Intelligent Video Surveillance Technology in Intelligent Transportation

Abstract

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.

RETRACTED: Geometric Construction of Video Stereo Grid Space

“…The automatic analysis, transmission, and decision making by algorithms based on valuable data, as well as the establishment of digital models, comprise an important basis for promoting the construction of digital twin cities. As an indispensable part of current urban construction, video surveillance systems are an important data source for digital twin cities [12]. Therefore, the construction and digital analysis of video data space is an urgent problem to be solved.…”

Improved lightweight vehicle detection algorithm based on YOLOv5s

“…Along with the rapid development of the economy, the number of vehicles in China has increased year by year, prompting a growing concern for traffic safety issues. Vehicle detection has gradually become a research hotspot due to its crucial role in autonomous driving, intelligent monitoring, and smart transportation [1] .…”

Design of foreign object debris detecting and monitoring using two sets of sensor system

“…Meanwhile, to capture object image IP camera can be used as it could transfer the data or convert recorded video files into a digital file that could be accessed through the internet using an IP address determined in advance. Currently, detection using image processing could be developed by easily accessing the website [19]. To control LiDAR and IP camera and to display the image on the web page, we could use a small-sized computer or Raspberry Pi [20], [21] with the programming language Python [22], [23].…”