Intelligent Data Sensing and Processing for Health and Well-being Applications
- 1st Edition - July 27, 2018
- Latest edition
- Editors: Miguel Antonio Wister Ovando, Pablo Pancardo Garcia, Francisco Diego Acosta Escalante, Jose Adan Hernandez Nolasco
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 1 2 1 3 0 - 6
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 1 2 3 2 0 - 1
Intelligent Data Sensing and Processing for Health and Well-being Applications uniquely combines full exploration of the latest technologies for sensor-collected intellige… Read more
Intelligent Data Sensing and Processing for Health and Well-being Applications uniquely combines full exploration of the latest technologies for sensor-collected intelligence with detailed coverage of real-case applications for healthcare and well-being at home and in the workplace. Forward-thinking in its approach, the book presents concepts and technologies needed for the implementation of today's mobile, pervasive and ubiquitous systems, and for tomorrow’s IoT and cyber-physical systems. Users will find a detailed overview of the fundamental concepts of gathering, processing and analyzing data from devices disseminated in the environment, as well as the latest proposals for collecting, processing and abstraction of data-sets.
In addition, the book addresses algorithms, methods and technologies for diagnosis and informed decision-making for healthcare and well-being. Topics include emotional interface with ambient intelligence and emerging applications in detection and diagnosis of neurological diseases. Finally, the book explores the trends and challenges in an array of areas, such as applications for intelligent monitoring in the workplace for well-being, acquiring data traffic in cities to improve the assistance of first aiders, and applications for supporting the elderly at home.
- Examines the latest applications and future directions for mobile data sensing in an array of health and well-being scenarios
- Combines leading computing paradigms and technologies, development applications, empirical studies, and future trends in the multidisciplinary field of smart sensors, smart sensor networks, data analysis and machine intelligence methods
- Features an analysis of security, privacy and ethical issues in smart sensor health and well-being applications
- Equips readers interested in interdisciplinary projects in ubiquitous computing or pervasive computing and ambient intelligence with the latest trends and developments
Researchers, academics, software developers, and industry practitioners working in the domains of mobile, pervasive and ubiquitous computing; control systems; computer science; computer engineering; applied informatics; and intelligent processing systems; also those with specific interest in health and well-being applications in mobile computing
Part 1. Introduction to Smart sensors
1. Charting the past, present, and future in mobile sensing research and development
2. Data fusion architecture of heterogeneous sources obtained of a smart desk
3. Wireless Sensor Technology for Intelligent Data Sensing: Research Trends and Challenges
Part 2. Sensing in health and well-being applications
4. Tangible interfaces for ambient assisted working
5. Ambient Assisted Working Applications
6. Home automation architecture for comfort, security and resource saving
7. Security, privacy and ethical issues in smart sensor health and well-being application
8. Diagnosing medical conditions using rule-based classifiers
Part 3. Smart sensor application for health and well-being applications
9. Assessing the Perception of Physical Fatigue using Mobile Sensing
10. Applications to improve the assistance of first aiders in outdoor scenarios
11. Indoor Activity Tracking for Elderly Using Intelligent Sensors
12. User-centered data mining for survival-mortality classification of breast cancer in Mexican origin women
13. Modelling Independence and Security in Dementia-Users Using Fuzzy Logic
14. Wireless Sensor Networks Applications for Monitoring Environmental Variables Using Evolutionary Algorithms
- Edition: 1
- Latest edition
- Published: July 27, 2018
- Language: English
MO
Miguel Antonio Wister Ovando
Miguel A. Wister received his Ph.D. in Information Technology and Communications Engineering from the University of Murcia, Spain (2008). He earned an MSc in Informatics Technology at the Monterrey Institute of Technology and Higher Education (ITESM), Mexico, (1997), and a BSc degree in Informatics at the Juarez Autonomous University of Tabasco (UJAT), Mexico, (1993). He has tutored over 40 BSc and MSc students. Dr. Wister has also authored and co-authored about 20 scientific papers published in peer-reviewed conferences and journals. He is the editor and co-author of the book Intelligent Data Sensing and Processing for Health and Well-being Applications (Editorial Academic Press, ELSEVIER). He is also associate editor in two Journals: 1. Internet of Things Engineering Cyber Physical Human Systems; 2. International Journal of Grid and Utility Computing. His research interests are ubiquitous computing, focusing on ambient intelligence and the Internet of Things. viewed conferences and journals.
Affiliations and expertise
Associate Professor, Academic Division of Information Technology and Systems (DAIS), Juarez Autonomous University of Tabasco (UJAT), Villahermosa, Tabasco, MexicoPG
Pablo Pancardo Garcia
Pablo Pancardo García is Associate Professor at Juarez Autonomous University of Tabasco (UJAT) from Mexico. He is PhD Candidate in Computer Sciences at the Distributed Systems Research Group of the UJAT. He received a Master Science degree in Distributed Systems from Monterrey Advances Studies Institute in Mexico. Since 2007, he has directed and participated on several projects related to Mobile and Ubiquitous Computing, Wireless Sensor Networks and RFID applications related to healthcare. Recently, he has especially focused on Ambient Intelligence for healthcare and well-being at workplace. He has directed over 20 undergraduate and graduate thesis and he has published over 20 international papers.
Affiliations and expertise
Associate Professor, Juarez Autonomous University of Tabasco (UJAT), MexicoFA
Francisco Diego Acosta Escalante
Francisco Diego Acosta Escalante holds a PhD. in computer science with honors from the University of Sciences and Techniques of Languedoc in the French city of Montpellier, he has a master's degree in computer science from the University of Grenoble National Polytechnic and the University Joseph Fourier in France and is an engineer in Computer Systems by Monterrey Institute of Technology and Higher Education (ITESM) in Monterrey, Mexico. In his teaching he has taught courses both undergraduate and graduate students and has authored more than 30 undergraduate and graduate thesis. It has also given lectures at scientific events and has over 20 scientific publications in the area of computing systems. His research interests cover topics like task and temporal Modeling & task management systems temporal data specification, distributed activities on Ad Hoc networks, and Ambient Intelligence; he has recently focused on Internet of Things (IoT).
Affiliations and expertise
Associate Professor, Juarez Autonomous University of Tabasco (UJAT), MexicoJH
Jose Adan Hernandez Nolasco
José Adán Hernández Nolasco holds a Ph. D. in Optics, National Institute for Astrophysics, Optics and Electronics, 2012. M.Sc. in Electronic Engineering [Telecommunications] by Monterrey Institute of Technology and Higher Education, 2003. Electronic and Communications Engineering graduate from the Autonomous University of Nuevo León, 1996. Seventeen years as Research Professor at the Juarez Autonomous University of Tabasco. Twenty publications in the areas of optics and ambient intelligence. and more than thirty participations in conferences. The areas of interest are ubiquitous systems, ambient intelligence, telecommunications infrastructure and the study of the propagation of communication signals.
Affiliations and expertise
Research Professor, Juarez Autonomous University of Tabasco, MexicoRead Intelligent Data Sensing and Processing for Health and Well-being Applications on ScienceDirect