Design And Implementation Of Smart Home System Based On User Habit

With the development of technology,people have higher requirements for the quality of their life,and smart home has become more and more popular.Nowadays,the smart home system can only provide the monitoring of your home,remote control or voice control of electrical appliances.But it is not real intelligent control and still needs the control of human.With the rapid development of artificial intelligence,we can create a truly intelligent home system by the technology of artificial intelligence and Internet of Things.The purpose of this thesis is to develop a smart home system based on the users’ habits,which means the smart home system can intelligently control home appliances by learning different environmental data according to users’ habits.As a result,the smart home system will develop its own "big brain".The main work of this system is as follows:(1)Design the overall framework of the system and divide the system into two parts.One is a hardware terminal responsible for collecting environmental data and controlling home appliances.And the other is a software platform responsible for storing data and using predictive algorithms for control.(2)Design and implement an environmental data collection module.In this thesis,the solution of Arduino + sensor + wifi module is used to collect various environmental data of the house such as temperature,humidity,light intensity,etc.and upload the data to the server,which is convenient for using neural networks to learn.(3)Design and implement a remote control module.This thesis uses the Arduino +controller + wifi module solution to receive control commands sent by the IoT platform and control the corresponding home appliances.(4)Design and implement the cloud remote control page.This article uses the solution of vue + springboot,uses vue to design the front-end page,uses java to write the background program,and the project runs on the Alibaba Cloud server.Through the control page,you can view important real-time environmental data and curve graphs,and you can control home appliances through switch buttons and adjustment sliders.(5)Design and implement a prediction module.The prediction algorithm is based on the long-term and short-term memory(LSTM)network.The data of the cloud database is used for model training and testing.And it’s used to predict the key environmental data.According to the prediction results,corresponding control instructions are sent to the IoT platform.In order to verify that the system can run normally and effectively,this thesis tests each part of the system.After experiments and tests,each part of the system can run normally and control the home appliances according to the results of the prediction algorithm.And the whole system achieves the expected effect.By combining the Internet of Things with artificial intelligence,the system can intelligently make future decisions for users according to the historical house environment data and the habits of individual users,allowing users to experience the intelligence and convenience of smart homes.