Research On Android Smart Home App Control System And User Behavior

In recent years,with the rapid development of China’s economy,people’s living standards have been continuously improved,and the requirements on household environment become higher.The traditional concept of life is moving away from us,and people begin to pursue intelligent life.At present,a variety of intelligent products emerge one after another.Android-based smart home products are popular because of their superior performance.The smart home products of Android will be more and more popular with huge users.In order to create a comfortable home experience,this paper designs a smart product with superior performance based on intelligent household function and structure,which can not only control the home equipment remotely,but also excavate users’ behavior habits.The main contents of the thesis are as follows:(1)For the smart home control system,this paper uses home gateways,sensor acquisition circuits,IO relays to control home devices and monitor environment.Firstly,the Android smart terminal sends a control instruction to the cloud server through the Internet,and then the cloud server analyzes the control instruction data.Finally,the parsed data is sent by the router to the home gateway.The home gateway is equal to a home control,which is responsible for communicating with sensor devices.Android smart home App features network communication,data storage,device management,device control,software upgrade,and message push.It is aimed to design a feature-rich and practical App.The results of functional test show that the intelligent control of home devices can be achieved.(2)The smart home users produce a large number of home device operation records every day,and few people performed use behavior analysis on these linked operation records.For this situation,this paper proposes a new GApriori algorithm which is used for data mining and user behavior analysis.The algorithm firstly mines frequent itemsets of user behaviors,and then obtains typical frequent itemsets of user behaviors by clustering frequent itemsets for redundancy.Finally,according to typical frequent itemsets,the user’s behavior habits are derived,and the obtained user behavior habits are pushed to the Android smart terminals through the cloud server.The experimental results show that the algorithm can realize the data mining of user behavior,and then analyze the user behavior habits.