Design And Optimization Of Intelligent Home Control System Based On User's Data

The intelligent home shows us the future household living environment and life style,and satisfies people's expectation of high intelligence,comfortable and safe household life.Therefore,an intelligent home control system has been designed based on user data by synthesizing the advantages of the artificial intelligence and cloud computing technologies and combing the existing sensor network and wireless communication technologies.It has mainly introduced how to conduct household environment data acquisition and fusion processing by multisensor,and to make use of BP neural network's self-learning to analyze the users' historic data,thus realizing the intelligent control.First of all,this work elaborates the development process and the current domestic and overseas research status,and has drawn up the main task of this design according to the existing problems in intelligent home system and its development trend.According to the main task,an intelligent home system is designed.It has also shortly introduced the idea of designing,function to be implemented and techniques involved such as sensor technology,neural network,cloud computing technology from the acquisition layer,transport layer and control layer.Secondly,this thesis completed the overall hardware design of intelligent home system.The hardware system consists of power module,signal acquisition module,the household equipment control module and wireless communication module.The power module provides the power circuit for the safe and stable operation of the whole system,and the APFC circuit is designed to improve the energy saving ability of the system.The signal acquisition module realizes multi-sensor information fusion and processing with sensor network as a core.The household equipment control module mainly realizes the intelligent control of the major household appliances;Wireless communication module is a systematic information transmission method via Wi-Fi.Thirdly,this thesis completed the overall software design of intelligent home system.Thesoftware system consists of signal acquisition software,signal transmission software based on Wi-Fi wireless communication technology,and the household equipment control software.The control software of household equipment studies user's data by BP neural network.The network model is built based on BP neural network.The automatic control of household equipment is realized based on user's history data training.Finally,it has conducted functional test on data acquisition and equipment control to this intelligent home control system.Through the analysis of the testing data,the system can accurately collect real-time household environment data and transmit it to the user so that the user can acquire the home situation at any time.Because of the introduction of BP neural network and the study on the user history data,the system becomes adjusted independently according to the change of environment.Experiments show that data-driven technology can improve the intelligence degree of intelligent home.