智能手机监控中能低码率应用

3G网络和智能手机的迅速发展和普及,为智能手机监控应用部署和使用高清摄像机提供了基础。通过对3G网络实际带宽的分析,可以知道码率低于512kbps的高清摄像机具备实用性。本文将探讨智能手机、摄像机和3G网络在智能手机监控中所起的作用、目前的状况以及在智能手机监控中实现高清视频的可能性。     

基于Android平台的嵌入式视频监控系统设计

对现有的视频监控设备进行了调查和研究,提出一种基于Android平台的嵌入式视频监控系统.该系统主要由基于S3C2440芯片的开发板和Android智能手机两部分组成.目标板用于视频的采集和压缩编码,并将生成MPEG-4视频流发送到Helix Server流媒体服务器.Android智能手机作为监控端的视频监控界面,以3G的方式进行登录,并通过Android智能手机自带的浏览器播放视频数据.通过Android智能手机浏览器观看到的视频达到正常监控的标准.     

短视频侵权行为的性质、分类及司法规制

0引言 近年来,随着智能手机、数据网络以及Wi-Fi的大规模普及,秒拍、美拍等视频平台开始出现,短视频作为一种新兴业务出现在用户面前.自2018年至今,短视频市场格局经过阶段性的发展趋于稳定,逐渐形成以抖音、快手为主要代表的短视频两极格局,短视频用户规模达八亿多,占互联网手机用户的九成,整个行业正处于蓬勃的高速发展期....     

助力网络监控，监控管理平台需求急剧升温

随着监控技术向网络化、集成化方向发展,为了满足客户在大型联网监控系统中对视频资源．用户权限以及网络性能的管理要求,视频监控管理平台应运而生,并发展为网络监控系统的核心部分。     

手机位置信息的保护和利用

高速发展的智能手机和无线网络将互联网推向了移动互联网的世界,众多手机操作系统和应用软件开发公司为了获取更多的资源,肆无忌惮地对手机用户的位置信息进行收集,广大用户如何对手机位置信息进行保护,以及如何利用好这些位置信息,本文中将进行探讨。     

快速制作九宫格截图

我们在将视频推荐给网友时,常常会将视频截图发送给他人,不过单张的截图显然不能说明什么问题,上传多张图片又显得比较麻烦。现在我们就可以使用GOM Player软件将多张视频截图合成为一张图片。     

车载主机与智能手机互动系统设计

通过无线和有线结合的方式将智能手机与车载主机连接起来,智能手机的音频/视频通过 MHL 或者HDMI接口输出,经过转换后传输到车载主机,车载主机显示手机屏幕和播放多媒体声音。车载主机后台运行一个监控鼠标事件的服务器程序,捕获用户在车载主机屏幕上的触摸事件和坐标,并经过蓝牙或 WiFi 发送给手机客户端,客户端模拟对应的鼠标事件,实现用户在车载主机屏幕操作手机的应用程序,运行手机上的应用程序,实现车载主机与智能手机的互动。     

3G移动互联网客户服务平台架构设计

随着各种智能手机的普及使用,传统的电话呼叫中心结合分布众多的营业厅模式已经无法满足3G移动手机用户多样化的服务需求。3G移动互联网客户服务平台将建立一个基于3G移动互联网的客户服务体系,通过3G移动互联网的方式向用户提供贴心服务,以文字、图片、演示视频、对讲、在线视频等服务方式远程指导、解答、协助解决用户在使用产品过程中遇到的实际困难和问题。     

移动终端数据泄露动态监控系统

随着手机应用的普及,智能手机的隐私泄露问题日益严重。文章基于Andriod平台,对涉及用户数据安全的敏感权限、流量等进行了分析,设计了一款数据泄露动态监控系统,实现对敏感权限和数据流量的监控,利用数学建模的方法对监控结果进行行为分析,计算出当前时刻各应用程序的危险系数。最后将系统监控结果以数据可视化的形式反馈给用户,实现对用户透明的隐私数据保护。     

互联网热点视频分析方法研究

随着互联网的不断发展,互联网视频从最初的出现到当前的主要应用使一个漫长的过程.而互联网视频具有丰富的资源,使用互联网观看视频的网络用户十分庞大,并且互联网视频的分布和更新也十分的快速.本文主要从互联网视频的主要特点出发,分析互联网热点视频分析、互联网热点视频采集以及互联网热点视频跟踪这些内容,并对于系统设计也展开了一些探究.以下分别进行详细的分析.     

