Research And Design Of Smart Home System Based On Cloud Platform

Smart home is a manifestation of the Internet of Things under the influence of the Internet and the Internet of Things.It aims to connect home devices in different fields through wireless sensing technology,Internet of Things technology and Internet technology to work together efficiently and improve user perception of various devices.Control ability to improve the comfort and intelligence of the house.The traditional smart home system deploys most of the software functions on the local server of the home.TThere are problems such as low data storage,high response delay,and difficulty in software upgrade and expansion.This article introduces cloud computing in smart homes,uses cloud platforms as data storage and exchange platforms,and cooperates with home gateway,APP,and Web platform to complete data transmission and communication control of smart home systems,recording the working status of home APPliances and indoor environment perception Data,and realize the remote control of home equipment through the APP terminal and Web platform.Combined with actual analysis,WIFI technology is selected as the network access method for home APPliances.The system hardware part selects STM32 as the main control chip to control various electrical APPliances.The DHT11 temperature and humidity and BH1750 light sensor are used to obtain indoor sensory data.Establish a connection and exchange information with the cloud server.The software part adopts the APPlication layer HTTP protocol as the network communication protocol,uses the JSON format as the data exchange format of the cloud platform,and MYSQL as the system database,develops the cloud platform software function based on the PHP language,and completes the communication process and page function for the Web platform and APP The design of the module.The system leases Alibaba Cloud Server(ECS)and builds a lightweight Nginx server as a Web server based on the Linux + PHP environment.And introduce the Aprior algorithm to screen users’ high-frequency and strong correlation behavior through the SPSS data analysis software as the direction of the cloud platform service function expansion and upgrade.Based on the BP neural network,the indoor temperature and humidity values are predicted using a single-step prediction method.The prediction model is deployed in Cloud platform,the system collects real-time data from the environment and enters the prediction model to obtain the predicted value,and then controls the underlying equipment to adjust the indoor temperature and humidity value.Finally,the test and implementation of the main functions of the system are completed.The temperature and humidity value prediction model and the cloud platform API test results meet the design requirements.