Research On LoRa Wireless Location System Based On Human Energy Collection And Selfpower Supply

With the rapid development of the Internet of Things,geographic information services based on wireless communication technology are closely related to our production and life.Traditional wireless communication technologies often have shortcomings such as short communication distance and high power consumption,which greatly limit their application range.In particular,various types of terminal nodes in a wireless sensor network are mostly powered by batteries,and cannot be self-sufficient in energy.Therefore,it is particularly important to develop a low-power,long-distance and self-powered wireless sensor network positioning system.Aiming at the problem of self-powering of terminal nodes in wireless sensor networks,this paper proposes an energy collection scheme for human body motion potential.The motion capture device is used to collect the body motion information under the natural behavior of the human body,and the motion characteristics of the limb position motion are analyzed,and a type of energy conversion mechanism adapted to the human body motion characteristics is designed.For the energy output characteristics of the conversion mechanism,a kind of energy collection circuit is designed to convert the weak pulse energy storage output by the human energy conversion mechanism into the energy source for the terminal nodes in the wireless sensor network.The experimental results show that the energy conversion efficiency of the energy collection system proposed in this paper reaches 41.5%,and the output power of the calorie can be collected to 2.5mW,which meets the daily needs of many low-power electronic products.For the traditional wireless communication technology positioning,there are problems such as short communication distance,high power consumption,and low positioning accuracy.This paper adopts a solution based on LoRa communication technology.By analyzing the characteristics of LoRa communication technology and traditional RSSI positioning method,a LoRa wireless sensor network positioning system based on BP neural network is proposed.In the off-line phase,a data acquisition model is established for mapping the anchor node's own coordinates with the received RSSI values;the data is collected during the online phase,and the data is preprocessed,and the trained BP neural network is used for positioning.The results show that compared with the traditional RSSI positioning algorithm,the LoRa wireless sensor network positioning system based on BP neural network proposed in this paper has greatly improved the positioning accuracy and stability.