Design And Research Of Smart Home System Based On Internet Of Things

Smart home is a kind of intelligent family living environment.It is still in the development stage,the standard is not unified enough.The development of new technology such as Internet of things provides a better solution for smart home system.The design and research of intelligent home system based on Internet of things has innovative and practical significance.The scheme designed in this paper can monitor the family living environment independently,control the family living environment from any distance,make the family life more comfortable and convenient,safer,and save energy and protect the environment.This paper mainly based on the Internet of things related technology,the construction of intelligent home system.First of all,the overall design of smart home system is planned.Then,from the selection of sensors and actuators in the hardware layer of home products,the design of middleware in the hardware layer,sensor acquisition and actuator control,use the transport layer to upload or download to the software middleware layer,to the final application layer design.Home products use sensors(such as temperature,humidity,gas concentration)to collect data to the hardware,hardware control home lights,locks,motors and other actuators.The protocols of transport layer are mainly Wifi,Ethernet and NB-IOT.The cloud platform of the Internet of things uses technologies such as HTML5,JS,AJAX,CSS,etc.The back end uses PHP's slim framework to write a Restful style API,the database uses MYSQL,and the data interactive format uses JSON.The mobile APP uses APP Inventor2 to develop an API interface for reading sensor data and controlling the actuator.This is the whole technology architecture of the intelligent home system based on Internet of things,which is also the main research content of this paper.In addition,the prediction of PMV thermal comfort model in smart home based on BP neural network is also studied,and the PMV thermal comfort controller based on fuzzy control is designed.Through common filtering algorithm or Kalman filter to optimize the accuracy of sensor data acquisition.With the help of edge computing,the smart home system can be redeployed to ensure the security and privacy of the data in the smart home system and relieve the pressure of external servers.Finally,the feasibility of the scheme is verified by experiments in the real family environment.The research results are as follows: First,the hardware has the intelligent distribution network function,the data collection precision is high and so on,can satisfy the intelligent home product data collection and the control;The software uses a flexible interface,so as long as the API is followed,it can be applied not only to smart home products,but also to other Internet of things related products,BP neural network is used to predict PMV thermal comfort model in smart home.The prediction error is small,and it is convenient to add into the mold and controller to control the thermal comfort of home.This paper also provides reference for the follow-up study of the whole smart home system.