基于ZIGBEE技术的嵌入式智能家居系统的研究

发布时间：2018-01-07 21:30

本文关键词：基于ZIGBEE技术的嵌入式智能家居系统的研究　出处：《天津工业大学》2017年硕士论文　论文类型：学位论文

更多相关文章： 智能家居 ZigBee RBF神经网络算法 ARM

【摘要】：随着生活质量的日益提高,人们追求智能化居住环境的期望更加强烈。为满足人们对居住环境智能化的需求,智能家居系统越来越受到重视。但传统智能家居系统多以有线的方式构建智能家居网络,不仅成本高,而且扩展性、美观程度都存在不足;系统仅仅能够实现用户的远程控制或预设参数的简单逻辑控制,不具备学习能力。论文比较了不同的智能家居网络组网方案,确定以ZigBee技术为基础组建智能家居网络;针对传统智能家居系统学习能力不足的特点,提出了一种基于ZigBee技术的采用神经网络使其具有学习能力的智能家居系统总体设计方案,通过运用神经网络作为辅助决策系统的机器学习算法,提高系统的智能性。根据系统的设计方案,采用RBF神经网络对温度、光照强度的控制进行建模、仿真,验证了在智能家居系统中引入RBF神经网络算法的可行性,接着完成了对该算法在主控制器模块上的移植。硬件上,采用三星公司的S3C2440作为智能网关的核心控制器,并添加电源模块、SDRAM存储器、以太网模块、触摸显示屏等模块及辅助电路,同时采用TI公司的CC2530作为ZigBee组网模块,完成了包括智能网关的电路设计、电路调试以及相关底层传感器与执行器的设计与调试。软件上,通过分析和研究Z-Stack协议栈的工作流程,实现了 ZigBee网络的组网、不同节点间的透传以及不同功能节点的软件编程,并通过构建Linux操作系统开发环境、设计智能网关应用软件以及移植嵌入式Boa服务器,完成了对智能网关的软件开发,其中智能网关的应用软件主要由设备监控进程与图形化显示进程两个部分组成。最后,对整个智能家居系统进行了软硬件调试,并对其功能进行了测试,验证了学习型智能家居系统的性能。
[Abstract]:With the increasing improvement of the quality of life, people want to pursue intelligent living environment more strongly. In order to meet the people's demand for intelligent living environment. More and more attention has been paid to the smart home system. But the traditional smart home system constructs the smart home network in the way of cable, which is not only high cost, but also expandability and aesthetic degree is insufficient. The system can only realize the remote control of users or simple logic control of preset parameters, and does not have learning ability. Decide to set up smart home network based on ZigBee technology; In view of the lack of learning ability of the traditional smart home system, this paper presents an overall design scheme of the intelligent home system based on ZigBee technology, which uses neural network to make it have the learning ability. By using the neural network as the machine learning algorithm of the auxiliary decision-making system, the intelligence of the system is improved. According to the design scheme of the system, RBF neural network is used to model the control of temperature and illumination intensity. Simulation results demonstrate the feasibility of introducing RBF neural network algorithm into smart home system, and then complete the transplantation of the algorithm in the main controller module. Hardware. The S3C2440 of Samsung Company is used as the core controller of the intelligent gateway, and the power module is added, such as SDRAM memory, Ethernet module, touch display screen and auxiliary circuit. At the same time, the CC2530 of TI Company is used as the ZigBee networking module, and the circuit design including the intelligent gateway is completed. Circuit debugging and the design and debugging of related bottom sensors and actuators. Software, through analyzing and studying the working flow of Z-Stack protocol stack, the network of ZigBee network is realized. The transmission between different nodes and the software programming of different functional nodes, and through the construction of Linux operating system development environment, the design of intelligent gateway application software and transplantation of embedded Boa server. The software development of intelligent gateway is completed, in which the application software of intelligent gateway is mainly composed of two parts: device monitoring process and graphical display process. Finally, the software and hardware of the whole smart home system are debugged. The function of the system is tested and the performance of the learning smart home system is verified.
【学位授予单位】：天津工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TU855;TN92

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