基于单片机控制的智能家庭防盗报警系统的设计

本文设计了一种基于DTMF技术的单片机进行远程控制的智能家庭防盗报警器,该系统能利用现有的公共电话网络随时实现异地监控家中的情况,并且家中发生危险情况时能及时将信息传递给主人,具有方便、安全的优点。     

IntelliHome: An internet of things-based system for electrical energy saving in smart home environment

Despite there has been an increasing energy price due to factors such as supply, demand, government regulation, among others, users do not like to spend their time to analyze their power consumption and establish actions to save money. Hence, there is a need for smart solutions that help users to save energy at home in an easy way. The smart home concept is attracting the attention of both academia and industry to address this need. Nowadays, high volumes of data are available in the smart home context, facilitated by the growth of internet of things (IoT)-based devices and advanced sensing infrastructure. Therefore, it is necessary to automatically extract useful knowledge from this information to cost-effective use of energy at home. In this sense, this work presents IntelliHome, a smart-home system that aims to reduce electrical energy consumption at home. To this end, IntelliHome uses big data analytics technologies and Machine Learning and statistical techniques to provide users with a meaningful perspective of their electricity consumption habits aiming to actively involve them in the energy-saving process through real-time information and energy-saving recommendations. This work also discusses a case study and an evaluation aligned with the objectives of this work. The obtained results verify the effectiveness of the proposed system regarding electrical energy saving.     

Smart homes and their users: a systematic analysis and key challenges

Published research on smart homes and their users is growing exponentially, yet a clear understanding of who these users are and how they might use smart home technologies is missing from a field being overwhelmingly pushed by technology developers. Through a systematic analysis of peer-reviewed literature on smart homes and their users, this paper takes stock of the dominant research themes and the linkages and disconnects between them. Key findings within each of nine themes are analysed, grouped into three: (1) views of the smart home—functional, instrumental, socio-technical; (2) users and the use of the smart home—prospective users, interactions and decisions, using technologies in the home; and (3) challenges for realising the smart home—hardware and software, design, domestication. These themes are integrated into an organising framework for future research that identifies the presence or absence of cross-cutting relationships between different understandings of smart homes and their users. The usefulness of the organising framework is illustrated in relation to two major concerns—privacy and control—that have been narrowly interpreted to date, precluding deeper insights and potential solutions. Future research on smart homes and their users can benefit by exploring and developing cross-cutting relationships between the research themes identified.     

基于ARM的视频数据采集传输系统的设计与实现

对基于ARM的视频数据采集传输系统进行研究及设计,通过ARM新一代嵌入式开发平台,与现在流行的互联网及无线传输技术相结合,实现视频数据的采集和远程数据的传输。设计中采用嵌入式Linux系统通过USB摄像头进行视频数据的采集,解决图像的格式转换和MJPEG编码压缩的数据处理,以及通过软件的设计实现MJPEG格式文件到流媒体输出等问题,最终实现视频数据采集和传输。本系统有以下几个方面的应用:家庭环境的实时监测、家居的智能化控制、高危车间厂房无线监控与控制、中长距离的家庭视频通讯、企业实时视频监控等。     

Automating smart Internet of Things devices in modern homes using context-based fuzzy logic

