Traditional Video Monitoring System Research Articles

A Cross-Platform Web3D Monitoring System of the Three-Machine Equipment in a Fully Mechanized Coalface Based on the Skeleton Model and Sensor Data

A fully mechanized coalface is a rugged environment that has poor visibility. The traditional video monitoring system has problems such as a lack of realism, a blurry monitoring effect, and poor reliability. It is an important task to monitor the operations of the three-machine equipment (we will refer to the shearer, hydraulic support, and scraper conveyor as the three-machine equipment) intuitively, accurately, and timely and ensure that it is operating safely. This study proposed a cross-platform Web3D monitoring system for the three-machine equipment. First, the virtual mesh model and skeleton model that was embedded in the mesh model were established according to three-machine ontology and basic motion units. Second, the kinematic model of the three-machine skeleton was established via the inverse kinematic modeling of the hydraulic support and the coordinate calculation of the vertices on the three-machine skeleton. Third, the motion data, which were captured by sensors, were applied to drive the movement of the three-machine skeleton and mesh model. Finally, WebGL, which is the latest Internet graphics standard, was used to render the three-machine models, and the performance of this monitoring system is tested on different equipment in the laboratory. The results of the test show that the three-machine cross-platform monitoring system has splendid performance, and it realizes cross-platform 3D monitoring effectively in the laboratory. In the future, this system will be used as a supervisory tool and be integrated with the traditional monitoring system to monitor the three-machine equipment with the field staff.

Architecture of embedded intelligent video analysis system for forest fire prevention

Forest fire has always been an important hidden danger in forestry management. It is necessary to monitor and manage forest fire through video monitoring system. However, due to the lack of real-time performance of traditional video monitoring system and the difficulty in data processing, an embedded intelligent video analysis system is designed. The system uses a software and hardware design method based on Zynq SoC, first, each functional module of the hardware architecture is divided, then the system software is designed, and finally the system is evaluated as a whole. Based on the application requirements of forest fire prevention, this paper focuses on the detailed description of the underlying hardware architecture and operating system software design, and provides some value and reference for the application scenarios of forest fire prevention.

Research on video enhancement concentration and intelligent monitoring technology in Substation

With the development of intelligent theory of computer vision and the popularization of surveillance cameras, intelligent video analysis and surveillance technology has been widely used. The traditional video monitoring system will produce a large amount of video information in the application process, which is not conducive to the storage and reference of information, and it can not carry out real-time warning, and has poor robustness to the bad environment. In view of these disadvantages, this paper proposes an improved video enhancement and concentration method, which has a good effect in ensuring the video concentration ratio and the target loss rate, and can improve the shortcomings brought by manual reference. Aiming at the problem of real-time early warning, an intelligent video analysis method is proposed to realize the functions of event alarm and detection analysis. It is of great significance to improve the video monitoring management level of the substation and realize the unattended operation of the substation.

Intelligent Video Surveillance System Guided by RADAR and AIS Data

In order to solve the problems of traditional video monitoring system that only can monitor a certain fixed area, the matching degree of monitored whole or associated surveillance field is not high, an intelligent video monitoring method which using navigation radar automatic tracking parameters and AIS dynamic data was proposed. The system using tracking parameters output messages of NMEA0183 radar or the output data package of AIS, to obtain the target’s motion elements by analyzing the messages to guide the station and network video station by solving the data allopatry to observe the cloud platform, and open the functions of returning Surveillance video, returning the data of AHRS’s azimuth and elevation, boundary violation alarm et al at the same time. Paper introduced the system’s design process and composition of hardware and software, and the simulation results were given.

Design of Embedded Video Monitoring System Based on DM6437

To solve the difficulty of traditional video monitoring system in system upgrade and expansion, an solution of embedded video monitoring system based on DaVinci technology was put forward in this paper. By building the monitoring platform by DM6437 and DSP/BIOS in the solution, TVP5151 was used for receiving video signal in PAL/NTSC formats, and an JPEG Baseline Profile Encoder was integrated for video encoding, and the 10/100M Ethernet transmission function was realized based on NDK. Finally, the system is tested and the result shows that the system can capture and transmit D1 format signal in 25f/s and met the real-time requirement. At the same time, the system is easy to use and expand with a bright application prospect.

Research of Methods of Theory and Application about Moving Object Detection

In view of the shortcoming and the insufficiency of the traditional video monitoring system is complex, the power and the cost is higher, cost a lot of human resources. This paper design a moving objects detection system on the basis of the traditional video monitoring system in moving target detection algorithm, which applied to special environment conditions. The design in this paper uses ARM processor as the hardware platform and embedded operation system as software platform, uses the algorithm combined the background subtraction method and the frame difference, realizes fast image recognition of moving objects. This system alarms, saves the moving object images, and sends the images to the monitor by mail. The experiment simulation results show that the system detects moving objects fast, accurate, stable, good real-time performance, so it can be applied to unmanned environment monitoring etc and has good market prospects.

Human detection based on motion object extraction and head–shoulder feature

Aimed at the shortcomings of the traditional video monitoring system, human detection method in intelligent video monitoring system was researched. This paper proposed a human detection method based on motion object extraction and head–shoulder feature to complete human detection and statistics in video image sequences. Firstly, background subtraction based on adaptive threshold was used to extract foreground moving object information, then image erosion and image dilation were used to bypass the object shade and remove false object in order to optimize the results of motion object extraction. And finally, for realizing human moving object detection, we proposed the object discrimination algorithm based on human head–shoulder feature to complete human detection and statistics. Experimental results show that the method can successfully realize human detection and statistics. The method is highly accurate and has good real-time and extensive applications. The identification rate is 86% through human video sequences to test. This method can detect human automatically and provide the theoretical and technological base for object detection in the intelligent surveillance system.

Research of Intelligent Video Surveillance System Based on the 3G Technology

Face to the questions in the traditional video monitoring system, this paper proposed the intelligent video surveillance system based on the 3G technology, developed by the embedded system. The system can realize the information transmitted through the 3G network. And the system has the function of remote real-time audio monitoring, remote viewing and download the video data acquisition, and message security alarm.