Centralized server application for air transportation security systems

BackgroundHealthcare worker hand hygiene is thought to be one of the most important strategies to prevent healthcare-associated infections, but compliance is generally poor. Hand hygiene improvement interventions must include audits of compliance (almost always with feedback), which are most often done by direct observation - a method that is expensive, subjective, and prone to bias. New technologies, including electronic and video hand hygiene monitoring systems, have the potential to provide continuous and objective monitoring of hand hygiene, regular feedback, and for some systems, real-time reminders. We propose a systematic review of the evidence supporting the effectiveness of these systems. The primary objective is to determine whether hand hygiene monitoring systems yield sustainable improvements in hand hygiene compliance when compared to usual care.Methods/DesignMEDLINE, EMBASE, CINAHL, and other relevant databases will be searched for randomized control studies and quasi-experimental studies evaluating a video or electronic hand hygiene monitoring system. A standard data collection form will be used to abstract relevant information from included studies. Bias will be assessed using the Cochrane Effective Practice and Organization of Care Group Risk of Bias Assessment Tool. Studies will be reviewed independently by two reviewers, with disputes resolved by a third reviewer. The primary outcome is directly observed hand hygiene compliance. Secondary outcomes include healthcare-associated infection incidence and improvements in hand hygiene compliance as measured by alternative metrics. Results will be qualitatively summarized with comparisons made between study quality, the measured outcome, and study-specific factors that may be expected to affect outcome (for example, study duration, frequency of feedback, use of real-time reminders). Meta-analysis will be performed if there is more than one study of similar systems with comparable outcome definitions.DiscussionElectronic and video monitoring systems have the potential to improve hand hygiene compliance and prevent healthcare-associated infection, but are expensive, difficult to install and maintain, and may not be accepted by all healthcare workers. This review will assess the current evidence of effectiveness of these systems before their widespread adoption.Study registrationPROSPERO registration number: CRD42013004519

The performance evaluation of database servers in N-tier applications is a serious challenge due to requirements such as non-stationary complex workloads and global consistency management when replicating database servers. We conducted an experimental evaluation of database server scalability and bottleneck identification in N-tier applications using the RUBBoS benchmark. Our experiments are comprised of a full scale-out mesh with up to nine database servers and three application servers. Additionally, the fourtier system was run in a variety of configurations, including two database management systems (MySQL and PostgreSQL), two hardware node types (normal and low-cost), and two database replication techniques (C-JDBC and MySQL Cluster). In this paper we present the analysis of results generated with a read-intensive interaction pattern (browse-only workload) in the client emulator. These empirical data can be divided into two kinds. First, for a relatively small number of servers, we find simple hardware resource bottlenecks. Consequently, system throughput increases with an increasing number of database (and application) servers. Second, when sufficient hardware resources are available, non-obvious database related bottlenecks have been found that limit system throughput. While the first kind of bottlenecks shows that there are similarities between database and application/web server scalability, the second kind of bottlenecks shows that database servers have significantly higher sophistication and complexity that require in-depth evaluation and analysis.

Video surveillance technology plays an important role in the security field, with its intuitive, convenient and abundant information and is widely used in city traffic, civil security and other various fields especially in the important safety departments or major events. In this paper, according to the video surveillance system features and functional requirements, we use embedded system ,OMAP4460 and Android operating system on the basis of the panoramic technology to realize vertical 180 degrees horizontal 360-degree panoramic video surveillance. In the paper we profoundly analyze and discuss the embedded panoramic video surveillance system mainly from the hardware platform structures, the design of the peripheral circuit and the panorama function implement. DOI: http://dx.doi.org/10.11591/telkomnika.v11i1.1874

More than 80% of video surveillance systems are used for monitoring people. Old human detection algorithms, based on background and foreground modelling, could not even deal with a group of people, to say nothing of a crowd. Recent robust and highly effective pedestrian detection algorithms are a new milestone of video surveillance systems. Based on modern approaches in deep learning, these algorithms produce very discriminative features that can be used for getting robust inference in real visual scenes. They deal with such tasks as distinguishing different persons in a group, overcome problem with sufficient enclosures of human bodies by the foreground, detect various poses of people. In our work we use a new approach which enables to combine detection and classification tasks into one challenge using convolution neural networks. As a start point we choose YOLO CNN, whose authors propose a very efficient way of combining mentioned above tasks by learning a single neural network. This approach showed competitive results with state-of-the-art models such as FAST R-CNN, significantly overcoming them in speed, which allows us to apply it in real time video surveillance and other video monitoring systems. Despite all advantages it suffers from some known drawbacks, related to the fully-connected layers that obstruct applying the CNN to images with different resolution. Also it limits the ability to distinguish small close human figures in groups which is crucial for our tasks since we work with rather low quality images which often include dense small groups of people. In this work we gradually change network architecture to overcome mentioned above problems, train it on a complex pedestrian dataset and finally get the CNN detecting small pedestrians in real scenes.

