Community-oriented ZigBee-based low-power-consumption fall detection system

Abstract

The invention discloses a community-oriented ZigBee-based low-power-consumption fall detection system. The system comprises a plurality of motion sensing modules and a server, wherein the motion sensing modules adopt ZigBee and an interrupt function to realize low-power-consumption human body motion data acquisition and transmit the acquired motion data to the server which integrates ZigBee aggregation nodes through a ZigBee network; the server performs Kalman filtering and analyzes and detects whether falling occurs or not by a kNN algorithm; once falling is detected, the system automaticallyalarms. In the aspect of the transmission distance, the motion range of a user is widened well; in the aspect of user falling data acquisition and transmission, equipment with low power consumption and an interrupt-driven data transmission algorithm are adopted, so that the problem of high energy consumption of wearing equipment is solved; in the aspect of falling data processing and detection, the precision of detecting and identifying falling is improved; and in the aspect of falling alarm, warning and notification can be conducted timely.

Description

technical field [0001] The invention belongs to the field of electronic information, and relates to a community-oriented ZigBee-based low-power fall detection system. Background technique [0002] The traditional wearable fall technology based on 3-axis accelerometer and gyroscope ignores the objective constraints of limited computing power and power supply of wearable devices. The main processing unit of the wearable device detects the 3-axis accelerometer and gyroscope online in real time, and sends the read 3-axis acceleration and angular velocity data to the computing device at the receiving end through the radio frequency module, and then performs fall detection. Since the main processing unit in the wearable device needs to monitor data in real time, and the radio frequency unit needs to send data in real time, the system consumes a lot of power. [0003] In addition, traditional fall detection is mostly based on Bluetooth technology, and the transmission distance of ...

AI Technical Summary

Problems solved by technology

Since the main processing unit in the wearable device needs to monitor data in real time and the radio frequency unit needs to send data in real time, the system consumes a lot of power

[0003] In addition, traditional fall detection is mostly based on Bluetooth technology, and the transmission distance of Bluetooth is usually about 10 meters, and the transmission range is limited; in addition, Bluetooth communication is easily interfered by occlusion, and usually uses a point-to-point communication method, which can only be applied to individual or family users. It is difficult to meet the needs of multi-user real-time detection in the elderly community

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