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Addresses an Emerging Shift in Developing CountriesThe authors and contributors of Ambient Assisted Living have recognized that the demographic profile is changing in many developing countries and have factored in an inversion of the demographic pyramid. The technology of ambient assisted living (AAL), supports the elderly and disabled in their dai
This book presents the state of the art of Internet of Things (IoT) from the perspective of healthcare and Ambient Assisted Living (AAL). It discusses the emerging technologies in healthcare services used for healthcare professionals and patients for enhanced living environments and public health. The topics covered in this book include emerging eHealth IoT applications, Internet of Medical Things, health sensors, and wearable sensors for pervasive and personalized healthcare, and smart homes applications for enhanced health and well-being. The book also presents various ideas for the design and development of IoT solutions for healthcare and AAL. It will be useful for bioengineers and professionals working in the areas of healthcare as well as health informatics.
The Symposium on Ubiquitous Computing and Ambient Intelligence (UCAmI) began as a workshop held in 2003 in San Sebastián (Spain) under the Spanish Artificial Intelligence Conference. This event gathered 32 attendees and 18 papers were p- sented. The second edition, already as a Symposium, took place in Granada (Spain) under the first Spanish Computer Science Conference (CEDI). Later, in 2006, a s- ond workshop was celebrated in Ciudad Real and, in 2007; the second Symposium was organized in Zaragoza by the CEDI conference. Now we continue to work on the organization of this event in Salamanca, a beautiful Spanish city. The European Community and the Sixth and Seventh Framework Programs - courage researchers to explore the generic scope of the AmI vision. In fact, some researchers have a crucial role in this vision. Emile Aarts from Philips describes - bient Intelligence as "the integration of technology into our environment, so that p- ple can freely and interactively utilize it". This idea agrees with the proposal of Mark Weiser regarding the Ubiquitous Computing paradigm.
Ambient Assisted Living and Enhanced Living Environments: Principles, Technologies and Control separates the theoretical concepts concerning the design of such systems from their real-world implementations. For each important topic, the book bridges theory and practice, introducing the instruments needed by professionals in their activities. To this aim, topics are presented in a logical sequence, with the introduction of each topic motivated by the need to respond to claims and requirements from a wide range of AAL/ELE applications. The advantages and limitations of each model or technology are presented through concrete case studies for AAL/ELE systems. The book also presents up-to-date technological solutions to the main aspects regarding AAL/ELE systems and applications, a highly dynamic scientific domain that has gained much interest in the world of IT in the last decade. In addition, readers will find discussions on recent AAL/ELE technologies that were designed to solve some of the thorniest business problems that affect applications in areas such as health and medical supply, smart city and smart housing, Big Data and Internet of Things, and many more. Introduces readers to technologies supporting the development of Ambient Assisted Living applications Explains state-of-the-art technological solutions for the main issues regarding AAL and Enhanced Living Environments Reports the development process of scientific and commercial applications and platforms that support AAL and ELE Identifies the advanced solutions in the context of Enhanced Living Environments
As innovators continue to explore and create new developments within the fields of artificial intelligence and computer science, subfields such as machine learning and the internet of things (IoT) have emerged. Now, the internet of everything (IoE), foreseen as a cohesive and intelligent connection of people, processes, data, and things, is theorized to make internet connections more valuable by converting information into wise actions that create unprecedented capabilities, richer experiences, and economic opportunities to all players in the market. Harnessing the Internet of Everything (IoE) for Accelerated Innovation Opportunities discusses the theoretical, design, evaluation, implementation, and use of innovative technologies within the fields of IoE, machine learning, and IoT. Featuring research on topics such as low-power electronics, mobile technology, and artificial intelligence, this book is ideally designed for computer engineers, software developers, investigators, advanced-level students, professors, and professionals seeking coverage on the various contemporary theories, technologies, and tools in IoE engineering.
"This book provides explanations of concepts, processes and acronyms related to different areas, issues and trends in various areas of wireless technologies for ambient assisted living and healthcare, focusing on emerging wireless technologies and innovative wireless solutions for smart home environments"--Provided by publisher.