Video Surveillance has become area of research and development due to increase in terrorist activities, thefts and other activities that can cause harm to human property and lives. Due to this researchers have been trying to add more and more intelligence in the video monitoring systems, so that it could automatically detect the malicious activities in the area under surveillance and raise alarm. The goal of visual surveillance is not only to put cameras in place of human eyes, but also to accomplish the entire surveillance task as automatically as possible. We can say that video surveillance is nothing but taking the video, identifying unwanted entities, tracking their actions, understanding their actions and raising an alarm. In this paper, we will be study the phases of the video surveillance system. We will study how a video is divided into frames, those frames are then sent to detect any change detection (human detection), further this information about detected humans in one frame is correlated with the information of the other frame and thus the detected human is tracked in the subsequent frame and this is called human tracking. We will see most salient region method for tracking and in this paper we propose a method of handling occlusion using velocity and direction information.

In intelligent traffic system, we not only need to get the corresponding traffic condition by image processing, but also need to illustrate the information and vehicles changes detected through the characters and graphics changes, thus to get traffic information visualization. A video monitoring and control system are designed in this paper based on DSP and FPGA. The system can realize the real-time traffic video data acquisition, DSP processors complete traffic information parameters extraction, FPGA complete the video overlap of traffic information parameters. This method realize the Dynamic video monitoring and controlling, is well applied in the intelligent traffic system.

To understand staff acceptance of a remote video monitoring system for operating room (OR) coordination. Improved real-time remote visual access to OR may enhance situational awareness but also raises privacy concerns for patients and staff. Survey. A system was implemented in a six-room surgical suite to display OR monitoring video at an access restricted control desk area. Image quality was manipulated to improve staff acceptance. Two months after installation, interviews and a survey were conducted on staff acceptance of video monitoring. About half of all OR personnel responded (n = 63). Overall levels of concerns were low, with 53% rated no concerns and 42% little concern. Top two reported uses of the video were to see if cases are finished and to see if a room is ready. Viewing the video monitoring system as useful did not reduce levels of concern. Staff in supervisory positions perceived less concern about the system's impact on privacy than did those supervised (p < 0.03). Concerns for patient privacy correlated with concerns for staff privacy and performance monitoring. Technical means such as manipulating image quality helped staff acceptance. Manipulation of image quality resulted overall acceptance of monitoring video, with residual levels of concerns. OR nurses may express staff privacy concern in the form of concerns over patient privacy. This study provided suggestions for technological and implementation strategies of video monitoring for coordination use in OR. Deployment of communication technology and integration of clinical information will likely raise concerns over staff privacy and performance monitoring. The potential gain of increased information access may be offset by negative impact of a sense of loss of autonomy.

The paper uses the control technology of computer big data and PLC, fieldbus communication technology and video monitoring technology to research, design and develop the monitoring system of the coal preparation plant’s production process. In this plan, the coal preparation plant’s video monitoring system, production centralized control system and other production support systems are fully integrated through network technology, to achieve the purpose of improving its safety guarantee function. The system improves the level of visual management, realizes unattended operation, and reduces potential safety hazards.

Network video surveillance has been a popular security application for many years. Target tracking in a cluttered environment remains one of the challenging problems of video surveillance. The task of target tracking is a key component of video surveillance and monitoring systems. It provides input to high-level processing such as recognition, access control or re-identification or is used to initialize the analysis and classification of human activities. Intelligent and automated security surveillance systems have become an active research area in recent time due to an increasing demand for such systems in public areas such as airports, underground stations and mass events. In this context, tracking of stationary foreground regions is one of the most critical requirements for surveillance systems based on the tracking of abandoned or stolen objects or parked vehicles. Object tracking based techniques are the most popular choice to detect stationary foreground objects because they work reasonably well when the camera is stationary and the change in ambient lighting is gradual, and they also represent the most popular choice to separate foreground objects from the current frame. In this paper, we did the literature survey on different technique and finally carried out our methodology for the same situation.

The Portuguese coastline, like many other worldwide coastlines, is often submitted to several types of extreme events resulting in erosion, thus, acquisition of high quality field measurements has become a common concern. The nearshore survey systems have been traditionally based on in situ measurements or in the use of satellite or aircraft mounted remote sensing systems. As an alternative, video-monitoring systems proved to be an economic and efficient way to collect useful and continuous data, and to document extreme events. In this context, is under development the project MoZCo (Advanced Methodologies and Techniques Development for Coastal Zone Monitoring), which intends to develop and implement monitoring techniques for the coastal zone based on a low cost video monitoring system. The pilot study area is Ofir beach (north of Portugal), a critical coastal area. In the beginning of this project (2010) a monitoring video station was developed, collecting snapshots and 10 minutes videos every hour. In order to process the data, several video image processing algorithms were implemented in Matlab®, allowing achieve the main video-monitoring system products, such as, the shoreline detection. An algorithm based on image processing techniques was developed, using the HSV color space, the idea is to select a study and a sample area, containing pixels associated with dry and wet regions, over which a thresholding and some morphological operators are applied. After comparing the results with manual digitalization, promising results were achieved despite the method’s simplicity, which is in continuous development in order to optimize the results.

