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The smart world is set to enhance everyday things with abilities of sensation, communication, computation and intelligence so that many tasks and processes could be simplified, efficient, and enjoyable It consists of numerous smart things that can be endowed with different levels forms of intelligence and be connected together for a network level of intelligence At the same time, the fairness and ethics in utilizing such an intelligence is of extreme importance Research on ubiquitous and trustworthy smart world is an emerging research field covering many interdisciplinary areas that benefits humanity and will have significant societal impacts
Smart World Ubiquitous Intelligence Computing Advanced and Trusted Computing Scalable Computing and Communications Cloud and Big Data Computing Internet of People Smart City Innovations
The smart world is set to enhance everyday things with abilities of sensation, communication, computation and intelligence so that many tasks and processes could be simplified, more efficient, and enjoyable It consists of numerous smart things that can be endowed with different levels forms of intelligence and even capable of thinking This smart world is set to be the next important stage in human history Research on smart world is an emerging research field covering many areas, essential problems and crucial issues in truly building the smart world that benefits humanity, and simultaneously safeguards the natural environment for sustainable development and evolution IEEE SmartWorld 2019 aims to provide a high profile, leading edge platform for researchers and engineers to exchange and explore state of art advances and innovations in graceful integrations of Cyber, Physical and Social Worlds with Ubiquitous Intelligence
FOG COMPUTING FOR INTELLIGENT CLOUD IOT SYSTEMS This book is a comprehensive guide on fog computing and how it facilitates computing, storage, and networking services Fog computing is a decentralized computing structure that connects data, devices, and the cloud. It is an extension of cloud computing and is an essential concept in IoT (Internet of Things), as it reduces the burden of processing in cloud computing. It brings intelligence and processing closer to where the data is created and transmitted to other sources. Fog computing has many benefits, such as reduced latency in processing data, better response time that helps the user’s experience, and security and privacy compliance that assures protecting the vital data in the cloud. It also reduces the cost of bandwidth, because the processing is achieved in the cloud, which reduces network bandwidth usage and increases efficiency as user devices share data in the local processing infrastructure rather than the cloud service. Fog computing has various applications across industries, such as agriculture and farming, the healthcare industry, smart cities, education, and entertainment. For example, in the agriculture industry, a very prominent example is the SWAMP project, which stands for Smart Water Management Platform. With fog computing’s help, SWAMP develops a precision-based smart irrigation system concept used in agriculture, minimizing water wastage. This book is divided into three sections. The first section studies fog computing and machine learning, covering fog computing architecture, application perspective, computational offloading in mobile cloud computing, intelligent Cloud-IoT systems, machine learning fundamentals, and data visualization. The second section focuses on applications and analytics, spanning various applications of fog computing, such as in healthcare, Industry 4.0, cancer cell detection systems, smart farming, and precision farming. This section also covers analytics in fog computing using big data and patient monitoring systems, and the emergence of fog computing concerning applications and potentialities in traditional and digital educational systems. Security aspects in fog computing through blockchain and IoT, and fine-grained access through attribute-based encryption for fog computing are also covered. Audience The book will be read by researchers and engineers in computer science, information technology, electronics, and communication specializing in machine learning, deep learning, the cyber world, IoT, and security systems.
This book provides an essential compilation of relevant and cutting edge academic and industry work on key cybersecurity applications topics. Further, it introduces cybersecurity applications to the public at large to develop their cybersecurity applications knowledge and awareness. The book concentrates on a wide range of advances related to Cybersecurity Applications which include, among others, applications in the areas of Data Science, Internet of Things, Artificial Intelligence, Robotics, Web, High-Tech Systems, Cyber-Physical Systems, Mobile Devices, Digital Media, and Cloud Computing. It introduces the concepts, techniques, methods, approaches and trends needed by cybersecurity application specialists and educators for keeping current their cybersecurity applications knowledge. Further, it provides a glimpse of future directions where cybersecurity applications are headed. The book can be a valuable resource to applied cybersecurity experts towards their professional development efforts and to students as a supplement to their cybersecurity courses.
The strategically sound combination of edge computing and artificial intelligence (AI) results in a series of distinct innovations and disruptions enabling worldwide enterprises to visualize and realize next-generation software products, solutions and services. Businesses, individuals, and innovators are all set to embrace and experience the sophisticated capabilities of Edge AI. With the faster maturity and stability of Edge AI technologies and tools, the world is destined to have a dazzling array of edge-native, people-centric, event-driven, real-time, service-oriented, process-aware, and insights-filled services. Further on, business workloads and IT services will become competent and cognitive with state-of-the-art Edge AI infrastructure modules, AI algorithms and models, enabling frameworks, integrated platforms, accelerators, high-performance processors, etc. The Edge AI paradigm will help enterprises evolve into real-time and intelligent digital organizations. Applied Edge AI: Concepts, Platforms, and Industry Use Cases focuses on the technologies, processes, systems, and applications that are driving this evolution. It examines the implementation technologies; the products, processes, platforms, patterns, and practices; and use cases. AI-enabled chips are exclusively used in edge devices to accelerate intelligent processing at the edge. This book examines AI toolkits and platforms for facilitating edge intelligence. It also covers chips, algorithms, and tools to implement Edge AI, as well as use cases. FEATURES The opportunities and benefits of intelligent edge computing Edge architecture and infrastructure AI-enhanced analytics in an edge environment Encryption for securing information An Edge AI system programmed with Tiny Machine learning algorithms for decision making An improved edge paradigm for addressing the big data movement in IoT implementations by integrating AI and caching to the edge Ambient intelligence in healthcare services and in development of consumer electronic systems Smart manufacturing of unmanned aerial vehicles (UAVs) AI, edge computing, and blockchain in systems for environmental protection Case studies presenting the potential of leveraging AI in 5G wireless communication