Soft Computing Techniques for Internet of Things in Healthcare and Wellness Applications

IoT-HWA 2020


Computing Systems



In recent times, the behavior monitoring has become harder due to the rapidly increasing data induction from the electronic smart devices. With the growth of the internet and technologies, the data has become humongous even when it is originated from a single source. Hence, when the data is originated from various heterogeneous sources in a distributed global scenario the data processing gets more complicated due to the magnitude of data. The soft computing techniques and machine learning have become standard in providing promising solutions to the processing, prediction and visualizing the data received from the Internet of Things. Soft computing techniques can bring the opportunity of predicting any misfortune even before they happen.
Recently, meaningful development has been reported in the field of risk and behavioral monitoring. These achievements are mostly based on ICT techniques, such as body area networking, human-assisted rehabilitation, and remote diagnosis. However, risk and behavioral monitoring (for example, integrating health services) with the existent communication method and providing remote medical treatments with accuracy and precision is still a challenging task. To this end, the new soft computing based decision-making approaches that comprehend the research findings from the fuzzy and rough sets theory, neural networks, genetic algorithm, and artificial intelligence are actively developing.
The aim of this special issue is to explore new technologies, methodologies, and applications that relate to all aspects of soft computing techniques with the focus on healthcare. Contributions may come from diverse fields engineering and healthcare, and the guest editors invite original and high-quality submissions addressing all aspects of this field, as long as the connection to the focus topic is clear and emphasized.
TOPICS:
Soft computing techniques for risk and behavioral management in healthcare
Signal processing and representing learning behavioral data
Fuzzy and rough sets theory for risk and behavioral monitoring
Real-time monitoring with big data processing and analytics for IoT in healthcare
Soft computing based multimedia technology for monitoring system with IoT
Ubiquitous sensing and intelligence in IoT based healthcare
High-performance computing for IoT applications in healthcare
Data Visualizations techniques for a ubiquitous environment in healthcare
Soft computing techniques for healthcare decision-support systems
Machine learning techniques for risk modelling and risk management
This special issue will be published in EAI Endorsed Transactions on Pervasive Health and Technology, an open access journal abstracted/indexed in Scopus, DOAJ, DBLP, CrossRef, EBSCO, WorldCat, Dimensions, among others. It focuses on personal electronic health assistants, health crowdsourcing, data mining and knowledge management, IT applications to needs of patients, disease prevention and awareness, electronic and mobile health platforms including design and more.
GUEST EDITORS:
•Dr. Logesh Ravi, Sri Ramachandra Institute of Higher Education and Research, Chennai, India. Email: logesh@sriramachandra.edu.in
•Dr. Subramaniyaswamy Vairavasundaram, SASTRA Deemed University, Thanjavur, India. Email: swamy@cse.sastra.edu