Research On Customer Behavior Analysis System Of Home Party Based On RFID Location Technology

With the rapid development of Internet of Things Technology,location-based information services play an increasingly important role in people's lives.Due to the serious interference of satellite signal propagation in indoor environment,global positioning system is difficult to meet the needs of indoor positioning services,and indoor positioning system has become a research hotspot.Based on the practical application requirements of the Home Party,this paper designs a customer behavior analysis system based on RFID positioning technology for the problem of large error and poor stability of indoor positioning system.The system can realize the real-time positioning of customers,and can use the positioning results for data analysis to improve the customer experience and guide the store operation.The main contents of this paper are as follows:1.Data cleaning model and Improvement of the weighted centroid algorithm.Firstly,Wireless Signal Propagation Loss Model is optimized.Additional factors related to signal strength are added to the typical shadow model,and the loss model is determined by curve fitting.Furthermore,in order to improve the accuracy of the distance data,a data cleaning model based on normal distribution is established.The abnormal data is eliminated by confidence,and new data is inserted by Newton interpolation method.The traditional positioning algorithm only considers that the intersection of three circles forms a common triangle.In this paper,a weighted centroid localization algorithm based on Euclidean distribution is proposed,which is modified from the intersection of three circles and the intersection of two circles respectively.The weighting factor is distributed by the distance between the measured point and the beacon node.The closer the distance is,the larger the weighting factor is.The test results show that the improved algorithm in this paper reduces the positioning error.2.Customer behavior analysis and personalized recommendation model based on TOPSIS algorithm.According to the types of entertainment facilities in the Home Party,the regional is obtained.The staying time and arrival times of customers in different areas are obtained from the positioning data,and the feature evaluation matrix is constructed based on the consumption information of the client.The TOPSIS algorithm is used to establish the regional heat and customer behavior preference model and analyze the popularity of each region and the degree of customer preference for each region.Combining the behavior analysis results with the customer similarity matrix to establish a personalized recommendation model to study the potential areas of interest of customers and recommend regional and path to them.Finally the feasibility of the model built in this paper is verified by an example analysis.3.Development of the customer behavior analysis system of the Home Party based on RFID positioning technology.The card reader is used to collect the electronic tag signals and transmit them to the micro-base station for aggregation.The micro-base station and the client platform ensure that the registration is valid through heartbeat instruction,and then the information is uploaded to the platform via the router.The acquired data is preprocessed by curve fitting,dithering algorithm and sliding window,and further transmitted to the positioning calculation module to calculate coordinates.This paper develops the positioning analysis system interface to visually display the positioning and behavior analysis results.The experimental results show that the system designed in this paper has a good positioning effect and meets the needs of the Home Party.