基于Mjpg-streamer的移动视频监控系统设计

为了满足视频监控的需求,设计并实现了一种基于Mjpg-streamer的嵌入式无线网络视频监控系统,以S3C6410作为核心处理器,使用CMOS摄像头OV9650作为视频采集设备,通过无线方式传输经过H.264压缩后的视频数据;重点阐述了在开源视频服务器软件Mjpg-streamer的框架结构下实现视频采集和H.264硬编码过程;最后以Android手机作为视频接收显示终端对系统进行测试,传输视频清晰、流畅,系统稳定、可靠,具有良好的扩展性和易用性。     

基于ATCA架构的加固服务器主模块设计技术

为了解决传统加固服务器主模块可靠性差和稳定性差的问题,提出了一种基于ATCA架构的加固主模块设计方法;该方法包括了基于冗余-48V的高性能服务器处理器供电电路设计技术、基于ECC校验的DDR2高带宽数据存储电路设计技术、基于SATA的高速存储技术等关键技术;经过了大量的测试和试验验证,该种新型的加固服务器主模块能够在恶劣环境下稳定运行,可靠性和稳定性都有了很大的提升。     

基于IIC和云服务器的智能家居控制系统设计

智能家居普遍采用无线通信技术对家居进行互联,不同的通信方法对智能家居系统的稳定性、便捷性、可靠性有很大的影响;针对智能家居的访问方式,通过对比不同的无线通信技术,选择合适的技术运用在智能家居系统的设计中,实现局域网和广域网两种访问方式;在无线传输的智能家居基础上,使用IIC总线进行功能扩展,使用云服务器来替代传统计算机服务器,增加了系统的灵活性和手机访问的快捷性,更好地实现家庭住宅管理与监测,为我们平时的生活提供便利和保护。     

基于云服务器的地磁感应电流监测系统的设计

地磁暴引起的地磁感应电流(GIC) 可能引起变压器直流偏磁, 对电网的安全稳定运行带来威胁, 远程实时监测GIC对电网的GIC防御具有重要的指导意义。设计了一种基于云服务器的电网GIC远程监测系统, 数据采集终端实时采集变压器中性点的GIC, 多监测点数据经GPRS分端口发送至云服务器的内网进行存储, 用户可通过云服务器的公网IP远程访问并对数据进行绘图、下载等处理, 实现了电网GIC数据的实时发布与共享。结合空间天气的预测数据, 还可以初步实现GIC的预警。对系统的数据采集终端以及基于云服务器的监测软件平台两大模块进行了实验室及变电站现场测试, 测试结果表明该系统实现了设计要求, 满足功能需求。     

基于双核的视频智能消防水炮设计

随着大空间公共建筑越来越多,传统的喷洒水灭火已满足不了需求,这些场所的消防安全也显得日益突出。针对现有自动消防炮灭火装置存在大多采用红外传感器作为火源探测元件,易受环境气流影响,导致灭火准确性降低。为此,采用红外视频探测方式,基于双核处理方式实现视频智能消防水炮。着重介绍了视频智能消防水炮工作原理,进行硬件电路结构设计和软件设计,并提出射流分段补偿方法。试验结果表明,所研制的水炮基于视频识别火源跟踪定位和射流分段补偿方法,提高了灭火定位的准确性;基于双核的工作方式,保证了水炮检测火源时效性。该水炮既能满足大空间场所设计要求,同时又能满足国标要求,为大空间场所和野外灭火提供了新的灭火设备选择。     

基于DM642 DSP技术视频图像采集与传输系统设计

视频图像的采集与传输技术一直是信号处理领域研究的热点与难点问题,文章主要以系统的硬件设计和软件设计来对系统进行详细论述,在硬件设计中,通过分析视频图像采集所需要的主要性能指标,确定了系统采用TMS320DM642 DSP芯片,并确定系统的总体设计方法,同时完成了DSP最小系统设计,电源设计以及图像传输模块设计等;在软件设计中,通过对DSP实际控制,从而实现了系统的视频编码余打包等功能,并完成了视频传输的驱动程序设计,最后通过对TMS320DM642 DSP的实时控制,实现视频图像传输与采集功能。     