Functional assessments of a person’s ability to perform activities of daily living (ADL) currently involves clinical rating scales. These scales are limited in providing objective and sensitive information. Aim To develop an automated tool for objective and quantitative assessment of functional ability in Alzheimer disease (AD). Methods 16 Patients with mild to moderate AD (age=76.7±4.0, MMSE=20,7±2.0) and 10 age and gender matched healthy controls (HC; age=73.9±4.5, MMSE=28.1±1.3) were evaluated clinically, cognitively, and functionally. Subsequently, each subject was asked to perform a set of daily tasks while monitored by two video cameras. A measure of functional impairment was then computed from quantitative and qualitative parameters collected from video recordings that were first annotated by two clinicians (blind to each other results and the participants’ clinical state). Results The VMS (Video monitoring system) function index (derived from a ratio of efficacy in ADLs) correlated strongly with cognitive results (MMSE, Rho=0.81) as well as with IADL-E scores (Rho=-0.65). Conclusion This study is a successful proof of concept for a novel assessment tool in dementia. The derived VMS function-index may provide a pragmatic, objective and continuous measure of cognitive and functional ability for clinical assessments as well as having a role as an outcome measure in clinical trials. Future research should complete the automation of the method.

This paper presents a Video Monitoring System, which aims to achieve behavior analysis of elderly people. Real-time tracking and posture discrimination enable to detect emergency situation (by trigging an alarm in case of fall detection for example) and to analyze long term activity which enforces medical follow-up. These are key-issues to improve healthcare quality for rural population. Monitoring human activity in a home environment is a challenging task in computer vision. A multi-camera system is proposed to address the complexity of home environment. Person silhouette is extracted thanks to a robust background/foreground segmentation process. A multi-view particle filter is built to track the silhouette in the scene and discriminate the person posture. This posture is used to interpret basic activities and detect falls. A finer gesture reconstruction is finally exposed which will offer a more accurate activity determination and gait analysis for future system.

Traffic monitoring and parameters estimation from urban to non urban (battlefield environment) traffic is fast-emerging field based on acoustic signals. We present here a comprehensive review of the state-of-the-art acoustic signal for vehicular speed estimation, density estimation and classification, critical analysis and an outlook to future research directions. This field is of increasing relevance for intelligent transport systems (ITSs). In recent years video monitoring and surveillance systems has been widely used in traffic management and hence traffic parameters can be achieved using such systems, but installation, operational and maintenance cost associated with these approaches are relatively high compared to the use of acoustic signal which is having very low installation and maintenance cost. The classification process includes sensing unit, class definition, feature extraction, classifier application and system evaluation. The acoustic classification system is part of a multi sensor real time environment for traffic surveillance and monitoring. Classification accuracy achieved by various studied algorithms shows very good performance for the 'Heavy Weight' class of vehicles as compared to the other category Light Weight. Also a slight performance degrades as vehicle speed increases. Vehicular speed estimation corresponds to average speed and traffic density measurement, and can be substantially used for traffic signal timings optimization.

In this paper we describe a software infrastructure that unifies replication and transaction processing in three-tier architectures and, thus, provides high availability and fault tolerance for enterprise applications. The infrastructure is based on the Fault Tolerant CORBA and CORBA Object Transaction Service standards, and works with commercial-off-the-shelf application servers and database systems. The infrastructure replicates the application servers to protect the business logic processing. In addition, it replicates the transaction coordinator which renders the two-phase commit protocol non-blocking and, thus, avoids potentially long service disruptions caused by coordinator failure. The infrastructure handles the interactions between the application servers and the database servers through replicated gateways that prevent duplicate requests from reaching the database servers. The infrastructure implements client-side automatic failover mechanisms, which guarantees that clients know the outcome of the requests that they have made. The infrastructure starts the transactions at the application servers, and retries aborted transactions, caused by process or communication failures, automatically on the behalf of the clients.

With the rapid development of information technology, video monitoring system has become an important part of modern city security system. Especially in prisons, surveillance cameras are almost everywhere. The concept of guided wave spread spectrum digital data communication in intelligent structure is proposed. However, with the continuous expansion of the monitoring network, surveillance cameras not only bring convenience, but also produce a lot of monitoring data, which brings great challenges to storage, analysis and retrieval. China is a big animal husbandry country. The development of animal husbandry directly affects the development of national economy. It is necessary to develop a new animal husbandry monitoring system based on Internet of things technology, which can detect the temperature, humidity, carbon dioxide and other information parameters in the process of animal growth. In order to monitor the growth quickly and accurately and realize the automation and intelligent control, an intelligent real-time monitoring system based on single chip microcomputer is designed. Animal husbandry monitoring system completes the planning and management of animal growth mode by collecting, monitoring and timely alarming the information of animal growth environment.KeywordsIntelligent monitoring systemLamb growthPregnant ewe feedingEnvironmental monitoring