A Survey and Tutorial of EEG-Based Brain Monitoring for Driver State Analysis

The driver’s cognitive and physiological states affect his/her ability to control the vehicle. Thus, these driver states are essential to the safety of automobiles. The design of advanced driver assistance systems (ADAS) or autonomous vehicles will depend on their ability to interact effectively with the driver. A deeper understanding of the driver state is, therefore, paramount. Electroencephalography (EEG) is proven to be one of the most effective methods for driver state monitoring and human error detection. This paper discusses EEG-based driver state detection systems and their corresponding analysis algorithms over the last three decades. First, the commonly used EEG system setup for driver state studies is introduced. Then, the EEG signal preprocessing, feature extraction, and classification algorithms for driver state detection are reviewed. Finally, EEG-based driver state monitoring research is reviewed in-depth, and its future development is discussed. It is concluded that the current EEG-based driver state monitoring algorithms are promising for safety applications. However, many improvements are still required in EEG artifact reduction, real-time processing, and between-subject classification accuracy.      

用于公众交通系统的分布式智能监控系统中的视听信息融合

提出了一个全新的概念,该概念表述了通过融合来自分布式视听处理系统的不同信息来提高事故检测鲁棒性以及提供更多的事件描述.最后利用来自伦敦和巴黎的现场测试验证了该系统的性能.本文是以欧盟的PRISMATICA项目为基础.     

Toward intelligent driver-assistance and safety warning system

A major problem associated with the rapid growth in automotive production is an increase in traffic congestion and accidents, especially in big cities of China. To solve the problem, the government has been increasing funds for improving the traffic infrastructure, enforcing traffic laws, and educating drivers about traffic regulations. In addition, research institutes have launched R&D projects in driver assistance and safety warning systems. In particular, in 1999, the Chinese Academy of Sciences' Intelligent Control and Systems Engineering Center started the Intelligent Vehicle Platforms project. The project aims to promote the use of intelligent technology for safe, efficient, and smart vehicles and to prototype vehicular electronic and sensory products and systems for the Chinese automotive industry. One of the project's key objectives is to develop a vehicular application-specific operating system (vASOS). The National Science Foundation of China and the CAS Knowledge Innovation Program support the project. Supported by the Vehicular Embedded Computing Platform project, the Xi'an Jiaotong University (XJTU-"Jiao Tong" means transportation in Chinese) Institute of Artificial Intelligence and Robotics and the CAS have collaborated to develop intelligent driver-assistance and safety warning systems for passenger vehicles, particularly GPS-and vision-based systems.     

智能校园安防系统的设计与实现

针对目前校园安防中存在的不足,基于智能视频分析和IPSAN存储构架,设计了一种智能校园安防系统。该系统包括前端设备、信号传输和监控室三部分,主要可以实现预警功能、监视功能、录像功能、联网服务功能、周界防范报警联动等功能;文中重点阐述了智能分析子系统中跨线检测、区域入侵检测和异常事件检测功能的实现方法。实际应用表明,该系统运行稳定,功能完整,可应用于高校校园的安全监控等。     

网络信息系统技术安全与防范

信息安全防范是进行全面的安全漏洞检测和分析,依据其结果制定防范措施和解决方案;正确配置防火墙、网络防病毒软件、入侵检测系统、建立安全认证系统等安全系统;完善安全管理规范和机制,切实落实安全管理制度。以增强安全防范意识,确保网络信息系统安全运转。     

土木工程智能健康监测与诊断系统

土木工程智能健康监测与诊断系统由传感元件、信号采集、信号传输与处理、健康诊断与安全评估、结果输出等部分构成。引入智能传感器、信息融合、故障诊断、结构损伤探测理论等对结构健康监测与诊断系统进行探讨 ,最后指出必须解决的关键问题与存在的困难 ,指明其广阔的应用前景     

一种面向物流网监控的物联网技术

目前物流运输配送安全管理主要依靠GPS技术进行管理, 缺乏整体安全管理技术手段. 提出了一种物流物联网监控技术. 该技术实现了物联网传感器系统、视频监控系统、单兵可视通话指挥系统、司乘人员终端、通讯系统等技术的综合应用. 通过实际项目应用, 验证了该技术可以广泛应用于实现保障运输安全、提高运输效率、管理运输绩效、处理应急情况等.     

Sharing Context-Aware Road and Safety Information

We present an integrated vehicular system for the collection, management, and provision of context-aware information on traffic and driver location. This system uses an integrated vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication paradigm enriched with an information management system. The infrastructure manages vehicle-detected safety hazards and other relevant information, adapting them to the vehicle's context and driver's preferences. This vehicular integrated system resembles the concept of a smart road.     

