Design And Implementation Of WLAN Indoor Positioning System Based On CNN

Many cities have sprung up different kinds of large shopping malls in recent years.Its style is diverse,with complex structure.It has caused troubles to customers with a weak sense of direction.At the same time,it also reduces the flow of people to the merchants in remote locations.The distribution of paper leaflets not only cannot introduce the store information in detail but also causes unnecessary waste of resources.Therefore,it is necessary to develop an indoor positioning system with the function of merchant push.The main research contents of this paper are as follows based on the above problems:(1)Let the indoor positioning system cater to the public more with the adoption of WLANs as AP nodes.The key point of indoor positioning technology lies in the accuracy of positioning and the convenience of use.In this thesis,the RSSI location fingerprint positioning method is used,RSSI is preprocessed by the median filter,and then the observation coordinates are obtained by CNN training and calculation.Finally,the moving target trajectory is corrected by the Kalman filter,and the final positioning trajectory is smoother and closer to the real trajectory.(2)The system is mainly composed of a Wi-Fi beacon,server platform,and WeChat applet in the design of the WLAN indoor positioning system based on CNN.Wi-Fi beacon is the source of the system and broadcasts Wi-Fi signals regularly.The server platform is the core and center of the whole system.On the one hand,it interfaces with WeChat applets.On the other hand,it needs to configure CNN neural network.WeChat applet is based on WeChat APP and provides users with real-time location queries through docking communication with the server platform.(3)The algorithm and system are further applied to the scene based on designing CNN WLAN indoor positioning system.The application of the system provides clear direction guidance for people with a poor sense of direction and provides opportunities for businesses in poor areas to increase the flow of people.The push of goods in APP reduces the waste of paper leaflets and customers'understanding of unknown shops.Long-term observation of big data user behavior can provide more considerable business opportunities.