Self-adaptive physiological monitoring and intelligent scheduling positioning system and method

Abstract

The invention relates to a self-adaptive physiological monitoring and intelligent scheduling positioning system and method. The system comprises a physiological data monitoring module and a rescue module. The physiological data monitoring module is used for collecting physiological data of a human body by utilizing a somatosensory network, dividing priority levels of the data through an RM-MAC improved protocol, and carrying out self-adaptive transmission through an RS algorithm; and the rescue module is used for assisting medical staff to efficiently position a patient by using a multi-source heterogeneous indoor sensing positioning and sensing node advanced scheduling technology when the physiological data of the user is abnormal, so that the patient is rescued in time and the energy consumption of an indoor heterogeneous sensing positioning network is saved. The deep learning target trajectory prediction technology is applied to the indoor rescue module, high-performance scheduling is performed on position tracking nodes in advance through trajectory prediction, the sensing tracking precision is ensured, the network energy consumption is reduced, and when the system monitors abnormal physiological data possibly endangering the life of a patient, the system can be used for monitoring the abnormal physiological data possibly endangering the life of the patient. The rescue module can implement efficient and rapid location rescue to avoid risks.

Description

technical field [0001] The invention relates to the technical field of physiological monitoring and pedestrian trajectory prediction, in particular to an adaptive physiological monitoring and intelligent dispatching and positioning system and method. Background technique [0002] With the development of wireless wearable biosensors, more heterogeneous wireless wearable biosensors are used in combination to identify and monitor complex physiological states of the human body, and these combinations are called low-power and low-cost wireless body-area networks ( WBANs). WBSNs have multiple application domains, such as healthcare, military, entertainment, and sports. Currently, WBANs are mainly applied in health monitoring. As the requirement for high-performance WBANs increases, it leads to the birth of IEEE 802.15.6, which is a communication standard specially designed for WBANs. Scholars have designed many algorithms and communication protocols with advanced performance ba...

AI Technical Summary

Problems solved by technology

However, the indoor positioning scheme based on WSN also has problems such as limited energy and difficult replenishment, and the most common method to extend the life of the WSN network is sleep scheduling, which makes some redundant nodes enter the dormant state while ensuring the coverage of the monitored area. , and then update the node state through the wake-up algorithm

However, this method may reduce the accuracy of location tracking

It is very difficult to carry out rescue work when the positioning accuracy is insufficient, and it is even possible to miss the best rescue time for the patient

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