The world is experiencing an unprecedented period of change and growth through all the electronic and technilogical developments and everyone on the planet has been impacted. What was once ‘science fiction’, today it is a reality. This book explores the world of many of once unthinkable advancements by explaining current technologies in great detail. Each chapter focuses on a different aspect - Machine Vision, Pattern Analysis and Image Processing - Advanced Trends in Computational Intelligence and Data Analytics - Futuristic Communication Technologies - Disruptive Technologies for Future Sustainability. The chapters include the list of topics that spans all the areas of smart intelligent systems and computing such as: Data Mining with Soft Computing, Evolutionary Computing, Quantum Computing, Expert Systems, Next Generation Communication, Blockchain and Trust Management, Intelligent Biometrics, Multi-Valued Logical Systems, Cloud Computing and security etc. An extensive list of bibliographic references at the end of each chapter guides the reader to probe further into application area of interest to him/her.

The rapid proliferation of connected devices in our daily lives, from smart homes to industrial sensors, has led to an explosion of data that requires processing before it is useful to experts. However, modern devices often have limited resources, making it challenging to decode and utilize this data effectively. Additionally, the need for real-time decision-making further complicates this issue, as traditional data processing methods take far too long to be able to keep up with the required volume and speed. Developments Towards Next Generation Intelligent Systems for Sustainable Development offers a comprehensive solution to these challenges by integrating novel technologies such as AI, edge computing, federated learning, quantum computing, and more. The book shows how intelligent systems can maximize computing power by leveraging these technologies to process large volumes of data efficiently and autonomously and make real-time decisions. The proposed architectures and frameworks focus on real-time analysis, faster decision-making, enhanced privacy, and efficient data processing.

This book provides a comprehensive guide to the design of sustainable and green computing systems (GSC). Coverage includes important breakthroughs in various aspects of GSC, including multi-core architectures, interconnection technology, data centers, high performance computing (HPC), and sensor networks. The authors address the challenges of power efficiency and sustainability in various contexts, including system design, computer architecture, programming languages, compilers and networking.

This book presents the latest developments in deep learning-enabled healthcare tools and technologies and offers practical ideas for using the IoT with deep learning (motion-based object data) to deal with human dynamics and challenges including critical application domains, technologies, medical imaging, drug discovery, insurance fraud detection and solutions to handle relevant challenges. This book covers real-time healthcare applications, novel solutions, current open challenges, and the future of deep learning for next-generation healthcare. It includes detailed analysis of the utilization of the IoT with deep learning and its underlying technologies in critical application areas of emergency departments such as drug discovery, medical imaging, fraud detection, Alzheimer's disease, and genomes. Presents practical approaches of using the IoT with deep learning vision and how it deals with human dynamics Offers novel solution for medical imaging including skin lesion detection, cancer detection, enhancement techniques for MRI images, automated disease prediction, fraud detection, genomes, and many more Includes the latest technological advances in the IoT and deep learning with their implementations in healthcare Combines deep learning and analysis in the unified framework to understand both IoT and deep learning applications Covers the challenging issues related to data collection by sensors, detection and tracking of moving objects and solutions to handle relevant challenges Postgraduate students and researchers in the departments of computer science, working in the areas of the IoT, deep learning, machine learning, image processing, big data, cloud computing, and remote sensing will find this book useful.

This book provides a detailed “how-to” guide, addressing aspects ranging from analysis and design to the implementation of applications, which need to be integrated within legacy applications and databases. The analysis and design of the next generation of software architectures must address the new requirements to accommodate the Internet of things (IoT), cybersecurity, blockchain networks, cloud, and quantum computer technologies. As 5G wireless increasingly establishes itself over the next few years, moving legacy applications into these new architectures will be critical for companies to compete in a consumer-driven and social media-based economy. Few organizations, however, understand the challenges and complexities of moving from a central database legacy architecture to a ledger and networked environment. The challenge is not limited to just designing new software applications. Indeed, the next generation needs to function more independently on various devices, and on more diverse and wireless-centric networks. Furthermore, databases must be broken down into linked list-based blockchain architectures, which will involve analytic decisions regarding which portions of data and metadata will be processed within the chain, and which ones will be dependent on cloud systems. Finally, the collection of all data throughout these vast networks will need to be aggregated and used for predictive analysis across a variety of competitive business applications in a secured environment. Certainly not an easy task for any analyst/designer! Many organizations will continue to use packaged products and open-source applications. These third-party products will need to be integrated into the new architecture paradigms and have seamless data aggregation capabilities, while maintaining the necessary cyber compliances. The book also clearly defines the roles and responsibilities of the stakeholders involved, including the IT departments, users, executive sponsors, and third-party vendors. The book’s structure also provides a step-by-step method to help ensure a higher rate of success in the context of re-engineering existing applications and databases, as well as selecting third-party products, conversion methods and cybercontrols. It was written for use by a broad audience, including IT developers, software engineers, application vendors, business line managers, and executives.