An IoT-based Smart Health Monitoring System with Hybrid Conversational Assistance

IoMT systems prevent frequent visits to doctors and meetings between patients and medical professionals. This end-to-end health monitoring system aims at offering monitoring of patients on their will along with consultant support and bringing up the adaptive conversational assistant as well. With a layered IoT architecture that restrictively balances between on-device signal pre-processing at the network edge with robust cloud-based analytics and hybrid assistance services, the system will collect continuous vital physiological data. The architecture provides threshold-based, role-based dashboards and to achieve sensor fidelity, data flow integrity and real-time responsiveness a prototype implementation was designed and experimentally confirmed, as well as an efficient proof of the automated warning feature. Having already initial data on its real-time functionality, our work delivers a working, configurable architecture of a health monitoring system based on an IoT and meets the stringent healthcare requirements of both latency and privacy. Our approach will help strengthen the trust of the patients and also aligns with the proposed system of modern healthcare in providing the remote patient monitoring with the hybrid conversational assistance.