Traffic Peak Period Detection from an Image Processing View

Xiao, Jiaqi; Li, Hang; Wang, Xiang; Yuan, Shangcao

doi:10.1155/2018/2097932

Cited by 11 publications

(4 citation statements)

References 22 publications

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“…b) Billauer's algorithm is used to validate outcomes of the box and whisker plot results and to detect local maxima and minima in a signal [11]. It provides a graphical visualization analysis of peaks to measure the degree of irregularity of the original data environment.…”

Section: Methodsmentioning

confidence: 99%

“…Iterative steps of the SeLFISA framework deliver an explainable and understandable way of determining the levels of irregularity of such datasets. It applied Billauer's algorithm and mathematical and interquartile range outlier calculations to select, explore and evaluate a variety of sequential datasets [11]. The daily exchange rate data between the GB Pound and the US Dollar has been identified as a dataset which is very suitable for learning because of high irregularity [12].…”

Section: A Datasetsmentioning

confidence: 99%

See 1 more Smart Citation

Selecting Datasets for Evaluating an Enhanced Deep Learning Framework

Dandajena,

Venter,

Ghaziasgar

et al. 2021

Preprint

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A framework was developed to address limitations associated with existing techniques for analysing sequences. This work deals with the steps followed to select suitable datasets characterised by discrete irregular sequential patterns. To identify, select, explore and evaluate which datasets from various sources extracted from more than 400 research articles, an interquartile range method for outlier calculation and a qualitative Billauer's algorithm was adapted to provide periodical peak detection in such datasets. The developed framework was then tested using the most appropriate datasets. The research concluded that the financial market-daily currency exchange domain is the most suitable kind of data set for the evaluation of the designed deep learning framework, as it provides high levels of discrete irregular patterns.

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Section: Methodsmentioning

confidence: 99%

Section: A Datasetsmentioning

confidence: 99%

Selecting Datasets for Evaluating an Enhanced Deep Learning Framework

Dandajena,

Venter,

Ghaziasgar

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…The results indicate that the difference of the periods (0:00-2:00, 6:00-8:00, and 12:00-14:00) is smaller. Considering the urban lifestyle and routine resident behavior [57], this article selects the FCD during 6:00-8:00 and 12:00-14:00 to analyze the changes in road speeds and to investigate the distribution and transfer of traffic-congestion points, areas, and bottlenecks. Table III reflects the influence of rainfall on road speeds under different weather conditions.…”

Section: B Impact Of Rainfall On Road Speedmentioning

confidence: 99%

Analyzing the Effects of Rainfall on Urban Traffic-Congestion Bottlenecks

Yao

Hong

et al. 2020

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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The development of geospatial big data makes it possible to study traffic-congestion issues. In particular, floating car data (FCD) is very suitable for it because FCD can help predict traffic-congestion bottlenecks and provide corresponding solutions to address traffic problems. Previous studies have discussed the impacts of rainfall on road speeds, but few studies have focused on the impacts of rainfall on the spatial distribution and changes in traffic-congestion bottlenecks throughout a mega-city. This article proposes an index calculation and clustering (ICC) model by integrating PageRank and clustering algorithms from multisource data, including rainfall data, FCD, and OpenStreetMap data. As the study area, we selected Shenzhen, which is the largest developed city in South China. The results demonstrate three peak periods of citizen travel, namely, 8:00-10:00, 14:00-16:00, and 18:00-20:00. Road speeds after rainfall decrease by 6.20% on weekdays and by 2.37% on weekends, and traffic-congestion areas increase by 23.53% and 20.65% on weekdays and on weekends, respectively. In addition, rainfall causes more significant effects on traffic conditions on weekdays compared with on weekends in Shenzhen. Compared with a traditional kernel density analysis, the proposed ICC model can offer a more thorough understanding of urban traffic-congestion areas, which can help policy makers optimize alleviation strategies.

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“…The mobile apps can also be exhibited as icons to help those with reading difficulties. The system can also be multilingual [57,58]. A brief description of various subsystems or mobile applications follows.…”

Section: Proposed Healthcare Management System (Hms)mentioning

confidence: 99%

Managing Crowds with Wireless and Mobile Technologies

Yamin

Basahel

Sen

2018

Wireless Communications and Mobile Computing

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Thousands of people have lost their lives in stampedes and other crowd related disasters in recent years. Most of these fatalities seem to have been caused by poor control and management of crowds, which is discussed in this article. An efficient and effective crowd management system must also have a plan to deal with the ongoing threat of terrorism and outbreak of various kinds of communicable diseases. In this article, we present a framework of a Crowd Control and Health Management System specially designed to prevent and manage stampedes and other disasters. The system has two subsystems; one for dealing with the management of stampedes and other disasters and the other with healthcare management. As part of the proposed system, an algorithm for an early detection of stampedes, with proof and simulation of implementation, is provided. As part of the healthcare management subsystem, we integrate several mobile applications and develop four of them dealing with relief issues, blood donations, complaints and alerts, and utilizing mobile phones as a sensor device. Our system makes use of various kinds of wireless, mobile, and other technologies and tools including Fog Computing, Smart Phones, Smart Digital Street, IP-Cameras, Radio Frequency Identification (RFID), Voice Alarm, Light Alarm, and Global Positioning System (GPS). We compare merits and effectiveness of RFID and Wireless Sensor Networks (WSNs), as well as those of Cloud and Fog with a view of using them as part of the proposed framework. We also discuss applications of our systems in real-life cases of Hajj, an annual pilgrimage of millions of people to Mecca, and Kumbh Mela, a periodic gathering of tens of millions of people in India, both of which have accounted for the majority of fatalities in stampedes and other disasters.

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Traffic Peak Period Detection from an Image Processing View

Cited by 11 publications

References 22 publications

Selecting Datasets for Evaluating an Enhanced Deep Learning Framework

Selecting Datasets for Evaluating an Enhanced Deep Learning Framework

Analyzing the Effects of Rainfall on Urban Traffic-Congestion Bottlenecks

Managing Crowds with Wireless and Mobile Technologies

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