Fast and Precise: Parallel Processing of Vehicle Traffic Videos Using Big Data Analytics

Perafan-Villota, Juan C.; Mondragon, Oscar H.; Mayor-Toro, Walter M.

doi:10.1109/tits.2021.3109625

Cited by 12 publications

(6 citation statements)

References 26 publications

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“…The emergence of intelligent technology tools has ushered in the fourth paradigm of scientific research, which is characterized by data-intensive research [ 1 ]. In this context, big data provides rich “nutrients” for research in various disciplines [ 2 – 4 ]. Data-driven approaches and concepts have become the new engine of big data utilization, gradually penetrating scientific research in various disciplines [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Hotspot Mining in the Field of Library and Information Science under the Environment of Big Data

Jiang

2022

Journal of Environmental and Public Health

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Currently, with the implementation of big data strategies in countries all over the world, big data has achieved vigorous development in various fields. Big data research and application practices have also rapidly attracted the attention of the library and information field. Objective. The study explored the current state of research and research hotspots of big data in the library and information field and further discussed the future research trends. Methods. In the CNKI database, 16 CSSCI source journals in the discipline of library information and digital library were selected as data sources, and the relevant literature was retrieved with the theme of “big data.” The collected literature was excluded and expanded according to the citation relationship. Then, with the help of Bicomb and SPSS, co-word analysis and cluster analysis would be carried out on these literature results. Results. According to the findings of the data analysis, the research hotspots on the topic mainly focus on five major research themes, namely, big data and smart library, big data and intelligence research, data mining and cloud computing, big data and information analysis, and library innovation and services. Limitations. At present, the research scope and coverage on this topic are wide, which leads to the research still staying at the macro level. Conclusions. Big data research will remain one of the hotspots in the future. However, the most study is still limited to the perspective of library and information and has not yet analyzed the research status, research hotspots, and development trends in this field from the perspective of big data knowledge structure. Moreover, machine learning, artificial intelligence, knowledge services, AR, and VR may be new directions for future attention and development.

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Section: Introductionmentioning

confidence: 99%

[Retracted] Hotspot Mining in the Field of Library and Information Science under the Environment of Big Data

Jiang

2022

Journal of Environmental and Public Health

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“…Internal Operation Architecture under Big Data and Internet of Things Technology. Under the technology of big data and Internet of things, in the process of metabolic prediction of human function, first determine the active intrusion intention of complex network [18][19][20], establish the set function of intrusion intention and attack behavior, and estimate the diffusion equation of active intrusion metabolism of complex network on this basis. Based on the diffusion equation, a grey prediction model of active intrusion metabolism in complex networks is constructed [21,22].…”

Section: Realize the Metabolic Grey Prediction Modelmentioning

confidence: 99%

The Metabolism Grey Prediction Model Based on Big Data and Internet of Things Technology

Ren

Sun

Shan

et al. 2022

Wireless Communications and Mobile Computing

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In view of the uncertainty and diversity of the metabolic grey prediction model in the prediction process, resulting in poor prediction effect, a metabolic grey prediction model based on big data and Internet of things technology is constructed. Establish the aerobic metabolic process of human telecontrol and put forward the detection index of aerobic metabolic cycle function in human telecontrol; on this basis, use the metabolic grey prediction model analysis algorithm to determine the active intrusion intention of complex network, establish the intrusion intention attack behavior set function, establish the internal operation architecture under the technology of big data and Internet of things, and realize the construction of metabolic grey prediction model. The experimental results show that the constructed model can realize data prediction, with high confidence level and good effect.

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“…It is not enough just to detect vehicles, other studies have also observed vehicle tracking using (Y. Chen & Hu, 2020;Perafan-Villota et al, 2022). Vehicle tracking is intended to find out the level of road congestion based on the average vehicle speed and type of highway which is divided into 3 types, namely highways (expressways), main roads, and secondary roads (branches) (Xing et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…Several things must be considered in managing congestion, such as the need to know the number of vehicles, detect the type of vehicle, track the vehicle, and estimate the speed of the vehicle. Vehicle detection uses the YOLO framework (Gomaa et al, 2022;Neupane et al, 2022;Perafan-Villota et al, 2022). This frame underwent framework innovation to improve its performance in object detection such as YOLOv2, YOLOv3, YOLOv4, and YOLO5 and of course, YOLOv5 has the best performance compared to others in the YOLO Family (Y. W. Chen & Shiu, 2022).…”

Section: Introductionmentioning

confidence: 99%

Indicator of Highway Conditions on Traffic Density Levels

Rosita

Akbar²,

Kurniawan³

2023

ijeeit

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Traffic problems, especially congestion which is the impact of high levels of traffic density, are problems that have not been properly resolved, especially in big cities in Indonesia. In this article, 7 features of road conditions are proposed on the level of traffic density. These features include the number of vehicles, the average speed of the vehicle, the area of the main road, the length of traffic that has been determined, the duration of traffic congestion, and the time of traffic congestion. Determining the level of traffic density can be determined by utilizing the MCDM hybrid technique to produce information that can be used to support decision-making in traffic management or other policies such as formulating policies on the buying and selling of private vehicles. The number of indicators related to computer vision for presenting information on the level of traffic density requires a large amount of time and memory. Besides that, the perception of a decision maker in determining priority weights also influences the results of the information on the level of traffic density.

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Fast and Precise: Parallel Processing of Vehicle Traffic Videos Using Big Data Analytics

Cited by 12 publications

References 26 publications

[Retracted] Hotspot Mining in the Field of Library and Information Science under the Environment of Big Data

[Retracted] Hotspot Mining in the Field of Library and Information Science under the Environment of Big Data

The Metabolism Grey Prediction Model Based on Big Data and Internet of Things Technology

Indicator of Highway Conditions on Traffic Density Levels

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