Human Remote Mobile Medical Information Collection Method Based on Internet of Things and Intelligent Algorithm

Abstract

In the environment of rapid social and economic development, the reform of medical informatization is constantly advancing, and the residents pay more and more attention to their own health status while improving their living standards. The traditional medical service system has some disadvantages in providing real-time, cross regional, long-term and easy-to-operate health services, which has become increasingly inadequate to meet the health needs of users. In order to solve the problem of difficulty in seeing a doctor caused by limited medical resources, and to carry out real-time health monitoring for a large number of groups suffering from chronic diseases and sub-health groups, this study conducted in-depth analysis and experimental exploration on the human remote mobile medical information collection method based on the Internet of things and intelligent algorithm. It established the information collection section by using KbaC clustering algorithm based on ant colony point system which, combined with a comparative study on the health indicators of related groups, has successfully proved that the Internet of things technology and intelligent algorithm for medical information collection and follow-up medical services are of certain positive significance, based on the Internet of things and other related technologies of human remote medical information collection system that can accurately and timely detect the patient's blood pressure, blood sugar and other health data, and then provide corresponding medical services.

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“…At present, people with various medical and health service needs such as patients, recovered people, healthy, subhealthy, and high-risk groups are flocking to the hospital, this leads to the shortage of clinical diagnosis and treatment service resources and the difficulty of seeing a doctor. However, public health resources such as disease management services and health management services are idle [ 2 ]. This is not to say that it can be solved by increasing the investment in clinical diagnosis and treatment service resources.…”