Enhancing Healthcare Through AI Deep Learning: A Human-Centric IoT Advisory System Cloud
S. Sridharan, S. Deivasigamani, R. Rajesh, R Surendran
Abstract
The medical industry in the modern world depends heavily on the healthcare sector. Over the past few years, the COVID-19 epidemic has considerably agitated the worldwide healthcare sector. An intelligent healthcare system is now more important than ever because of the devastating impact that a shortage of physicians, nurses, and medical facilities has had on the healthcare industry. Positive and uplifting solutions to the healthcare industry's difficulties can be found in AI/ML algorithms and intelligent medical technologies. There is an immediate need for a sophisticated system that allows humans and machines to converse via video. Using edge, fog, and cloud computing techniques with a focus on video, this study proposes a novel design for the video interactive and intelligent healthcare system. The primary rationale for communication in the medical area is interaction recognition and the extent to which it may be employed in interactive systems. A lot of changes have recently occurred in the healthcare industry as a result of the COVID-19 pandemic. As time goes on and things get back to normal, many health programs that were created and utilized during difficult times are not utilized. Ensuring that such technologies are continuously deployed requires consideration of both the present needs and the basic concepts and frameworks required to enhance the current system. Information security and confidentiality concerns must be addressed by contemporary solutions for CF-based health video conferencing recommendation systems. This research presents a data-mining-focused intelligent health video conference recommendation system (HRS).