Systematic review of smart health monitoring using deep learning and Artificial intelligence

In the rapidly growing world of technology and evolution, the outbreak and emergences diseases have become a critical issue. Precaution, prevention and controlling the diseases by technology has become the major challenge for healthcare professionals and health care industries. Maintaining a healthy lifestyle has become impossible in the busy work schedules. Smart health monitoring system is the solution to the above poses challenges. The recent revolution of industry 5.0 and 5G has led to development of smart cum cost effective sensors which help in real time health monitoring or individuals. The SHM has led to fast, cost effective, and reliable health monitoring services from remote locations which was not possible with traditional health care systems. The integration of blockchain framework improved data security and data privacy of confidential data of patient to prevent the data misuse against patients. Involvement of Deep Learning and Machine learning to analyze health data to achieve multiple targets has helped attain preventive healthcare and fatality management in patients. This has helped in the early detection of chronic diseases which was not possible recently. To make the services more cost effective and real time, the integration of cloud computing and cloud storage has been implemented. The work presents the systematic review of SHM along with recent advancements in SHM with existing challenges.