Data decision method, device and system

Abstract

The invention provides a data decision method, device and system, which relate to the communication technology field and can accurately and effectively analyze information contained by fragmented data. The data decision method comprises: a data decision device obtains an analysis condition for performing data analysis and reports the analysis condition to a cloud server in order to make the cloud server determine that the data decision device can process first kind data according to the analysis condition; the data decision device obtains first data satisfying the first data kind, wherein the first data is sensing data generated by a human body device connected to the data decision device; and the data decision device performs data analysis and data decision on the first data in order to generate first decision data, wherein the first decision data is decision information reflecting data characteristics by the first data.

Description

technical field [0001] The present invention relates to the field of communication technology, in particular to a data decision-making method, device and system. Background technique [0002] At present, a large number of wearable devices (such as smart bracelets) and implantable devices (such as cardiac pacemakers) have been widely used in the daily life of users. These human body devices (this application refers to wearable devices and implantable devices as Human body device) can perceive the parameters of human body activities and the external environment, and the human body device can summarize the obtained data so that users can reasonably arrange various matters in life according to the data provided by the human body device. [0003] However, with the emergence of a large number of human body devices, everyone may have multiple human body devices at the same time, so how to effectively analyze the data provided by multiple human body devices has become an urgent prob...

AI Technical Summary

Problems solved by technology

For example, when a user falls, the posture detector on his body will obtain posture change data, the blood pressure monitor will obtain blood pressure change data, and the heart rate monitor will obtain heart rate change data. The data are collectively referred to as perception data. It can be seen that the perception data obtained by these human body devices is fragmented, and it is impossible to provide users with more accurate data analysis results based on these fragmented data.

Images