Design of an IoT-based smart healthcare eco system for precise ageing illness detection and prognosis

Abstract

The article aims to provide a comprehensive review of the current state of smart healthcare systems, focusing on important topics such as the use of wearables and smartphones for health monitoring, the application of AI and machine learning for illness detection, and the integration of assistive frameworks like social robots for ambient-supported living. One of the key aspects discussed in the study is the software integration architectures required for the development of smart healthcare systems and the seamless integration of data. Analytics and various AI technologies are utilized in conjunction to create these systems. The article examines the different approaches employed in the development of these systems, highlighting the contributions of each framework, the overall functioning methodology, performance outputs, and comparative advantages and limitations. Moreover, the article also addresses current research challenges and identifies prospective future directions. It emphasizes the shortcomings of existing smart healthcare systems and proposes strategies for introducing innovative frameworks to overcome these limitations. The analysis aims to provide detailed insights into recent advancements in smart healthcare systems, enabling specialists to contribute to the field with their expertise. Overall, the article serves as a valuable resource for understanding the current landscape of smart healthcare systems, shedding light on recent breakthroughs, and encouraging further research and development in this rapidly evolving field.