examines multilevel quantum systems characterized by qudits and higher-level quantum states as more robust alternatives to conventional bilevel quantum approaches. It introduces novel multilevel applications of quantum metaheuristics for addressing optimization problems in areas including function optimization, data analysis, scheduling, and signal processing. The book also showcases real-world examples, case studies, and contributions that emphasize the effectiveness of proposed multilevel techniques over existing bilevel methods. Researchers, professionals, and engineers working on intelligent computing, quantum computing, data processing, clustering, and analysis, and those interested in the synergies between quantum computing, metaheuristics, and multilevel quantum systems for enhanced data exploration and analysis will find this book to be of great value.Provides insights into the future of quantum-inspired optimization by covering recent trends and mathematical techniquesAdvances knowledge of evolving time-efficient hybrid quantum algorithms that leverage the processing capabilities of emerging qudit-based paradigmsPresents in-depth analysis of quantum mechanical principles with special reference to multilevel quantum states

Applied Mathematical Modelling for Biomedical Robotics and Wearable Devices delves into the innovative convergence of mathematical frameworks and biomedical engineering. The book begins by exploring how advanced mathematical modelling underpins the development and optimization of robotic systems and wearable technologies tailored for medical applications. With a strong emphasis on practical implementation, it serves as a bridge between theoretical concepts and real-world engineering challenges in the healthcare sector. Readers will gain insights into the transformative role of mathematical techniques that drive precision, functionality, and human-centric design in cutting-edge medical technologies.The book also covers interdisciplinary applications, integrating domains like biomechanics, sensor technology, and data analytics. By highlighting case studies and real-world scenarios, it showcases practical advancements in wearable devices that monitor health metrics and robotic systems that assist in surgical procedures.Examines the role of applied mathematical modeling in the design, analysis, and optimization of biomedical robots and wearable devicesProvides an insightful exploration of cutting-edge developments in robotics and wearable devicesBridges the gap between the areas of mathematics, engineering, and healthcare

AI-Enabled Sustainable Healthcare: Demystifying Secure Quantum Blockchain explores the convergence of quantum computing, blockchain technology, and artificial intelligence in the context of healthcare. In today's rapidly evolving technological landscape, traditional healthcare systems face challenges related to data security, interoperability, and the efficient utilization of patient information. The emergence of quantum computing, blockchain, and AI presents unprecedented opportunities to overcome these challenges and revolutionize healthcare delivery. This book provides a clear and accessible overview of these complex technologies and their potential applications in healthcare. By demystifying these concepts and illustrating their real-world implications, the book equips readers with the knowledge and insights needed to navigate the intersection of technology and healthcare effectively. Furthermore, as the demand for secure, transparent, and sustainable healthcare solutions continues to grow, there is an urgent need for informed discussions and innovative approaches in this field.Allows readers to grasp the interconnectedness of the technologies and their potential to revolutionize various aspects of healthcare delivery, from data security to personalized treatmentExplores the ethical and sustainability implications of integrating emerging technologies into healthcare systems Includes real-world case studies and examples, demonstrating how emerging technologies can be applied to improve healthcare outcomes and efficiency

Quantum Cryptography and Annealing for Securing Industrial IoT focuses on the rapidly evolving field of quantum security solutions for Industrial Internet of Things (IIoT) platforms, emphasizing the critical intersection of quantum cryptography, post-quantum cryptography, and their practical applications in IIoT. The book’s primary objective is to drive advancements that significantly intersect quantum cryptography in securing IIoT devices, elevate secure IIoT infrastructures, and optimize the overall delivery. Distinguishing itself by prioritizing practical applications, it offers a nuanced perspective on how technological integrations in quantum cryptosystems are actively employed in real-world scenarios. The authors meticulously examine the role of quantum cryptosystems in the design, analysis, and optimization of IIoT-specific hardware, covering their resilience to physical and side-channel attacks and evaluating performance. This book strikes a balance between theoretical concepts and practical applications, providing insights into the challenges and solutions encountered in applying quantum cryptographical principles to IIoT engineering problems.Presents clear, concise, and reader-friendly quantum cryptographical concepts through the use of accessible language, diagrams, and examples to enhance the learning experienceIncludes real-world examples and case studies, demonstrating the practical applications of quantum cryptographical concepts in the design and development of industrial robots and IIoT devicesCaters to a diverse audience with backgrounds in mathematics, engineering, cybersecurity, quantum computing, and industrial engineering, making the content accessible to a broad range of readers

