Construction And Implementation Of A Cloud Nursing Health Service Platform Bases On K-means Aigorithm

With the improvement of the Chinese people’s economic level,people’s pursuit has shifted from simply eating,drinking,warming to a well-off,to pursuing wealth in the spiritual world.But at the same time,more and more sub-healthy people are suffering from various diseases such as diabetes,hypertension,and cardiovascular and cerebrovascular diseases.So how to prevent the sub-health from aggravating or even reaching the abyss of disease?This has always been a problem.This article is intended to break through the traditional embarrassment of treating small illnesses and having no money to cure major illnesses.Design a health management platform.People can monitor their physical health status by wearing health-sensing devices,and prevent people from falling from sub-health status to the abyss of disease through the platform’s early warning and prediction.This paper introduces the classic algorithm k-means and random forest algorithm into the code of the background architecture.The platform studied in this paper is itself a platform that can monitor the user’s physical health,and can make a real-time Early warning reminder.Now that this k-means algorithm function module is introduced,a cluster analysis can be performed on the existing data,and then the random forest can be used to analyze the user’s physical state in the future based on the clustered data.Based on the above ideas,the functions to be implemented in this paper start from the architecture of the health management platform,and first realize the overall background function framework required,so that the code without the algorithm and prediction module will run first,and then consider adding k-means algorithm module and the random forest module are used to make a prediction based on the existing data of a user to remind the user what kind of condition his body will be in the next period.The overall background framework of this thesis is built and implemented based on python3.6+Django2.0.Through smart wearable devices,this thesis uses a health management bracelet to collect various physical indicators of the human body,and uses mobile phones as middleware.It is then transmitted to the background for analysis,and then the k-means algorithm and random forest are used to predict the user’s physical condition.