There is a significant percentage rise in chronic illness among the aging population. A number of E-healthcare systems are in place to offer healthcare services. Each of these existing systems has its own limitations in terms of scalability, connectivity, reliability, etc. A smart healthcare system with cognitive and intelligent capabilities is essential to offer a real-time computing environment and provide quality care to chronically ill patients. The IT industry is facing many challenges in handling the enormous volumes of data generated and to find useful and important medical insights to offer real-time assistance to patients. With the introduction of ubiquitous computing (UC), cloud computing and big data platforms and cognitive analytics, better and improved medical models could be designed for efficient storage, processing, and providing real-time solutions. A systematic review was conducted to evaluate UC from a theoretical perspective. The research challenges and existing technologies in healthcare were looked at from the perspective of developing a new framework that offers cognitive and ambient intelligence. In this paper, a novel framework was proposed with four-tier functionality that incorporates the latest cutting-edge technologies such as ubiquitous, edge, fog, cloud and big data, and cognitive analytics. The framework is designed to support large-scale heterogeneous data generated from dynamic and complex environments.
|Title of host publication||Systems Simulation and Modeling for Cloud Computing and Big Data Applications|
|Number of pages||19|
|Publication status||Published - 1 Jan 2020|