A data decision-making method, device and system

Abstract

Embodiments of the present invention provide a data decision-making method, device, and system, which relate to the field of communication technologies and can accurately and effectively analyze information contained in fragmented data. The solution includes: the data decision device obtains analysis conditions for data analysis; the data decision device reports the analysis conditions to the cloud server, so that the cloud server determines a first data type that the data decision device can process according to the analysis conditions; First data of a data type, where the first data is sensory data generated by a human body device connected to the data decision device; the data decision device performs data analysis and data decision on the first data, and generates first decision data, the first decision data It is decision information for the data features reflected 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.

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