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Smart health infrastructure that incorporates the Internet of Things (IoT) and edge computing offers an innovative approach to improving disease response and surveillance Public health emergencies and chronic disease surveillance are two areas where this program is particularly important because of the significant impact that early intervention can have on patient outcomes. Hurdles for the integration of healthcare IoT and edge computing are data privacy and security concerns, performance issues on IoT devices as well as robust network infrastructure needs. To reduce its reliance on computers, Cloud has come up with a plan of introducing Edge Computing-based Context Health Monitoring System (EC-CHMS) which enables faster data analysis and response times by eliminating its use. The healthcare information is locally managed between the networks throughout the system network through edge computing in EC-CHMS that incorporates cloud to manage healthcare information locally between networks within the entire network. This technology can recognize a patient’s life threatening condition by fusing IoT sensors with machine learning algorithms and has numerous possibilities for healthcare applications such as early disease detection, real-time outbreak management, remote patient care among others. Continuous and context-aware health monitoring is possible using this system that supports proactive healthcare interventions towards enhancing overall health delivery efficiency. These results demonstrate that EC-CHMS outperforms traditional cloud-based systems in terms of handling data efficiently and time taken to run the code. To ensure accuracy and reliability of these vital signs, simulation shows how multiple health issues can be handled by it.
Soni et al. (Mon,) studied this question.
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