Lightweight, Real-time Deep Learning Models for Healthcare Applications addresses the pressing need for deploying efficient artificial intelligence models in clinical environments constrained by limited computational resources. As AI adoption accelerates in healthcare, this reference targets the gap between advanced deep learning research and practical real-time applications, emphasizing model optimization, privacy, and regulatory compliance. The content comprehensively covers model compression techniques such as pruning, quantization, knowledge distillation, and neural architecture search, alongside federated learning frameworks and real-time inference optimization. Detailed chapters present hardware-aware strategies, security considerations, continuous learning, and regulatory validation. The book also provides extensive case studies and implementation blueprints demonstrating practical deployment on devices like Raspberry Pi, NVIDIA Jetson, and mobile health platforms. This book benefits researchers, clinicians, and healthcare technology professionals by offering practical solutions to develop, validate, and implement AI models that maintain diagnostic accuracy while meeting clinical constraints. It equips students and educators with theoretical foundations and hands-on examples to foster innovation in biomedical AI, ultimately enhancing diagnostic capabilities and patient care in diverse healthcare settings.Provides end-to-end case studies with deployment blueprints for healthcare AI applicationsExplores advanced model compression and optimization techniques tailored for medical useIncludes compliance and ethical considerations for real-time AI in clinical environmentsDelivers practical methodologies for deploying AI on resource-constrained medical devicesCovers federated learning and privacy-preserving AI for multi-institutional healthcare networks

This book presents a framework for integrating blended learning and massive open online courses (MOOCs) in the Indian education system. It argues that blended teaching and learning is the most suitable approach to education in a post-COVID-19 world. Drawing on case studies used in blended learning practices around the world, the book provides ample resources for beginners to improvise the spread of knowledge around information technology in higher education. It discusses various concepts such as flip learning in blended learning models and examines the self-assessment tools and structures it offers to institutions for building competencies.In addition to addressing the challenges and opportunities of adopting the digital mode of teaching, the book also offers techniques and concepts helpful for designing MOOCs. It covers concepts such as curriculum designing, content flow, teaching behavior, and evaluation patterns, which are important aspects of online teaching. An indispensable guide to navigating the shift from offline to online teaching, this book will be of interest to students, teachers, and researchers of education, education technology, digital education, and information technology. It will also be useful to policymakers, educational institutions, EdTech start-ups, NGOs in the education sector, and online education centers.

Object Detection with Deep Learning Models discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its applications to computer vision, illustrating them using key topics, including object detection, face analysis, 3D object recognition, and image retrieval.The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in deep learning, computer vision and beyond and can also be used as a reference book. The comprehensive comparison of various deep-learning applications helps readers with a basic understanding of machine learning and calculus grasp the theories and inspires applications in other computer vision tasks.Features:A structured overview of deep learning in object detectionA diversified collection of applications of object detection using deep neural networksEmphasize agriculture and remote sensing domainsExclusive discussion on moving object detection

Legal Analytics: The Future of Analytics in Law navigates the crisscrossing of intelligent technology and the legal field in building up a new landscape of transformation. Legal automation navigation is multidimensional, wherein it intends to construct streamline communication, approval, and management of legal tasks. The evolving environment of technology has emphasized the need for better automation in the legal field from time to time, although legal scholars took long to embrace information revolution of the legal field.• Describes the historical development of law and automation.• Analyzes the challenges and opportunities in law and automation.• Studies the current research and development in the convergence of law, artificial intelligence, and legal analytics.• Explores the recent emerging trends and technologies that are used by various legal systems globally for crime prediction and prevention.• Examines the applicability of legal analytics in forensic investigation.• Investigates the impact of legal analytics tools and techniques in judicial decision making.• Analyzes deep learning techniques and their scope in accelerating legal analytics in developed and developing countries.• Provides an in-depth analysis of implementation, challenges, and issues in society related to legal analytics.This book is primarily aimed at graduates and postgraduates in law and technology, computer science, and information technology. Legal practitioners and academicians will also find this book helpful.

