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The book is the first international reference on the field of smart device recognition and Ubiquitous Electric Internet of Things (UEIOT). It presents a range of state-of-the-art key methods and applications for smart device recognition. In future smart environments, obtaining energy consumption information for identifying every device is an effective approach to guarantee the energy efficiency of smart industrial systems. Such as, the Ubiquitous Electric Internet of Things (UEIOT) technology represents one of the most effective measures for electricity and energy management and has attracted considerable attention from scientists and engineers around the world. The realization of smart device recognition in the UEIOT framework has become the core and basis of UEIOT’s success. The device smart recognition can help governments and managers to distribute energy and power better, and help device manufacturers to improve their products regarding smart energy conservation. Accordingly, in the future smart industry, implementing smart device recognition is desired and very important. In the book, several methods, strategies, and experiments for achieving smart device recognition are presented in details. As the first monograph in the field of smart device recognition, the book can provide beneficial reference for students, engineers, scientists, and managers in the fields of power, energy, electromechanical devices, smart cities, artificial intelligence, etc.
The book is the first international reference on the field of smart device recognition and Ubiquitous Electric Internet of Things (UEIOT). It presents a range of state-of-the-art key methods and applications for smart device recognition. In future smart environments, obtaining energy consumption information for identifying every device is an effective approach to guarantee the energy efficiency of smart industrial systems. Such as, the Ubiquitous Electric Internet of Things (UEIOT) technology represents one of the most effective measures for electricity and energy management and has attracted considerable attention from scientists and engineers around the world. The realization of smart device recognition in the UEIOT framework has become the core and basis of UEIOT's success. The device smart recognition can help governments and managers to distribute energy and power better, and help device manufacturers to improve their products regarding smart energy conservation. Accordingly, in the future smart industry, implementing smart device recognition is desired and very important. In the book, several methods, strategies, and experiments for achieving smart device recognition are presented in details. As the first monograph in the field of smart device recognition, the book can provide beneficial reference for students, engineers, scientists, and managers in the fields of power, energy, electromechanical devices, smart cities, artificial intelligence, etc. .
Smartphone usage has created a new means for detection, analysis, diagnosis and monitoring through the use of new apps and attachments. These breakthrough analytical methods offer ways to overcome the drawbacks of more conventional methods, such as the expensive instrumentation that is often needed, complex sample pre-treatment steps, or time-consuming procedures. Smartphone-Based Detection Devices: Emerging Trends in Analytical Techniques gathers these modern developments in smartphone analytical methods into one comprehensive source, covering recent advancements in analytical tools while paying special attention to the most accurate, highly efficient approaches. Serving as a guide not only to analytical chemists but also to environmentalists, biotechnologists, pharmacists, forensic scientists and toxicologists, Smartphone-Based Detection Devices: Emerging Trends in Analytical Techniques is an important source for researchers who require accurate analysis of their on- and off-site samples. Students in these fields at the graduate and post-graduate level will also benefit from this topical and comprehensive book. - Provides an integrated approach for advanced analytical methods and techniques using smartphones - Covers the usage of smartphones in sample prep, integration and detection stages of analytical chemistry - Applicable for researchers of all levels, from graduate students to professionals
Currently, informatics within the field of public health is a developing and growing industry. Clinical informatics are used in direct patient care by supplying medical practitioners with information that can be used to develop a care plan. Intelligent applications in clinical informatics facilitates with the technology-based solutions to analyze data or medical images and help clinicians to retrieve that information. Decision models aid with making complex decisions especially in uncertain situations. The Handbook of Research on Applied Intelligence for Health and Clinical Informatics is a comprehensive reference book that focuses on the study of resources and methods for the management of healthcare infrastructure and information. This book provides insights on how applied intelligence with deep learning, experiential learning, and more will impact healthcare and clinical information processing. The content explores the representation, processing, and communication of clinical information in natural and engineered systems. This book covers a range of topics including applied intelligence, medical imaging, telehealth, and decision support systems, and also looks at technologies and tools used in the detection and diagnosis of medical conditions such as cancers, diabetes, heart disease, lung disease, and prenatal syndromes. It is an essential reference source for diagnosticians, medical professionals, imaging specialists, data specialists, IT consultants, medical technologists, academicians, researchers, industrial experts, scientists, and students.
This book offer clear descriptions of the basic structure for the recognition and classification of human activities using different types of sensor module and smart devices in e.g. healthcare, education, monitoring the elderly, daily human behavior, and fitness monitoring. In addition, the complexities, challenges, and design issues involved in data collection, processing, and other fundamental stages along with datasets, methods, etc., are discussed in detail. The book offers a valuable resource for readers in the fields of pattern recognition, human–computer interaction, and the Internet of Things.
This book contains the contributions presented at the 2nd international KES conference on Smart Education and Smart e-Learning, which took place in Sorrento, Italy, June 17-19, 2015. It contains a total of 45 peer-reviewed book chapters that are grouped into several parts: Part 1 - Smart Education, Part 2 – Smart Educational Technology, Part 3 – Smart e-Learning, Part 4 – Smart Professional Training and Teachers’ Education, and Part 5 – Smart Teaching and Training related Topics. This book can be a useful source of research data and valuable information for faculty, scholars, Ph.D. students, administrators, and practitioners - those who are interested in innovative areas of smart education and smart e-learning.