Implement And Research On Supermarket Intelligent Shopping Guide System Based On Android

In recent years,with the rapid development of national economy,people's philosophy of life and consumption patterns have undergone great changes.To cater to this change of people,the city's malls and shopping centers are also becoming increasingly more and the types and quantities of goods they have more and more.Although these changes to meet consumer demand,but customers want to find out what you want to buy merchandise in thousands of goods is very difficult.Traditional shopping guide way relied solely on the direction of the target and shopping guide to provide shopping malls,which makes consumers in the large shopping malls easily disoriented.In view of the problems encountered by consumers in shopping malls,this paper designs a shopping mall based on Android platform.The system uses C/S(Client/Server)structure and multiple WiFi layout,to provide the Android system for mobile phones of consumers with shopping malls indoor space electronic map,rapid positioning services,destination navigation services and personalized recommendation services.Android client positioning service uses position fingerprint positioning technology,in offline training phase,the client will be used to collect the WiFi hot spot signal strength value RSSI stored in the database.On line positioning stage,the client collects the RSSI value of the current position with the data stored in the server database through matching algorithm to achieve the client location.The WiFi hotspot can effectively solve the problem that the GPS can not be accurately located in the interior.SVG(Scalable Vector Graphics)technology will be realized the display of the electronic map of the shopping malls indoor environment,combined with DOM analysis and SAX analysis to depict the user's current position and navigation path in the electronic map.The navigation service uses A-Star algorithm to help customers find the best way to reach the target product.Personalized recommendation services using TF-IDF(term frequency-inverse document frequency)algorithm combined with collaborative filtering algorithm,which can not only for consumers to recommend commodity of interest,but also to avoid the traditional collaborative filtering algorithm brings the cold start,interest point drift,data sparsity problem.This paper studies the shopping malls smart shopping guide system,mainly adopt a number of WiFi hot spots of shopping malls to provide consumers with a smart,convenient and user-friendly shopping guide way.The system in the simulation environment of Beijing Nongke building A1017 and A1016 room has been preliminary implementation,and in line with the initial needs analysis.