开放网络环境下客户端的安全

开放网络环境下进行信息传输时,用户在客户端面临很大的安全风险,因为客户程序的真实性得不到保障。目前使用的绝大部分系统中,用户不得不信任所在的客户节点。可采取的办法之一是采用智能卡,而且理想的情况下,智能卡拥有足够的计算能力和附加的输入输出设备,提供全部的密码处理以及必要的输入输出,但由于目前的工艺水平,,智能卡只能提供有限的计算资源。文中针对客户端的安全问题,对于基于对称密销密码体制的身份监别系统,给出了一个合理的增强客户安全的方法。该方法采用一个预先鉴别交换协议,在客户程序和KDC之间达成共享密钥,而不暴露用户的密钥,并保证对后继身分鉴别的透明性。文中还给出了协议的分析,对完全解决客户端的安全也进行了探讨。     

基于腕部可穿戴设备的跌倒监护系统设计与实现

随着社会老龄化加快,老年人或病人的人工监护成本越来越高,针对目前各种跌倒监测装置的不足,设计了一款基于腕部智能穿戴设备的生理体征采集、跌倒监测和报警系统,该装置通过集成的各种传感器采集腕部高度、加速度、角速度等体征信号,并采用合适的算法实现了跌倒检测报警功能。实验结果表明,通过佩戴本文设计的腕部智能穿戴设备可以较好地实现对跌倒行为和日常非跌倒行为的区分,在不影响佩戴者舒适度情况下行为检出率可达到98.5%。     

网络安全检测框架与方法研究

网络和信息系统已经成为关键基础设施乃至整个经济社会的核心,一旦遭受攻击破坏、发生重大安全事件,将严重危害国家经济安全和公共利益。如何检测网络攻击行为,保障网络基础设施的安全,是保障核心技术装备安全可控,构建国家网络安全保障体系的核心环节。系统地介绍了针对入侵检测框架、特征自动生成、安全检测理论及方法、网络拓扑监控与网络路由控制等问题已取得的若干创新成果,梳理出网络安全检测算法和框架、无线网络安全检测、网络监控和安全增强等若干科学发现,最后总结了网络安全检测与控制技术发展趋势。     

统一密钥支撑体系的研究

随着企业互动化、移动化和智能化业务的逐步推进,密码技术作为业务信息安全保护的核心内容越来越重要,但由于业务系统所采用的密码算法及应用模式的不同,通常企业存在多种多样的密钥管理系统,导致密钥资源无法有效快速利用,缺少统一的密钥监控和保护措施。文中介绍的统一密钥支撑体系以密钥管理PDCA为模型,从密钥管理体系及标准,密钥监控与分析系统和密钥安全性检测平台出发构建层次化的体系架构,规范业务系统密码技术的使用方式和流程,完善密钥全生命周期安全管控措施,建立业务系统标准化、通用和统一的密钥检测和评价体系,消除密码应用的安全隐患,保障密钥的安全、可靠以及高效使用,提升企业密钥管理水平。     

Applying evolutionary methods for early prediction of sleep onset

Driving safety can be achieved by predicting imminent falling asleep at the wheel. Several methods of early detection have been investigated by continuous monitoring of physiological and behavioral parameters. Requirements for noninvasive, unattended, personal adaptation need to be met, along with the effectiveness of the detection method, in order to perform reliably when applied. Because wakefulness and sleep are reflected in several human physiological conditions, such as cardiac activity, breathing, movement, and galvanic skin conductance, captured bioelectric signal features were extracted. A fuzzy decision-fusion logic was tuned to make inferences about oncoming driver fatigue and drowsiness. The evolving fuzzy neural network paradigm was applied to the previous developed framework to improve reliability while keeping target system complexity low.     

基于文件系统过滤驱动的安全增强型加密系统技术研究

应用层加密系统在实际的应用中一般要求用户在访问文件前手动进行加解密操作,有些系统中文件正常使用时必须以明文形式存储在磁盘上.基于文件系统驱动的加密文件系统减少了用户的参与操作,同时保证了磁盘上文件处于加密状态,但是其在设计与实现上较为复杂.针对上述方法存在的问题,本文采用Windows NT内核操作系统的驱动框架,基于文件系统过滤驱动技术实现对数据进行透明加解密.通过这种方法不仅解决了应用层加密系统存在的不足,与加密文件系统相比开发实现较简单灵活.另外使用智能卡作为加解密密钥的存储容器,进一步增强整个系统的安全性.     

