Method for multi-sensor adaptation and real-time data acquisition of wearable device

Abstract

The invention discloses a method for multi-sensor adaptation and real-time data acquisition of a wearable device. The method comprises the following steps that S1 Bluetooth device adaptation, namely a Bluetooth device develops a broadcast packet feature recognition module, a control interface module and a data standardization module; S2 device binding, namely a cloud server establishes a binding relationship between a user ID (Identification) and a device ID in a database; and S3 concurrent real-time acquisition of multi-sensor data, namely a user logs in to the cloud server on a mobile intelligent terminal to obtain a list for the bound devices, the mobile intelligent terminal opens Bluetooth scan and compares the device ID of each Bluetooth device discovered through scanning with the ID of the bound device, a new device thread is created if matching and a connection is established. The method has the beneficial effects that real-time acquisition of the cross-manufacturer multi-sensor data is realized, real-time processing requirements for the multi-sensor data are met, and real-time concurrent acquisition of the multi-sensor data is realized.

Description

Technical field [0001] The present invention involves multi -sensor adaptation and real -time data collection technology fields such as human physiological indicators, and specificly involves a wearable device multi -sensor adaptation and real -time data collection method. Background technique [0002] In recent years, due to the innovation of sensor technology, especially the technical progress of the micro-electromeChanicalSystems (MEMS) and biosensors (MEMS), the wearable smart devices containing various micro-sensors have continued to appear and are applied to human body-relatedThe collection of various data, which derives corresponding applications and services, such as smart homes in the field of automated control, positioning applications in security, and remote monitoring in human health. [0003] The data of common micro-electromeChanicalSystems (MEMS) and biosensors (Biosensor) include the following categories: the following categories: [0004] 1) Various physiological...

AI Technical Summary

Problems solved by technology

[0008] 1. The problem of singleness: Due to technical limitations such as chip technology, low power requirements, and small size of wearable devices, the hardware of specific wearable smart devices often includes one or a few sensors, which can only collect specific information

Relevant manufacturers often focus on processing the relevant information collected by their own developed hardware devices, and the types of sensors supported are relatively single

[0009] 2. Compatibility issues: Different manufacturers implement different interfaces for the same type of sensor

This results in the fact that the same sensors are incompatible with each other, affecting the use of users

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