scholarly journals Intelligent Video Surveillance Technology in Intelligent Transportation

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Fangcheng He
Keyword(s):  
Video Surveillance ◽  
Traffic Accidents ◽  
Intelligent Transportation ◽  
Traffic Monitoring ◽  
Motion Blur ◽  
Urban Traffic ◽  
Technology Research ◽  
Monitoring Technology ◽  
Intelligent Video Surveillance ◽  
Surveillance Technology

Along with the strength of the country’s overall strength, the people’s pockets have become more and more popular, and there have been significant improvements in all aspects of life, especially in terms of travel methods. This reflects the increase in residents’ income, but it also brings huge traffic pressure. In the long run, traffic congestion is not only detrimental to urban development, but frequent traffic accidents threaten residents’ travel safety. Effective monitoring methods are essential to solving these problems, so it is necessary to carry out research on intelligent video monitoring technology in intelligent transportation. The purpose of this article is to solve the current situation of excessive traffic pressure in the city. Through the study of intelligent video surveillance technology in intelligent traffic, the use of constrained least squares algorithm to remove motion blur and apply Kalan filtering to the sharpening process is used to eliminate noise ambiguity and make a brief introduction to various classic moving target detection methods to realize real-time monitoring of intelligent traffic conditions and continuously adjust and verify the monitoring situation, and then establish intelligent video in intelligent traffic monitoring technology research system. The research results show that this kind of intelligent video surveillance technology research in intelligent transportation can effectively increase the awareness of intelligent video surveillance technology and improve the level of intelligent video surveillance technology. The data measurement time has been shortened by one hour, the aggregation time has been changed from three hours to two hours, and the analysis time has been shortened by half. Eased urban traffic road pressure and greatly reduced the incidence of traffic accidents, which is conducive to socialist harmony social construction.

Semantic Based Annotation for Surveillance Big Data Using Domain Knowledge

2015 ◽  
Vol 9 (1) ◽  
pp. 16-29 ◽  
Author(s):  
Feng Xie ◽  
Zheng Xu
Keyword(s):  
Video Surveillance ◽  
Domain Knowledge ◽  
Traffic Monitoring ◽  
Static Properties ◽  
Multimedia Resources ◽  
Surveillance Technology ◽  
Intelligent Analysis ◽  
Traffic Violations ◽  
Crucial Information ◽  
Traffic Detection

Video surveillance technology is playing a more and more important role in traffic detection. Vehicle's static properties are crucial information in examining criminal and traffic violations. Image and video resources play an important role in traffic events analysis. With the rapid growth of the video surveillance devices, large number of image and video resources is increasing being created. It is crucial to explore, share, reuse, and link these multimedia resources for better organizing traffic events. With the development of Video Surveillance technology, it has been wildly used in the traffic monitoring. Therefore, there is a trend to use Video Surveillance to do intelligent analysis on vehicles. Now, using software and tools to analyze vehicles in videos has already been used in smart cards and electronic eye, which helps polices to extract useful information like plate, speed, etc. And the key technology is to obtain various properties of the vehicle. This paper provides an overview of the algorithms and technologies used in extracting static properties of vehicle in the video.

Semantic Based Annotation for Surveillance Big Data Using Domain Knowledge

2019 ◽  
pp. 660-674
Author(s):  
Feng Xie ◽  
Zheng Xu
Keyword(s):  
Video Surveillance ◽  
Domain Knowledge ◽  
Traffic Monitoring ◽  
Static Properties ◽  
Multimedia Resources ◽  
Surveillance Technology ◽  
Intelligent Analysis ◽  
Traffic Violations ◽  
Crucial Information ◽  
Traffic Detection

