Dinesh – författare

Despite their widespread impact, computer networks that provide the foundation for the World Wide Web and Internet have many limitations. These networks are vulnerable to security threats, break easily, and have a limited ability to respond to changing conditions. Recent research on overcoming these limitations has used biological systems for inspiration, resulting in the development of biologically-inspired computer networks. These networks are designed and developed using principles that are commonly found in natural and biological systems. Biologically Inspired Networking and Sensing: Algorithms and Architectures offers current perspectives and trends in biologically-inspired networking, exploring various approaches aimed at improving network paradigms. Research contained within this compendium of papers and surveys introduces studies in the fields of communication networks, performance modeling, and distributed computing, as well as new advances in networking.

Smart homes, smart cities, and wearable technologies are the growing applications of the internet of things (IoT). Ranging from healthcare tracking applications to smart watches and smart bands for personal safety, the IoT has turned out to be one of the most indispensable parts of our lives even as it is becoming more interconnected to better serve people. With the exponential growth of the IoT and its applications, building the next-generation smart world becomes much more feasible. The IoT and the Next Revolutions Automating the World covers a spectrum of intelligent applications of the IoT in parking, traffic management, waste management, lighting, air pollution controlling, healthcare, weather tracking, retail, and other areas calling for automation. Highlighting a wide range of topics such as e-commerce, security management, and web infrastructure, this book is ideal for academicians, students, researchers, industry professionals, IT consultants, engineers, and scientists.

Despite their widespread impact, computer networks that provide the foundation for the World Wide Web and Internet have many limitations. These networks are vulnerable to security threats, break easily, and have a limited ability to respond to changing conditions. Recent research on overcoming these limitations has used biological systems for inspiration, resulting in the development of biologically-inspired computer networks. These networks are designed and developed using principles that are commonly found in natural and biological systems. Biologically Inspired Networking and Sensing: Algorithms and Architectures offers current perspectives and trends in biologically-inspired networking, exploring various approaches aimed at improving network paradigms. Research contained within this compendium of papers and surveys introduces studies in the fields of communication networks, performance modeling, and distributed computing, as well as new advances in networking.

Healthcare is an industry that has seen great advancements in personalized services through big data analytics. Despite the application of smart devices in the medical field, the mass volume of data that is being generated makes it challenging to correctly diagnose patients. This has led to the implementation of precise algorithms that can manage large amounts of information and successfully use smart living in medical environments. Professionals worldwide need relevant research on how to successfully implement these smart technologies within their own personalized healthcare processes. Applications of Deep Learning and Big IoT on Personalized Healthcare Services is a pivotal reference source that provides a collection of innovative research on the analytical methods and applications of smart algorithms for the personalized treatment of patients. While highlighting topics including cognitive computing, natural language processing, and supply chain optimization, this book is ideally designed for network designers, analysts, technology specialists, medical professionals, developers, researchers, academicians, and post-graduate students seeking relevant information on smart developments within individualized healthcare.

Deep learning includes a subset of machine learning for processing the unsupervised data with artificial neural network functions. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. When applied to engineering, deep learning can have a great impact on the decision-making process. Deep Learning Applications and Intelligent Decision Making in Engineering is a pivotal reference source that provides practical applications of deep learning to improve decision-making methods and construct smart environments. Highlighting topics such as smart transportation, e-commerce, and cyber physical systems, this book is ideally designed for engineers, computer scientists, programmers, software engineers, research scholars, IT professionals, academicians, and postgraduate students seeking current research on the implementation of automation and deep learning in various engineering disciplines.