基于VLC的室内无线视频语音通信系统的设计和实现

提出了一种基于可见光通信技术的新型室内无线视频语音通信系统。本文介绍了相关的系统架构,全双工的实现技术及TCP/IP的组网方案等,并对室内可见光通信中提高系统整体性能的若干关键技术进行了讨论。     

基于线结构光的视频内窥镜测量技术

针对视频内窥镜的测量需求,提出了一种基于线结构激光照射的测量技术。采用线激光作为定标光照射物体表面,建立了线结构光成像模型,标定了不同物距时的放大率和图像中线位置间的比例系数。通过构建测量平台计算了物体的几何参数,实验结果表明测量误差在10%以内,能够满足视频内窥镜观测和测量要求。     

认知无线网络中基于Sigmoid函数的功率控制算法研究

为了实现认知无线网络中频谱分配公平性以及契合现代化绿色通信的需求,根据非合作博弈论和干扰温度,引入信道状态概念,设计出一种新型功率控制算法,分析了该算法的收敛性、纳什均衡解的存在性和唯一性。该算法不仅可以快速收敛,符合实时通信,而且分布式实施,简单实用。仿真结果表明,相比其他算法,该算法系统干扰小,能源消耗低,具有抗干扰性能,而且在日益多用户网络的情况下,具有低功率、低干扰,提高网络的整体效益,更加符合现代化的绿色通信的需求。     

分布式网络化测试系统的中心服务器技术与研究

为了实现测试系统的网络化、开放化和标准化 ,基于传感器振动测试平台远程实物实验系统提出一种具有开放与互联能力的分布式网络化测试系统体系结构 ,并在逻辑上将该体系结构划分为测控中心服务器、测试服务器和标定服务器。中心服务器是分布式网络测试系统的核心逻辑组成单元 ,是系统中事务响应和处理中心。该服务器向上服务于测试用户 ,提供测试请求响应服务 ;向下管理、控制和协调测试服务器与标定服务器进行工作 ,完成具体的测试请求和测试服务。文章给出了中心服务器的组建方案 ,并重点阐述了中心服务器的体系结构、组件应用技术及组件接口 ,同时也对其关键技术进行了介绍。     

基于无线传感器网络的智能LED灯控制系统设计

针对无线传感器网络为基础的控制系统中其板载电池的能量有限,从而影响无线传感器节点的运行寿命问题。本文设计并采取了嵌入式与分布式智能无线传感器网络（WSN）,目的是优化和使控制照明系统更加高效,为了克服这个问题,基于能量感知的通信协议被引入,以减少为了延长其使用时间的无线传感器网络的功耗。本文中的以智能无线传感器网络为基础的LED照明系统,经过实验结果表明,无线传感器节点都能够运行的时间较长,从87天至102天,而增加了约20％的工作寿命。     

Enhancing network lifespan in wireless sensor networks using deep learning based Graph Neural Network

Inadequate energy of sensors is one of the most significant challenges in the development of a reliable wireless sensor network (WSN) that can withstand the demands of growing WSN applications. Implementing a sleep-wake scheduling scheme while assigning data collection and sensing chores to a dominant group of awake sensors while all other nodes are in a sleep state seems to be a potential way for preserving the energy of these sensor nodes. When the starting energy of the nodes changes from one node to another, this issue becomes more difficult to solve. The notion of a dominant set-in graph has been used in a variety of situations. The search for the smallest dominant set in a big graph might be time-consuming. Specifically, we address two issues: first, identifying the smallest possible dominant set, and second, extending the network lifespan by saving the energy of the sensors. To overcome the first problem, we design and develop a deep learning-based Graph Neural Network (DL-GNN). The GNN training method and back-propagation approach were used to train a GNN consisting of three networks such as transition network, bias network, and output network, to determine the minimal dominant set in the created graph. As a second step, we proposed a hybrid fixed-variant search (HFVS) method that considers minimal dominant sets as input and improves overall network lifespan by swapping nodes of minimal dominating sets. We prepared simulated networks with various network configurations and modeled different WSNs as undirected graphs. To get better convergence, the different values of state vector dimensions of the input vectors are investigated. When the state vector dimension is 3 or 4, minimum dominant set is recognized with high accuracy. The paper also presents comparative analyses between the proposed HFVS algorithm and other existing algorithms for extending network lifespan and discusses the trade-offs that exist between them. Lifespan of wireless sensor network, which is based on the dominant set method, is greatly increased by the techniques we have proposed.     

