Design Of Monitoring System For Indoor Intelligent Service System Based On BP Neural Network

With the development of information-sensing technology,artificial intelligence technology and network technology,the quality of people's life has been greatly improved.As the indoor environment is the main living environment,indoor environment monitoring system in this context comes into being.All the indoor environment monitoring systems on the market are very short of intelligentize function.The systems are not inconvenient for users,and can not provide real-time and reasonable serves.An ideal indoor environment monitoring system presents more demanding,such as the ability to collect indoor environment data,the ability to deal with massive data,and the ability to monitor decision-making,to provide users with intelligent,personalized monitoring services.Based on neural network,embedded technology,ZigBee wireless technology and other related technologies,the thesis presents an improved BP neural network algorithm and apply the algorithm to indoor environment monitoring system.For purpose of the systematic management of all the equipment indoor,this thesis builds a wireless sensor networks with all the indoor sensors and equipment by ZigBee wireless technology.This system chooses S3C6410 controller as the hardware development platform.By the server on the S3C6410 controller,users can take remote access to live data.When the live environment parameters are out of preset values,S3C6410 will control associated equipment to attain favorable inhabiting environment.By the analysis and treatment of the sensor data,indoor environment monitoring system gets the data output of corresponding control operation.Thus to ensure the intelligent and intelligent control of the home environment.Aiming at the slow convergence rate of standard BP neural network,the thesis presents to improve learning rate adaptive algorithm of BP neural network.Then,the improved BP neural network algorithm is applied to indoor environment monitoring system,and the algorithm is simulated.Comparing the mean square error convergence curve of standard BP neural network and modified BP neural network,the error convergence speed of improved BP neural network algorithm is improved obviously.Finally,the hardware and software of the system are debugged,and the feasibility of applying the improved BP neural network algorithm in the indoor environment monitoring system is demonstrated.