This open access book was prepared as a Final Publication of the COST Action IC1303 “Algorithms, Architectures and Platforms for Enhanced Living Environments (AAPELE)”. The concept of Enhanced Living Environments (ELE) refers to the area of Ambient Assisted Living (AAL) that is more related with Information and Communication Technologies (ICT). Effective ELE solutions require appropriate ICT algorithms, architectures, platforms, and systems, having in view the advance of science and technology in this area and the development of new and innovative solutions that can provide improvements in the quality of life for people in their homes and can reduce the financial burden on the budgets of the healthcare providers. The aim of this book is to become a state-of-the-art reference, discussing progress made, as well as prompting future directions on theories, practices, standards, and strategies related to the ELE area. The book contains 12 chapters and can serve as a valuable reference for undergraduate students, post-graduate students, educators, faculty members, researchers, engineers, medical doctors, healthcare organizations, insurance companies, and research strategists working in this area.
The book details deep learning models like ANN, RNN, LSTM, in many industrial sectors such as transportation, healthcare, military, agriculture, with valid and effective results, which will help researchers find solutions to their deep learning research problems. We have entered the era of smart world devices, where robots or machines are being used in most applications to solve real-world problems. These smart machines/devices reduce the burden on doctors, which in turn make their lives easier and the lives of their patients better, thereby increasing patient longevity, which is the ultimate goal of computer vision. Therefore, the goal in writing this book is to attempt to provide complete information on reliable deep learning models required for e-healthcare applications. Ways in which deep learning can enhance healthcare images or text data for making useful decisions are discussed. Also presented are reliable deep learning models, such as neural networks, convolutional neural networks, backpropagation, and recurrent neural networks, which are increasingly being used in medical image processing, including for colorization of black and white X-ray images, automatic machine translation images, object classification in photographs/images (CT scans), character or useful generation (ECG), image caption generation, etc. Hence, reliable deep learning methods for the perception or production of better results are a necessity for highly effective e-healthcare applications. Currently, the most difficult data-related problem that needs to be solved concerns the rapid increase of data occurring each day via billions of smart devices. To address the growing amount of data in healthcare applications, challenges such as not having standard tools, efficient algorithms, and a sufficient number of skilled data scientists need to be overcome. Hence, there is growing interest in investigating deep learning models and their use in e-healthcare applications. Audience Researchers in artificial intelligence, big data, computer science, and electronic engineering, as well as industry engineers in transportation, healthcare, biomedicine, military, agriculture.
This is a broad introductory handbook, for academic and industry researchers, covering the major technologies and applications in Ambient Assisted Living (AAL). Set out in three main sections: Part 1 focuses on current state-of-the-art technology and critical analysis: Part 2 covers the applications of these technologies; and Part 3 includes general issues such as usability, accessibility, privacy and ethics. With contributions from around the world, topics covered include: smart homes, environmental sensors and data fusion, wearable sensors, devices and smart clothes, standards and interoperability, computer vision for AAL, reasoning systems, person-environment interaction, networks and integration platforms, assistive and service robotics, tele-care and telehealth, gait analysis, fall prevention, detection and intervention, prevention and management of chronic conditions, support to activities of daily living, mental health and cognitive stimulation, indoor and outdoor mobility, well being, social interaction and isolation, usability, accessibility, privacy and ethical issues. Active and Assisted Living is an essential resource for researchers in academia and industry developing AAL technologies. Students, healthcare practitioners and engineers, in this cross-disciplinary field, which includes robotics and automation, telecommunications, computing and healthcare, will find this handbook of use.
Business intelligence supports managers in enterprises to make informed business decisions in various levels and domains such as in healthcare. These technologies can handle large structured and unstructured data (big data) in the healthcare industry. Because of the complex nature of healthcare data and the significant impact of healthcare data analysis, it is important to understand both the theories and practices of business intelligence in healthcare. Theory and Practice of Business Intelligence in Healthcare is a collection of innovative research that introduces data mining, modeling, and analytic techniques to health and healthcare data; articulates the value of big volumes of data to health and healthcare; evaluates business intelligence tools; and explores business intelligence use and applications in healthcare. While highlighting topics including digital health, operations intelligence, and patient empowerment, this book is ideally designed for healthcare professionals, IT consultants, hospital directors, data management staff, data analysts, hospital administrators, executives, managers, academicians, students, and researchers seeking current research on the digitization of health records and health systems integration.