The Research And Implementation Of Bluetooth Intelligent Lighting System Based On Android

With the continuous progress of the internet of things and communication technology in the 21 st century,intelligent home has become an inevitable trend in the future.As an indispensable subsystem of smart home,intelligent lighting begins to influence and change people’s concept.In daily life,people’s demands for lighting environment are not only brightness can be adjusted with personal habits,but also different lighting effects can be used in various life scenes,and the energy efficient is guaranteed at the same time.In recent years,lighting system combined with intelligent terminals has been developed rapidly in the mobile internet era.In this thesis,a Bluetooth intelligent lighting system based on Android is studied and designed in the background of the innovative project,EcoxLight lighting control system based on internet of things in Wode Technology Co.,Ltd.in Chongqing.The main work and innovation are as follows:Firstly,Android-based Bluetooth smart lighting client software is designed and developed.The intelligent lighting client application with the modules of light color control,timer switch,custom life scenes and other functions is designed by using Android programming and Bluetooth 4.0 instant messaging technology.The application can achieve real-time control of the lamps through a friendly human-computer interaction interface.Considering that the intelligent lighting client software designed in this thesis needs to communicate with lamps in point-to-multipoint way frequently,a communication scheduling algorithm based on energy priority is proposed at the software side,which increases the cooperative working length of each device node.The client software has the following advantages: easy-operation,friendly interface,high stability,so this system has a broad prospects in application market.Then,an adaptive lighting algorithm based on BP neural network is proposed for the shortcomings of the existing intelligent lighting system with poor adaptive dimming.By introducing the BP neural network algorithm into the intelligent lighting system,the lighting device can adjust brightness adaptively according to the surrounding environment and the user’s habits.First,the appropriate data parameters are selected according to the realization principle of BP neural network,and the BP neural network model is constructed,then the experimental data are inputted into the above model for training.Finally,the brightness prediction algorithm proposed in this thesis is simulated on the MATLAB simulation platform.The simulation results show that the predicted luminance data are within the acceptable error range compared with the user’s expected data.Meanwhile,the power consumption is reduced.