Personal artist recommendation via a listening and trust preference network

Trust information provided by a user unfolds his/her reliable friends with similar tastes. It not only has the potential to help provide better recommendations but also emancipates the recommendation process from heavy computation for seeking friends. In this paper, by taking into account the latent value of trust information, our personal artist recommendation algorithm via a listening and trust preference network (LTPN for short) is presented. We argue that the excellent recommendation should be acquired via the listening and trust preference network instead of the original listening and trust relation information. Experimental results demonstrate LTPN can not only provide better recommendation but also help relieve the cold start problem caused by new users.     

Edge adaptive image resolution enhancement in video sensor network

Video sensor network usually uses fairly low-resolution images due to the limited transmission bandwidth in transmitting images. It is potential to enhance the captured low-resolution images using image resolution enhancement technique that is able to produce a high-resolution image from its low-resolution counterpart. The key challenge of image resolution enhancement is to preserve the edge structure in images. In this paper, a new image resolution enhancement approach is proposed to estimate the intensity of the unknown pixel using a bilateral weighted average of that of its neighboring pixels. More specifically, the neighboring pixels with nearer distance have larger contributions. Furthermore, the neighboring pixels belonging to direction with smaller variation have larger contributions. Experimental results are provided to show that the proposed approach outperforms several conventional edge-directed image interpolation algorithms. Furthermore, the proposed approach yields low computational complexity; it is potential for real-time implementation.     

基于FPGA视频合成系统设计与实现

为实现将输入的六路BT656视频无失真地合并成一路BT1120视频输出,采用将FPGA技术和视频合成系统相结合的设计方法,用verilog语言设计完成有效视频数据的抽取、SRAM乒乓操作以及FPGA对于视频的拼接处理方法。该系统由视频输入解码模块、存储模块、输出解码模块、i2c模块以及时钟管理模块组成。经算法仿真和逻辑综合,该设计可以实现视频合成的基本功能,满足视频监控系统的实时性要求.综合结果表明该设计占用FPGA片上逻辑资源少,系统运行频率高。     

Personalized recommendation via an improved NBI algorithm and user influence model in a Microblog network

Bipartite network based recommendations have attracted extensive attentions in recent years. Differing from traditional object-oriented recommendations, the recommendation in a Microblog network has two crucial differences. One is high authority users or one’s special friends usually play a very active role in tweet-oriented recommendation. The other is that the object in a Microblog network corresponds to a set of tweets on same topic instead of an actual and single entity, e.g. goods or movies in traditional networks. Thus repeat recommendations of the tweets in one’s collected topics are indispensable. Therefore, this paper improves network based inference (NBI) algorithm by original link matrix and link weight on resource allocation processes. This paper finally proposes the Microblog recommendation model based on the factors of improved network based inference and user influence model. Adjusting the weights of these two factors could generate the best recommendation results in algorithm accuracy and recommendation personalization.     

数字、模拟无线混合网络视频节点设计

针对无线多媒体传感器网络广泛的应用前景和目前节点平台稀缺的情况,设计并研制了一种小型化的无线多媒体传感器网络节点。节点采用ADI公司的ADSP-BF561微处理器和Helicomm公司的基于Zigbee网络协议的无线收发模块IP-Link研制而成。在输入通道上可分别支持模拟图像传感器和数字图像传感器。输出通道具有多媒体传输通道和数据/命令传输通道,其中多媒体传输通道用于传输实时的模拟视频,数据/命令传输通道用于传输节点处理之后的有效数据以及接收来自上层网络的命令。