A Logical Design of Internet of Things Assisted Digital Health Record Monitoring System using Deep Learning Principles

Intelligent systems for monitoring health have been made possible by the IoT and the mental/physical health of an individual may be monitored using such a system. Determinants of numerous diseases, both physical and mental include tension, worry and high blood pressure. Problems associated with aging including anxiety, depression, stress and pressure require specialized care in this context. The prompt identification of health issues by monitoring of nervousness tension, stress, and heart rate is a key to avoiding irreversible harm. This will improve health outcomes; lessen the burden on caregivers, and save money. Find innovative technological answers for continuous monitoring of stress, anxiety, and blood pressure through the use of covert embedded sensors as well as deep learning methods. As a result of the suggested smart health monitoring system, health monitoring services may now be provided quickly, cheaply, and reliably from remote places, whereas this was not previously achievable with conventional health care systems. The implementation of a blockchain-based framework has increased the safety and privacy of patients' private information and reduced the likelihood of it being misused. Using Deep Learning and related technologies to evaluate health data for numerous goals has aided in the achievement of both preventative healthcare and fatality control. This has allowed for the early diagnosis of chronic illnesses, which was previously impossible. The combination of computing resources in the cloud and electronic storage has been introduced in order to render operations cheaper and instantaneously. This research provides a comprehensive overview of the state of health monitoring technology, including the most up-to-date developments and the most pressing problems.