Research On Energy Harvesting And Allocation Of Node In Motion Rechargeable Wireless Body Area Networks

In recent years,the development of wireless communication technology and microelectronic technology has made the wireless body area network based on wearable computing devices have received extensive attention,which has brought great convenience to people's lives,especially in the field of human health monitoring.By wearing a micro-inertial sensor to collect daily activity signals,remote health monitoring and analysis of the living rules and health status of the monitored objects can be realized.In the traditional wireless body area network,the node has limitations in power supply and becomes the bottleneck of its development.The new charging method of energy harvesting technology makes the node expected to achieve continuous self-power supply.However,due to the instability of the energy collected from the environment,it is very important to allocate and optimize the energy in the wireless body area network.In this paper,the wireless body area network node that collects human kinetic energy is taken as the research object.Achieving long-term continuous operation of wearable devices under the performance of human activity monitoring requirements is taken as the research goal.Research from the issue of kinetic energy harvesting and distribution.The main work is as follows:1.The human motion data acquisition platform based on energy harvester and accelerometer is designed and implemented,and a human daily activity data set and human exercise energy data set based on human motion acceleration are established.The daily activity data set of the human body is composed of data samples of seven daily exercises of ten testers(5 boys and 5 girls).The human exercise energy data set is a sample of exercise energy data collected under one's daily behavior habits.All data collection is performed using a single sensor node placed on the body under naturally unconstrained conditions.2.In this paper,we studied the problem of energy allocation and optimization under the condition of battery limitation in mobile rechargeable wireless body area network.And established the mathematical model of energy allocation optimization based on motion rechargeable wireless body area network.This model fully considers the relationship between the recognition performance and power consumption of the sensor node in the actual working process.The node energy distribution is realizedwhile ensuring that the node can work continuously and the energy is not wasted as much as possible,thereby maximizing the average recognition rate of the network.3.For the deterministic energy harvesting process and the random energy harvesting process,the offline and online energy allocation algorithms are designed respectively.The offline energy allocation algorithm adopts a heuristic adaptive energy allocation scheme.According to the relationship between the recognition accuracy of different actions and the system power consumption,the sensor node achieves an average recognition accuracy of 96.47% while saving 28.2 mW of the system energy consumption.The online energy allocation algorithm is an energy distribution scheme designed for the random motion energy harvesting process.It is not necessary to know the subsequent energy harvesting when energy distribution is performed on a time slot.The simulation experiment proves its superiority.