基于ARM9的智能家居系统设计
发布时间：2018-07-18 10:47
【摘要】：智能家居作为物联网领域的重要应用发展迅速。近年来,国内涌现了大量的智能家居企业,传统的家电企业也纷纷开启了自己的智能家居模式,甚至连三星、谷歌等公司也加入到了智能家居的研究浪潮中,研究构建一个便捷、高效、低成本的智能家居系统将有重要的使用价值。 本文结合嵌入式linux技术、ZigBee技术和QT技术,设计开发了一套基于ARM9的智能家居系统,为用户提供舒适、便利、智能的生活环境。 文章开始介绍了目前智能家居行业的背景及其国内外发展状况,随后,结合目前家庭内部家用电器和其他家庭设备的实际情况,在调查了部分用户对于智能家居的功能需求、分析讨论了系统实现的可能性以后,介绍了智能家居系统的总体架构,设计了系统的软硬件方案。从功能角度来讲,本系统可以划分成无线传感器网络子系统和红外自学习遥控器子系统。 BOA服务器以及用户交互页面是实现两个子系统功能的基础。BOA服务器、HTML网页以及CGI后台处理程序使得用户在任何地点任何时间接入智能家居系统成为可能,用户在系统交互页面经用户信息验证后,即可完成对家庭普通设备和配备遥控器设备的控制以及住宅信息的获取。无线传感器网络子系统中,通过研究ZigBee无线传感器网络协议,结合室内的布局情况,组建了适用于住宅内部的无线传感器网络,网络中设置了协调器节点、路由器节点和终端节点并依据节点之间的数据传输方式设计了各个节点的应用程序,此外,为了便于无线传感器网络内部的数据传输以及各节点和BOA服务器对传输数据的识别和关键信息的提取,本文还按照计算机网络中数据包的设计思想制定了无线传感器网络子系统的数据传输标准。红外自学习遥控器子系统是利用ARM9技术、QT技术和WEBKIT技术设计实现的一个红外自学习遥控器,此遥控器和无线传感器网络子系统配合,实现了用户与目前家庭中绝大部分设备的远程交互,减少了控制盲点,本文重点讲述了红外自学习遥控器QT主界面的设计、编译、移植过程和基于WEBKIT技术的远程控制方法,测试结果表明,本文设计的红外自学习遥控器不仅可以集中控制而且可以通过网络远程控制各个配备遥控器的家电设备,此外,本文设计的红外自学习遥控器在性能、可扩展性和在智能家居系统中的应用等方面也具有较多独特的优势。
[Abstract]:As an important application of the Internet of things, smart home is developing rapidly. In recent years, a large number of smart home enterprises have emerged in our country, and traditional home appliance enterprises have opened their own smart home model one after another. Even Samsung, Google and other companies have joined the research tide of smart home. It is of great value to study and construct a convenient, efficient and low-cost smart home system. In this paper, a smart home system based on ARM9 is designed and developed based on embedded linux technology, ZigBee technology and QT technology, which provides a comfortable, convenient and intelligent living environment for users. This paper introduces the background of smart home industry and its development at home and abroad. Then, combining with the actual situation of household appliances and other household devices, it investigates the functional needs of some users for smart home. After analyzing and discussing the possibility of realizing the system, this paper introduces the overall architecture of the intelligent home system, and designs the software and hardware scheme of the system. From a functional point of view, The system can be divided into wireless sensor network subsystem and infrared self-learning remote control subsystem. BOA server and user interaction page are the basis of realizing the function of the two subsystems. Background processors make it possible for users to access smart home systems at any time, anywhere, After the interactive page of the system is verified by the user information, the user can complete the control of the home common equipment and the equipment equipped with the remote control, as well as the acquisition of the house information. In the wireless sensor network subsystem, by studying the ZigBee wireless sensor network protocol and combining the indoor layout, the wireless sensor network suitable for the residential interior is established, and the coordinator node is set up in the network. The router node and the terminal node design the application program of each node according to the data transmission mode between the nodes, in addition, In order to facilitate the data transmission in wireless sensor networks and the identification of transmission data and the extraction of key information between nodes and BOA servers, According to the design idea of data packet in computer network, the data transmission standard of wireless sensor network subsystem is established in this paper. Infrared self-learning remote control subsystem is an infrared self-learning remote controller designed and implemented by using ARM9 technology QT technology and WEBKIT technology. The remote controller cooperates with wireless sensor network subsystem. The remote interaction between the user and most of the devices in the home at present is realized, and the control blind spot is reduced. This paper focuses on the design, compilation, transplant process and remote control method based on WEBKIT of the QT main interface of the infrared self-learning remote controller. The test results show that the infrared self-learning remote controller designed in this paper can not only centrally control but also remotely control each household appliance equipment equipped with remote control through the network. In addition, the infrared self-learning remote controller designed in this paper has the performance. Scalability and applications in smart home systems also have many unique advantages.
【学位授予单位】：太原理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP212.9;TN92;TU855
本文编号：2131666
[Abstract]:As an important application of the Internet of things, smart home is developing rapidly. In recent years, a large number of smart home enterprises have emerged in our country, and traditional home appliance enterprises have opened their own smart home model one after another. Even Samsung, Google and other companies have joined the research tide of smart home. It is of great value to study and construct a convenient, efficient and low-cost smart home system. In this paper, a smart home system based on ARM9 is designed and developed based on embedded linux technology, ZigBee technology and QT technology, which provides a comfortable, convenient and intelligent living environment for users. This paper introduces the background of smart home industry and its development at home and abroad. Then, combining with the actual situation of household appliances and other household devices, it investigates the functional needs of some users for smart home. After analyzing and discussing the possibility of realizing the system, this paper introduces the overall architecture of the intelligent home system, and designs the software and hardware scheme of the system. From a functional point of view, The system can be divided into wireless sensor network subsystem and infrared self-learning remote control subsystem. BOA server and user interaction page are the basis of realizing the function of the two subsystems. Background processors make it possible for users to access smart home systems at any time, anywhere, After the interactive page of the system is verified by the user information, the user can complete the control of the home common equipment and the equipment equipped with the remote control, as well as the acquisition of the house information. In the wireless sensor network subsystem, by studying the ZigBee wireless sensor network protocol and combining the indoor layout, the wireless sensor network suitable for the residential interior is established, and the coordinator node is set up in the network. The router node and the terminal node design the application program of each node according to the data transmission mode between the nodes, in addition, In order to facilitate the data transmission in wireless sensor networks and the identification of transmission data and the extraction of key information between nodes and BOA servers, According to the design idea of data packet in computer network, the data transmission standard of wireless sensor network subsystem is established in this paper. Infrared self-learning remote control subsystem is an infrared self-learning remote controller designed and implemented by using ARM9 technology QT technology and WEBKIT technology. The remote controller cooperates with wireless sensor network subsystem. The remote interaction between the user and most of the devices in the home at present is realized, and the control blind spot is reduced. This paper focuses on the design, compilation, transplant process and remote control method based on WEBKIT of the QT main interface of the infrared self-learning remote controller. The test results show that the infrared self-learning remote controller designed in this paper can not only centrally control but also remotely control each household appliance equipment equipped with remote control through the network. In addition, the infrared self-learning remote controller designed in this paper has the performance. Scalability and applications in smart home systems also have many unique advantages.
【学位授予单位】：太原理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP212.9;TN92;TU855
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