The book emphasizes the predictive models of Big Data, Genetic Algorithm, and IoT with a case study. The book illustrates the predictive models with integrated fuel consumption models for smart and safe traveling. The text is a coordinated amalgamation of research contributions and industrial applications in the field of Intelligent Transportation Systems. The advanced predictive models and research results were achieved with the case studies, deployed in real transportation environments.Features: Provides a smart traffic congestion avoidance system with an integrated fuel consumption model. Predicts traffic in short-term and regular. This is illustrated with a case study. Efficient Traffic light controller and deviation system in accordance with the traffic scenario. IoT based Intelligent Transport Systems in a Global perspective. Intelligent Traffic Light Control System and Ambulance Control System. Provides a predictive framework that can handle the traffic on abnormal days, such as weekends, festival holidays. Bunch of solutions and ideas for smart traffic development in smart cities. This book focuses on advanced predictive models along with offering an efficient solution for smart traffic management system. This book will give a brief idea of the available algorithms/techniques of big data, IoT, and genetic algorithm and guides in developing a solution for smart city applications. This book will be a complete framework for ITS domain with the advanced concepts of Big Data Analytics, Genetic Algorithm and IoT.This book is primarily aimed at IT professionals. Undergraduates, graduates and researchers in the area of computer science and information technology will also find this book useful.

The book IoT and Big Data Analytics (IoT-BDA) for Smart Cities – A Global Perspective, emphasizes the challenges, architectural models, and intelligent frameworks with smart decisionmaking systems using Big Data and IoT with case studies. The book illustrates the benefits of Big Data and IoT methods in framing smart systems for smart applications. The text is a coordinated amalgamation of research contributions and industrial applications in the field of smart cities.Features:Provides the necessity of convergence of Big Data Analytics and IoT techniques in smart city applicationChallenges and Roles of IoT and Big Data in Smart City applicationsProvides Big Data-IoT intelligent smart systems in a global perspectiveProvides a predictive framework that can handle the traffic on abnormal days, such as weekends and festival holidaysGives various solutions and ideas for smart traffic development in smart citiesGives a brief idea of the available algorithms/techniques of Big Data and IoT and guides in developing a solution for smart city applicationsThis book is primarily aimed at IT professionals. Undergraduates, graduates, and researchers in the area of computer science and information technology will also find this book useful.

The main aim of Healthcare 4.0: Health Informatics and Precision Data Management is to improve the services given by the healthcare industry and to bring meaningful patient outcomes by applying the data, information and knowledge in the healthcare domain.Features:Improves the quality of health data of a patientPresents a wide range of opportunities and renewed possibilities for healthcare systemsGives a way for carefully and meticulously tracking the provenance of medical recordsAccelerates the process of disease-oriented data and medical data arbitrationBrings meaningful patient health outcomesEradicates delayed clinical communicationsHelps the research intellectuals to step down further toward the disease and clinical data storageCreates more patient-centered servicesThe precise focus of this handbook is on the potential applications and use of data informatics in healthcare, including clinical trials, tailored ailment data, patient and ailment record characterization and health records management.

Nowadays, raw biological data can be easily stored as databases in computers but extracting the required information is the real challenge for researchers. For this reason, bioinformatics tools perform a vital role in extracting and analyzing information from databases. Bioinformatics Tools and Big Data Analytics for Patient describes the applications of bioinformatics, data management, and computational techniques in clinical studies and drug discovery for patient care. The book gives details about the recent developments in the fields of artificial intelligence, cloud computing, and data analytics. It highlights the advances in computational techniques used to perform intelligent medical tasks.Features:Presents recent developments in the fields of artificial intelligence, cloud computing, and data analytics for improved patient care.Describes the applications of bioinformatics, data management, and computational techniques in clinical studies and drug discovery.Summarizes several strategies, analyses, and optimization methods for patient healthcare.Focuses on drug discovery and development by cloud computing and data-driven researchThe targeted audience comprises academics, research scholars, healthcare professionals, hospital managers, pharmaceutical chemists, the biomedical industry, software engineers, and IT professionals.

Nowadays, raw biological data can be easily stored as databases in computers but extracting the required information is the real challenge for researchers. For this reason, bioinformatics tools perform a vital role in extracting and analyzing information from databases. Bioinformatics Tools and Big Data Analytics for Patient describes the applications of bioinformatics, data management, and computational techniques in clinical studies and drug discovery for patient care. The book gives details about the recent developments in the fields of artificial intelligence, cloud computing, and data analytics. It highlights the advances in computational techniques used to perform intelligent medical tasks.Features:Presents recent developments in the fields of artificial intelligence, cloud computing, and data analytics for improved patient care.Describes the applications of bioinformatics, data management, and computational techniques in clinical studies and drug discovery.Summarizes several strategies, analyses, and optimization methods for patient healthcare.Focuses on drug discovery and development by cloud computing and data-driven researchThe targeted audience comprises academics, research scholars, healthcare professionals, hospital managers, pharmaceutical chemists, the biomedical industry, software engineers, and IT professionals.