Health monitoring system and method based on cloud resource low delay scheduling

Abstract

The invention discloses a health monitoring system based on cloud resource low delay scheduling. The system comprises a physiological sensor node, a fog computing server, a cloud data center and a mobile intelligent terminal. The invention further discloses a health monitoring method based on the cloud resource low delay scheduling. The physiological sensor node transmits physiological monitoringdata to the fog computing server with nearest network distance; the fog computing server is responsible for receiving, processing and merging data, and uploading the data to the cloud data center; themobile intelligent terminal is connected with the fog computing server with nearest network distance, receives intelligent alarm information, a health assessment result and an intervention measure; the fog computing server and a resource scheduling algorithm restrained based on a time threshold in the cloud data center process a request to ensure the low delay. The health monitoring system and method based on the cloud resource low delay scheduling have the advantages that the system is intelligent and front-end, the delay is low, the location awareness is strong, the limitations of physiological sensors in terms of energy and storage are overcome, the user experience is improved, and the method is conducive to finding problems and providing ambulance at the first time.

Description

technical field [0001] The invention belongs to the field of medical information, in particular to a health monitoring system and method based on low-delay scheduling of cloud resources. Background technique [0002] According to the "China Cardiovascular Health Index (2017)", residents are generally exposed to cardiovascular disease (CVD) risk factors, showing a trend of rapid growth and individual aggregation among younger age and low-income groups. The mortality rate of cardiovascular and cerebrovascular diseases in China is on the rise. The number of vascular diseases is 290 million, of which 13 million are stroke, 11 million are coronary heart disease, 5 million are cor pulmonale, 4.5 million are heart failure, 2.5 million are rheumatic heart disease, 2 million are congenital heart disease, and 270 million are hypertension. Cardiovascular disease (CVD) prevention and monitoring are very important, especially sudden heart disease. If subtle signs can be monitored in adv...

AI Technical Summary

Problems solved by technology

[0003] At present, hospital health monitoring centers, community hospitals, nursing centers and other places are crowded with people and have a large flow rate. Desktop monitoring equipment is often bulky and inconvenient to carry. The cost of monitoring is high, and it is difficult to meet the growing needs of patients.

The computing and storage resources of the portable monitoring terminal are limited, and short-distance protocols such as Bluetooth, ZigBee, WIFI, and 6LoWPAN are used to centralize the data in the cloud with large storage and computing capabilities, but the cloud faces challenges such as response speed, network bandwidth, and network congestion. , it is difficult to meet the requirements of low latency, mobility and location awareness, which affects the real-time and practicality of human health monitoring

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