Research And Design Of Environmental Comfort Adjustment Software For Smart Families

With the continuous popularization of smart home products and the continuous improvement of people's living standard,people pay more and more attention to the comfort of home environment.This thesis introduces the PMV index of ISO7730 standard to study the comfort of family environment.This index involves indoor air temperature,indoor wind speed,average radiation temperature,relative humidity,clothing thermal resistance,human activity and human mechanical work.The traditional temperature control system cannot adjust the environmental comfort scientifically.This thesis collects and analyzes the historical data of the user's environment,and completes the development of the home environment comfort adjustment software,which can meet the user's personalized needs for comfort adjustment.1.Study the current situation of comfort adjustment in family environment.This thesis studies the development of home environment comfort and neural network,and expounds the importance of autonomous adjustment of comfort in smart home.2.Design the overall scheme of the comfort adjustment software.This thesis analyzes the system architecture,requirements and performance of the comfort adjustment software,and gives the design scheme of the comfort adjustment software.At the same time,the key technologies used in the software are analyzed and studied.3.Develop major devices that support the running of the software.The primary devices are the underlying nodes and the home gateway.The bottom node can be divided into control node and sensor node.CC2530 is used as the main control chip and Zig Bee is used to realize wireless networking.Node development includes power circuit,reset circuit,serial port circuit and CC2530 main chip circuit.The home gateway contains RT5350 main chip circuit,Zig Bee coordinator circuit,interface circuit,memory circuit and power circuit.4.Develop family environment comfort adjustment software.The comfort adjustment software uses the Django framework's MVT model to develop the various functional modules of the software.The functions of the software include home data information management module,user management module,indoor comfort adjustment module,equipment information management module and home electrical control module.The comfort adjustment module uses BP neural network to solve the PMV index,and adjusts the comfort of the environment by changing the indoor temperature and humidity,which solves the problem of continuous iteration and poor timeliness in the traditional PMV solution.5.Set up the test environment of the environment comfort adjustment software.According to the requirements of the software quality testing standards GB/T25000.51-2016 and GB/T25000.51-2016,this thesis tests the software function,performance and compatibility of the comfort adjustment software.The test results show that the software meets the user's demand for adjusting the comfort level of the home environment.The function,performance and compatibility of the software conform to relevant testing requirements.