scholarly journals Remote Video Surveillance System Based on Direct Show and Image Compression

2013 ◽  
Vol 756-759 ◽  
pp. 439-442
Author(s):  
Shang Fu Gong ◽  
Li Gang Wu ◽  
Yan Jun Wang
Keyword(s):  
Image Compression ◽  
Real Time ◽  
Video Surveillance ◽  
Data Transmission ◽  
Video Transmission ◽  
Massive Data ◽  
Time Requirements ◽  
Rich Information ◽  
Precautionary Measures ◽  
Application Requirements

Video surveillance, convenience and rich information, has been widely used in security, protection, monitoring and other occasions, and has already been one of the most important precautionary measures in commercial, residential and transportation areas. However, considering the massive data transmission needs and higher real-time requirements for video surveillance, a remote video surveillance plan has been put forward on the analysis basis of Microsoft DirectShow and Image Compression. This plan adopts the C/S structure, adapts to the requirements of real-time video transmission, with a better fluency. In addition, the picture clarity satisfies the application requirements.

scholarly journals Guarantee of Information Delivery in the Spacecraft Onboard Network Based on the SpaceWire Interface

2020 ◽  
Vol 7 (4) ◽  
pp. 83-89
Author(s):  
A. Yu. Koshelev ◽  
◽  
A. M. Dianova ◽  
D. O. Petukhov ◽  
◽  
...  
Keyword(s):  
Real Time ◽  
Data Transmission ◽  
Information Delivery ◽  
Protocol Stack ◽  
Software Model ◽  
Time Requirements

Nowadays SpaceWire is regarded as a perspective aerospace data transmission interface standard. This paper gives an analysis of a guaranteed information delivery of SpaceWire networks. The result of the analysis showed key problems that did not allow using this standard in real-time networks. A method was developed and proposed to guarantee the information delivery in the SpaceWire network based on scheduled routing. Tests using a software model of the modified network were performed. The results obtained confirmed the efficiency of the method used to ensure the guarantee of information delivery in the network. It is shown that a network with a modified protocol stack meets real-time requirements.

Ultrasonic Slurry Concentration Meter Design

2013 ◽  
Vol 385-386 ◽  
pp. 488-491
Author(s):  
Xiao Min Han ◽  
Jian Min Wang ◽  
Cong Cong Wang
Keyword(s):  
Data Processing ◽  
Real Time ◽  
Data Transmission ◽  
Ultrasonic Attenuation ◽  
Serial Port ◽  
The Core ◽  
Power Amplification ◽  
Lcd Display ◽  
Rich Information ◽  
The Rich

This design is based on the theory of ultrasonic attenuation,design of pulp concentration is C8051F021 microcontroller as the core of the meter, And contains the ultrasonic transmitting circuit, receiving circuit, the power amplification circuit, detection shaping circuit, LCD display circuit, 485 communication circuit. In addition to the data processing by appropriate filtering software, shield the noise and clutter signal, the rich information of real-time display, and the measurement of data transmission in serial port to a PC through the analysis and comparison.

Telemetric Control of Remote Vehicles using an Inverse RTK Technique

2003 ◽  
Vol 56 (1) ◽  
pp. 123-136
Author(s):  
Ahmed El-Mowafy
Keyword(s):  
Real Time ◽  
Ambiguity Resolution ◽  
Data Transmission ◽  
Video Transmission ◽  
Base Station ◽  
Real Time Control ◽  
Time Control ◽  
Long Baseline ◽  
Satellite Visibility ◽  
Rtk Gps

In this study, an inverse Real Time Kinematic (RTK) GPS positioning approach is presented and discussed. GPS data from a remote receiver mounted on an unmanned vehicle is sent to the base station to determine the vehicle location at the centimetre level of accuracy in real time. Control of the vehicle's movement and manoeuvring can thus take place at the base station, which could be a few kilometres away, and the vehicle can be sent to specific locations to do certain tasks. Two GPS antennas were used in order to increase positioning reliability and estimate real time heading and pitch of the vehicle for better control. In addition, the vehicle was fitted with cameras with wireless video transmission to provide the operator with a good level of vision in different directions during operation. The main applications of such a system would be in exploration, breaching and clearance of minefields, and hazardous situations such as fire fighting of burning oil wells. The system design and techniques employed are discussed first. Issues addressed include antenna layout, data transmission, solution algorithm, and ambiguity resolution. The proposed system was mounted on a prototype vehicle and tested under different satellite visibility conditions. Results show that high positioning accuracy with reliable ambiguity resolution can be obtained with the developed approach if the number of observed satellites is 5 or more and PDOP is less than 5. Heading and pitch were determined within 0·2–0·3 degree using a 1·2 m long baseline. This performance can be improved as the length of the on-board baseline increases.

