Design Of Intelligent Home Environment Monitoring System Based On Internet Of Things And Artificial Neural Network

With the rapid development of Internet of Things technology and the continuous improvement of people's living standards,people's requirements for home life's intelligence and comfort have also gradually increased.Smart homes come into being in this context.This article combines the Internet of Things technology,designed a smart home environment monitoring system based on the embedded gateway,the system can monitor all major environmental parameters in the home in real time,artificial neural network algorithm to indoor environment parameters as input to simulate people in the home Comfort experience in the environment;At the same time using openHAB?open home automation bus?based intelligent gateway design to solve poor device compatibility and network heterogeneous issues.The subject first studied several commonly used wireless communication technologies such as EnOcean and ZigBee,and compared and analyzed their operating frequencies and other characteristics,determined the internal network construction process of the home environment and conducted networking to monitor the temperature,humidity,light intensity,and CO₂ concentration in the home environment in real time.The main environmental parameters affecting human comfort.Secondly,it studies the establishment of home intelligent gateway and middleware technology.The embedded gateway adopts Raspberry Pi 3B and Linux operating system as embedded systems,uses middleware technology to connect smart home devices of different protocols,and compiles home automation programs and user interfaces of various terminals through the configuration of WiFi and Bluetooth.Other functional components allow the system to support multiple protocols and weather services,use the RRD database to record environmental data,use motion software to implement camera video surveillance,and implement remote login management functions.Afterwards,a human comfort evaluation system model was established to determine the main environmental parameters affecting human comfort,and BP neural network models,fuzzy set theory models,fuzzy neural network models,etc.were separately studied.Finally,human comfort was established through artificial neural networks.Evaluation system model to achieve the evaluation of human comfort.Finally,designing the mobile phone and Web page client mainly includes combining the openHAB software function to complete the interface layout,increasing the response speed of the server by loading the JavaScript script form,and using the AJAX technology to realize partial data refresh of the web page.Through the client interface operation,the overall system function is tested.Based on the analysis of test results,the home environment internal network,embedded gateway,mobile phone,and Web client can run normally in this system.The environment data and human comfort can be queried in real time,effectively supporting multiple devices and protocols,and enabling remote Functions such as login,database and camera video monitoring can meet the system design expectations.The smart home environment monitoring system improves the applicability of the smart home system to a certain extent,enhances the comfort of the user,and reduces the user's use cost.