A Fog-Assisted Cloud Computing Architecture for Healthcare Monitoring Applications Using IoT

The emergence of COVID-19 has heightened the demand for innovative methods like the Internet of Medical Things (IoMT), Wireless Body Area Networks (WBANets), and Cloud Computing (CC) in the healthcare industry and various other domains. These innovations have facilitated the connectivity and communication of billions of gadgets, enabling them to link to the internet and interact with one another. This paper presents the development of an IoMT framework that incorporates WBANets. Fog Computing (FC) is employed for rapid and effortless evaluation, whereas CC is utilized for lengthy and intricate investigation. The loMT concept is introduced in the context of predicting diabetes. Predicting diabetes is conducted on a fog computing platform using fuzzy logic for decision-making. The database generated in WBANets is utilized for extensive data evaluation in the context of Machine Learning (ML) algorithms. The findings indicate that the suggested framework decreases the latency by 60%, the mean execution time by 39%, and the authentication time by 36% for many devices.