Lightweight deep network-enabled real-time low-visibility enhancement for promoting vessel detection in maritime video surveillance

2021 ◽  
pp. 1-21
Author(s):  
Yu Guo ◽  
Yuxu Lu ◽  
Ryan Wen Liu
Keyword(s):  
Real Time ◽  
Video Surveillance ◽  
Traffic Safety ◽  
Visual Sensing ◽  
Maritime Surveillance ◽  
Vessel Detection ◽  
Low Visibility ◽  
Degraded Image ◽  
Time Requirements ◽  
Visibility Enhancement

Abstract Maritime video surveillance has become an essential part of the vessel traffic services system, intended to guarantee vessel traffic safety and security in maritime applications. To make maritime surveillance more feasible and practicable, many intelligent vision-empowered technologies have been developed to automatically detect moving vessels from maritime visual sensing data (i.e., maritime surveillance videos). However, when visual data is collected in a low-visibility environment, the essential optical information is often hidden in the dark, potentially resulting in decreased accuracy of vessel detection. To guarantee reliable vessel detection under low-visibility conditions, the paper proposes a low-visibility enhancement network (termed LVENet) based on Retinex theory to enhance imaging quality in maritime video surveillance. LVENet is a lightweight deep neural network incorporating a depthwise separable convolution. The synthetically-degraded image generation and hybrid loss function are further presented to enhance the robustness and generalisation capacities of LVENet. Both full-reference and no-reference evaluation experiments demonstrate that LVENet could yield comparable or even better visual qualities than other state-of-the-art methods. In addition, it takes LVENet just 0⋅0045 s to restore degraded images with size 1920 × 1080 pixels on an NVIDIA 2080Ti GPU, which can adequately meet real-time requirements. Using LVENet, vessel detection performance can be greatly improved with enhanced visibility under low-light imaging conditions.

scholarly journals Real-Time Implementation of Change Detection for Automated Video Surveillance System

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Sanjay Singh ◽  
A. S. Mandal ◽  
Chandra Shekhar ◽  
Anil Vohra
Keyword(s):  
Change Detection ◽  
Real Time ◽  
Video Surveillance ◽  
Surveillance System ◽  
Vlsi Architecture ◽  
Video Stream ◽  
Video Surveillance System ◽  
Time Requirements ◽  
Selection Of ◽  
Automated Video Surveillance

Change detection is one of the several important problems in the design of any automated video surveillance system. Appropriate selection of frames of significant changes can minimize the communication and processing overheads for such systems. This research presents the design of a VLSI architecture for change detection in a video sequence and its implementation on Virtex-IIPro FPGA platform. Clustering-based scheme is used for change detection. The proposed system is designed to meet the real-time requirements of video surveillance applications. It robustly detects the changes in a video stream in real time at 25 frames per second (fps) in gray scale CIF size video.

Safety Monitoring and Warning System for Subway Construction Workers using Wearable Technology

2019 ◽  
Vol 13 ◽  
Author(s):  
Jun-hua Chen ◽  
Da-hu Wang ◽  
Cun-yuan Sun
Keyword(s):  
Real Time ◽  
Video Surveillance ◽  
Early Warning ◽  
Warning System ◽  
Safety Monitoring ◽  
Wearable Technology ◽  
Construction Workers ◽  
Great Success ◽  
Subway Construction ◽  
Monitoring And Early Warning

Objective: This study focused on the application of wearable technology in the safety monitoring and early warning for subway construction workers. Methods: With the help of real-time video surveillance and RFID positioning which was applied in the construction has realized the real-time monitoring and early warning of on-site construction to a certain extent, but there are still some problems. Real-time video surveillance technology relies on monitoring equipment, while the location of the equipment is fixed, so it is difficult to meet the full coverage of the construction site. However, wearable technologies can solve this problem, they have outstanding performance in collecting workers’ information, especially physiological state data and positioning data. Meanwhile, wearable technology has no impact on work and is not subject to the inference of dynamic environment. Results and conclusion: The first time the system applied to subway construction was a great success. During the construction of the station, the number of occurrences of safety warnings was 43 times, but the number of occurrences of safety accidents was 0, which showed that the safety monitoring and early warning system played a significant role and worked out perfectly.

scholarly journals Intelligent IoT systems for civil infrastructure health monitoring: a research roadmap

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
E. Bertino ◽  
M. R. Jahanshahi ◽  
A. Singla ◽  
R.-T. Wu
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Original Data ◽  
Local Analysis ◽  
Civil Infrastructure ◽  
Time Requirements ◽  
Iot Devices ◽  
Learning Reinforcement ◽  
The Times ◽  
Acquisition Processes

AbstractThis paper addresses the problem of efficient and effective data collection and analytics for applications such as civil infrastructure monitoring and emergency management. Such problem requires the development of techniques by which data acquisition devices, such as IoT devices, can: (a) perform local analysis of collected data; and (b) based on the results of such analysis, autonomously decide further data acquisition. The ability to perform local analysis is critical in order to reduce the transmission costs and latency as the results of an analysis are usually smaller in size than the original data. As an example, in case of strict real-time requirements, the analysis results can be transmitted in real-time, whereas the actual collected data can be uploaded later on. The ability to autonomously decide about further data acquisition enhances scalability and reduces the need of real-time human involvement in data acquisition processes, especially in contexts with critical real-time requirements. The paper focuses on deep neural networks and discusses techniques for supporting transfer learning and pruning, so to reduce the times for training the networks and the size of the networks for deployment at IoT devices. We also discuss approaches based on machine learning reinforcement techniques enhancing the autonomy of IoT devices.

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