Internet of Things (IoT) is mainly used to connect different embedded objects over the internet to make communication between them possible. With the help of IoT, devices find a way to interact, work together, and study from each other's experiences just like humans do. IoT finds its way in applications such as smart home, smart city, healthcare, agriculture, and so on. The name smart home arises due to the automation of the normal home appliances to make it smart. When the devices of the normal smart home are connected via the internet, they become a part of the IoT. The smart home should ensure the following characteristics such as security, comfort, convenience, and energy saving. The article presents a technique for IoT controlled devices in a smart home using context-based fuzzy logic. Fuzzy logic is mainly used to monitor and analyze the real-time data collected from the sensors in the smart homes from various environments. Context-based fuzzy logic uses a multivalued logic principle which differs from the normal Boolean logic, where the truth value lies between only zero and one (ie, true or false). The proposed smart home is implemented in a real case scenario where it yields an accuracy of 90.5%, response time of 6.41 milliseconds, and an F-measure of 97%.     

基于无线的物联智能家居控制系统设计

提出一种基于无线的物联智能家居控制系统设计,该系统通过PXA270和nRF24L01模块实现无线采集、发送各项家居信息;通过GSM通信将烟雾、煤气、红外等传感器的异常报警信息以短信方式通知用户,并连接PXA270的PC实现实时远程监控。经过测试,该系统工作稳定,便于实际应用,市场前景广阔。     

智能家居中语义知识表达及推理研究

针对地源热泵智能家居“以用户为中心”的需求,文中将语义技术和X列表引入智能家居领域,并建立包括用户、环境变量、需求任务、设备资源和服务5大本体要素列表的语义智能家居模型。在语义推理方面,提出并构建了基于jena的跨列表交互规则,使智能家居各列表互相联系,智能家居本体知识库、规则库和jena推理机进行封装并按需组合推理,可为用户提供个性化服务,实现智能家居的语义人工智能化。文中最后进行了智能家居系统开发,并列举典型应用场景说明了语义智能家居系统的可行性。     

Learning Situation Models in a Smart Home

This paper addresses the problem of learning situation models for providing context-aware services. Context for modeling human behavior in a smart environment is represented by a situation model describing environment, users, and their activities. A framework for acquiring and evolving different layers of a situation model in a smart environment is proposed. Different learning methods are presented as part of this framework: role detection per entity, unsupervised extraction of situations from multimodal data, supervised learning of situation representations, and evolution of a predefined situation model with feedback. The situation model serves as frame and support for the different methods, permitting to stay in an intuitive declarative framework. The proposed methods have been integrated into a whole system for smart home environment. The implementation is detailed, and two evaluations are conducted in the smart home environment. The obtained results validate the proposed approach.     

基于HOG+SVM的智能家居入侵检测系统设计

当前,大多数的智能家居视频监控系统仅仅完成简单的视频图像传输功能,不太智能;或是保持 PC常开,将视频图像数据传输到PC端进行相应的检测和识别,增加消耗.为解决该问题,系统以嵌入式技术为载体,利用 Cortex-A9处理器芯片搭载 Linux操作系统,结合机器视觉图像处理技术,融入 HOG+SVM机器学习方法来对视频中是否有外人入侵进行检测,并可通过 GPRS模块进行短信报警通知.同时可通过智能终端,登录指定网页或者相应的客户端进行实时查看和取证.实验结果表明,该系统数据传输稳定、算法准确度较高,可替代传统的智能家居视频监控系统.     

基于嵌入式Internet/Intranet的智能家居系统模型及实现

讨论了智能家居系统的发展方向、设计准则和系统的总体结构框架、设计思想和实现步骤;实现了带有多种家庭终端接口的嵌入式家庭网关,在此基础上构造了运行在Internet/Intranet上的智能家居系统模型;系统由智能家居控制平台、小区服务管理平台及宽带互联网3部分组成,支持Web和Wap两种接入方式,具有低成本、高适应性、高稳定性、易操作性等优点,提高了智能家居系统的自动化和智能化水平;最后分析了原型系统的功能与技术特点.