基于热释电红外的安防系统设计

当今社会，在没有安保措施的家庭、小商铺和中小型商场，不时有报道称发生人室盗窃案，给人们带来巨大的经济损失。本文将介绍一种通过热释电红外传感器实时监测，在发生异常时发出报警信号并封锁出口的安防系统，有效的保护人们的财产安全。同时，系统还可以动态统计并显示场馆内人员数量，实现对场馆内容量的控制，广泛应用于公益性博物馆、图书馆、体育馆等场所。     

A method of NC machine tools intelligent monitoring system in smart factories

The construction of effectual connection to bridge the gap between physical machine tools and upper software applications is one of the inherent requirements for smart factories. The difficulties in this issue lies in the lack of effective and appropriate means for real-time data acquisition, storage and processing in monitoring and the post workflows. The rapid advancements in Internet of things (IoT) and information technology have made it possible for the realization of this scheme, which have become an important module of the concepts such as “Industry 4.0”, etc. In this paper, a framework of bi-directional data and control flows between various machine tools and upper-level software system is proposed, within which several key stumbling blocks are presented, and corresponding solutions are subsequently deeply investigated and analyzed. Through monitoring manufacturing big data, potential essential information are extracted, providing useful guides for practical production and enterprise decision-making. Based on the integrated model, an NC machine tool intelligent monitoring and data processing system in smart factories is developed. Typical machine tools, such as Siemens series, are the main objects for investigation. The system validates the concept and performs well in the complex manufacturing environment, which will be a beneficial attempt and gain its value in smart factories.     

针对机场行李传送监控视频的侵入者检测

随着智能监控技术的快速发展,越来越多的公共场合监控系统由人力监控向计算机辅助监控转化。机场传送仓作为机场中的重点安全区域,对其进行侵入者的实时检测是十分必要的。人体检测是视觉分析领域的重要组成部分,其在视频监控领域当中有着广泛的应用。针对机场行李传送监控视频,提出了一种用于区分人体与常规行李的视觉特征,并且利用该特征实现了一个实时的智能视频监控系统,用于检测传送仓中的侵入者。实验结果表明,该系统降低了人力资源的消耗,且有效地降低了侵入者的漏报率,从而提高监控质量。     

A smartphone based technique to monitor driving behavior using DTW and crowdsensing

Safety issues while driving in smart cities are considered to be top-notch priority in contrast to traveling. Today’s fast paced society, often leads to accidents. In order to reduce the road accidents, one key area of research is monitoring the driving behavior of drivers. Understanding the driver behavior is an essential component in Intelligent Driver Assistance Systems. One of potential cause of traffic fatalities is aggressive driving behavior. However, drivers are not fully aware of their aggressive actions. So, in order to increase awareness and to promote driver safety, a novel system has been proposed. In this work, we focus on DTW based event detection technique, which have not been researched in motion sensors based time series data to a great extent. Our motivation is to improve the classification accuracy to detect sudden braking and aggressive driving behaviors using sensory data collected from smartphone. A very significant feature of DTW is to be able to automatically cope with time deformations and different speeds associated with time-dependent data which makes it suitable for our chosen application where data might get affected due to factors such as: high variability in road and vehicle conditions, heterogeneous smartphone sensors, etc. Our technique is novel as it uses fusion of sensors to enhance detection accuracy. The experimental results show that proposed algorithm outperforms the existing machine learning and threshold-based techniques with 100% detection rate of braking events and 97% & 86.67% detection rate of normal left & right turns and aggressive left & right turns respectively.     

A flexible communications protocol for a distributed surveillance system

On-line surveillance for safety and security is a major requirement of public transport and other public places to address the modern demands of mobility in major urban areas and to effect improvements in quality of life and environment protection. The surveillance task is a complex one involving technology, management procedures and people. Visual surveillance based on Closed Circuit Television system is an important part of such systems, but visual processing is not sufficient and the geographical distribution of devices and management has to be taken into account. In this paper we present a surveillance architecture that reflects the distributed nature of the monitoring task and allows for distributed detection processes, not only dealing with visual processing but also with devices such as acoustic signature detection and mobile smart cards, actuators and a range of other possible sensors. The design uses ideas from control engineering and distributed communications networks resulting in a communications architecture based on CORBA and XML messaging. We have shown how to define a generic device/sensor model appropriate for the surveillance task and sufficiently flexible so as to allow for scalability, expansion and customisation of a practical surveillance task. The paper gives sufficient details on the protocols to show how intelligent detection modules can be integrated as part of this kind of system. The system components have been implemented and integrated in two major successful trials in metropolitan railway stations in London and in Paris, as part of a major EU-funded project (PRISMATICA).     

基于语音识别的安全认证系统

文章在对智能终端安全性需求进行分析的基础上,将语音识别与沙盒防护技术应用于智能终端。使用者是否获得授权的验证是文章分析的一个重点问题。通过选择在广泛使用的Android系统上设计实现了一个基于语音识别的安全认证系统,从使用者声音的识别、沙盒防护的交互接口和交互协议等几个方面对系统构建的关键技术进行了详细分析。