Research And Implementation Of An Active Household Intelligent Lighting System

Internet of things is new period of the technology which called Internet.Objects could be connected through Internet information technology.Meanwhile,the works such as communicating with each other,collecting information etc also could be done.Internet of Things has become the main issue of the technical industry all over the world.Intelligent lighting system is the comprehensive application of Internet of Things,intelligent control and other technologies,to achieve the intelligent control and management of household lighting equipment.so that the intelligent degree of people’s life is further improved.Intelligent lighting technology is extremely important for the construction of smart home life.Consumers in the market have been paying a great sea of attention and recognition to Intelligent lighting devices.Due to the poor performance such as low intelligence and large error of old intelligent home lighting system.This thesis completes the work about the implementation of an active household intelligent Lighting System.The system is on the basis of the Internet of Things.With the study of user control habits mining technology and adaptive lighting brightness adjustment technology,improving the degree of the intelligence and users’ experience.The main works of this thesis are as follows:(1)To solve the problem of low intelligence,the control habit mining technology which relies on improved self-organizing clustering method is proposed.With artificial neural network’s help,self-learning ability is strengthened during the period of initializing algorithm.Generating a reasonable number of category clusters and the corresponding centroid vector is the purpose.Then,a forgetting factor is put to optimize the centroid update strategy.The factor follows the relevant law of H.Ebbinghaus forgetting curve,and improves the brain-like learning ability.In the end,the simulation experiment demonstrates that the algorithm is better than other clustering analysis algorithms in self-organizing learning and brain-like forgetting learning,and it can play a better role in mining the users’ control habits of lighting system.(2)For the purpose of solving the problem of unsatisfactory performance about the error index.The adaptive adjustment technology that is on the basis of adaptive backstepping control algorithm for brightness was proposed in this thesis.The new control technology combines advantages of backstepping control algorithm and adaptive control algorithm.New technology calculates the predicted value of intelligent lighting equipment based on the data of perceptual layer and the expected value of consumers.Results of the experiment certify that the algorithm performs well in reducing error.Both customers’experience and the intelligent degree of lighting system have been improved greatly.(3)Designing and implementing the active home intelligent lighting system on the basis of the Internet of Things.In the first place,the perception layer ensure normal operation of getting the data of perceptual layer and desgning core hardware modules.Network layer makes the transmission of Optical parameters and other data come true.Platform layer’s duty is connecting devices to the network.Meanwhile,processing data with relative algorithm.Application layer is in the charge of controlling of lamps and all lighting modes.The improved data mining technology is used in the thesis to liberate the consumers’ hands and improve intelligent degree of the system.To ensures the accuracy of automatic adjustment for brightness and improve the consumers’ experience.Adaptive backstepping control technology is adopted to control the lighting equipment.