Video surveillance technology is playing a more and more important role in traffic detection. Vehicle's static properties are crucial information in examining criminal and traffic violations. Image and video resources play an important role in traffic events analysis. With the rapid growth of the video surveillance devices, large number of image and video resources is increasing being created. It is crucial to explore, share, reuse, and link these multimedia resources for better organizing traffic events. With the development of Video Surveillance technology, it has been wildly used in the traffic monitoring. Therefore, there is a trend to use Video Surveillance to do intelligent analysis on vehicles. Now, using software and tools to analyze vehicles in videos has already been used in smart cards and electronic eye, which helps polices to extract useful information like plate, speed, etc. And the key technology is to obtain various properties of the vehicle. This paper provides an overview of the algorithms and technologies used in extracting static properties of vehicle in the video.

scholarly journals Spatio-Temporal Visual Analysis for Urban Traffic Characters Based on Video Surveillance Camera Data

2021 ◽  
Vol 10 (3) ◽  
pp. 177
Author(s):  
Haochen Zou ◽  
Keyan Cao ◽  
Chong Jiang
Keyword(s):  
Video Surveillance ◽  
Traffic Management ◽  
Visual Analysis ◽  
Urban Traffic ◽  
License Plate ◽  
Road Vehicle ◽  
Urban Road ◽  
Surveillance Camera ◽  
Vehicle Density ◽  
Spatio Temporal

Urban road traffic spatio-temporal characters reflect how citizens move and how goods are transported, which is crucial for trip planning, traffic management, and urban design. Video surveillance camera plays an important role in intelligent transport systems (ITS) for recognizing license plate numbers. This paper proposes a spatio-temporal visualization method to discover urban road vehicle density, city-wide regional vehicle density, and hot routes using license plate number data recorded by video surveillance cameras. To improve the accuracy of the visualization effect, during data analysis and processing, this paper utilized Internet crawler technology and adopted an outlier detection algorithm based on the Dixon detection method. In the design of the visualization map, this paper established an urban road vehicle traffic index to intuitively and quantitatively reveal the traffic operation situation of the area. To verify the feasibility of the method, an experiment in Guiyang on data from road video surveillance camera system was conducted. Multiple urban traffic spatial and temporal characters are recognized concisely and efficiently from three visualization maps. The results show the satisfactory performance of the proposed framework in terms of visual analysis, which will facilitate traffic management and operation.

scholarly journals LPWAN-based hybrid backhaul communication for intelligent transportation systems: architecture and performance evaluation

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Taghi Shahgholi ◽  
Amir Sheikhahmadi ◽  
Keyhan Khamforoosh ◽  
Sadoon Azizi
Keyword(s):  
Low Power ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation System ◽  
Road Traffic ◽  
Intelligent Transportation ◽  
Traffic Monitoring ◽  
Transportation Systems ◽  
Area Network ◽  
Emergency Vehicle ◽  
Wide Area Network

AbstractIncreased number of the vehicles on the streets around the world has led to several problems including traffic congestion, emissions, and huge fuel consumption in many regions. With advances in wireless and traffic technologies, the Intelligent Transportation System (ITS) has been introduced as a viable solution for solving these problems by implementing more efficient use of the current infrastructures. In this paper, the possibility of using cellular-based Low-Power Wide-Area Network (LPWAN) communications, LTE-M and NB-IoT, for ITS applications has been investigated. LTE-M and NB-IoT are designed to provide long range, low power and low cost communication infrastructures and can be a promising option which has the potential to be employed immediately in real systems. In this paper, we have proposed an architecture to employ the LPWAN as a backhaul infrastructure for ITS and to understand the feasibility of the proposed model, two applications with low and high delay requirements have been examined: road traffic monitoring and emergency vehicle management. Then, the performance of using LTE-M and NB-IoT for providing backhaul communication infrastructure has been evaluated in a realistic simulation environment and compared for these two scenarios in terms of end-to-end latency per user. Simulation of Urban MObility has been used for realistic traffic generation and a Python-based program has been developed for evaluation of the communication system. The simulation results demonstrate the feasibility of using LPWAN for ITS backhaul infrastructure mostly in favor of the LTE-M over NB-IoT.

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