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Journal articles on the topic 'Analysis crowd'

Author: Grafiati

Published: 9 March 2023

Last updated: 31 July 2025

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1

Husman, Muhammad Afif, Waleed Albattah, Zulkifli Zainal Abidin, et al. "Unmanned Aerial Vehicles for Crowd Monitoring and Analysis." Electronics 10, no. 23 (2021): 2974. http://dx.doi.org/10.3390/electronics10232974.

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Crowd monitoring and analysis has become increasingly used for unmanned aerial vehicle applications. From preventing stampede in high concentration crowds to estimating crowd density and to surveilling crowd movements, crowd monitoring and analysis have long been employed in the past by authorities and regulatory bodies to tackle challenges posed by large crowds. Conventional methods of crowd analysis using static cameras are limited due to their low coverage area and non-flexible perspectives and features. Unmanned aerial vehicles have tremendously increased the quality of images obtained for

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Elbishlawi, Sherif, Mohamed H. Abdelpakey, Agwad Eltantawy, Mohamed S. Shehata, and Mostafa M. Mohamed. "Deep Learning-Based Crowd Scene Analysis Survey." Journal of Imaging 6, no. 9 (2020): 95. http://dx.doi.org/10.3390/jimaging6090095.

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Recently, our world witnessed major events that attracted a lot of attention towards the importance of automatic crowd scene analysis. For example, the COVID-19 breakout and public events require an automatic system to manage, count, secure, and track a crowd that shares the same area. However, analyzing crowd scenes is very challenging due to heavy occlusion, complex behaviors, and posture changes. This paper surveys deep learning-based methods for analyzing crowded scenes. The reviewed methods are categorized as (1) crowd counting and (2) crowd actions recognition. Moreover, crowd scene data

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Bhuiyan, Roman, Junaidi Abdullah, Noramiza Hashim, et al. "Deep Dilated Convolutional Neural Network for Crowd Density Image Classification with Dataset Augmentation for Hajj Pilgrimage." Sensors 22, no. 14 (2022): 5102. http://dx.doi.org/10.3390/s22145102.

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Almost two million Muslim pilgrims from all around the globe visit Mecca each year to conduct Hajj. Each year, the number of pilgrims grows, creating worries about how to handle such large crowds and avoid unpleasant accidents or crowd congestion catastrophes. In this paper, we introduced deep Hajj crowd dilated convolutional neural network (DHCDCNNet) for crowd density analysis. This research also presents augmentation technique to create additional dataset based on the hajj pilgrimage scenario. We utilized a single framework to extract both high-level and low-level features. For creating add

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R, Shaamili. "A Research Perceptive on Deep Learning Framework for Pedestrian Detection in a Crowd." Computational Intelligence and Machine Learning 3, no. 2 (2022): 9–14. http://dx.doi.org/10.36647/ciml/03.02.a002.

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In populated cities, we often find crowded events like political meetings, religious festivals, music concerts, and events in shopping malls, which have more safety issues. Smart surveillance systems are used in big cities to keep crowds safe and make crowd security less complicated and more accurate. However, the surveillance systems proposed for a crowd are monitored by human agents, which are inefficient, error-prone, and overwhelming. Even with deep learning-based feature engineering in crowds, many variants of crowd analysis still lack attention and are technically unaddressed. Considerin

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Yugendar, Poojari, and K. V. R. Ravishankar. "Crowd Behavioural Analysis at a Mass Gathering Event." Journal of KONBiN 46, no. 1 (2018): 5–20. http://dx.doi.org/10.2478/jok-2018-0020.

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Abstract Religious occasions, gathering at fairs and terminals, are the events of crowd gatherings. Such gatherings act as severe threats for crowds because of high density in less space, which ends up in adverse outcomes resulting in crowd stampedes. The movement of an individual person in a crowd is influenced by the physical factors. In the present study, characteristics like age, gender, group size, child holding, child carrying, people with luggage and without luggage are considered for crowd behaviour analysis. The average speed of the crowd movement was observed as 0.86 m/s. The statist

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Andriyanto, Sidhiq, M. Suyanto, and Sukoco Sukoco. "Implementasi Metode Reynolds menggunakan Simulasi Kerumunan Bebek." INTENSIF 1, no. 2 (2017): 75. http://dx.doi.org/10.29407/intensif.v1i2.788.

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 "Simulation of Duck Crows Using Reynolds Method" is a study with the aim to find out the behavior of duck breeding crowd. The next goal is to make a crowd simulation using the Reynolds method. Limitations of this research variable is the object of research on adult duck Turi, the method used is Reynolds method. The simulations are made using Unity3D software in the form of 3D and the animation provided is just a running gesture. The method of analysis of this research is using research and development method. The result of the research is the data of duck walking in the crowd to be appl

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JOHANSSON, ANDERS, DIRK HELBING, HABIB Z. AL-ABIDEEN, and SALIM AL-BOSTA. "FROM CROWD DYNAMICS TO CROWD SAFETY: A VIDEO-BASED ANALYSIS." Advances in Complex Systems 11, no. 04 (2008): 497–527. http://dx.doi.org/10.1142/s0219525908001854.

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The study of crowd dynamics is interesting because of the various self-organization phenomena resulting from the interactions of many pedestrians, which may improve or obstruct their flow. Besides formation of lanes of uniform walking direction and oscillations at bottlenecks at moderate densities, it was recently discovered that stop-and-go waves [D. Helbing et al., Phys. Rev. Lett.97 (2006) 168001] and a phenomenon called "crowd turbulence" can occur at high pedestrian densities [D. Helbing et al., Phys. Rev. E75 (2007) 046109]. Although the behavior of pedestrian crowds under extreme condit

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Aiello, Lucia. "Digital Skill Evolution in an Industrial Relationship." International Journal of R&D Innovation Strategy 1, no. 1 (2019): 1–15. http://dx.doi.org/10.4018/ijrdis.2019010101.

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Crowdsourcing is a powerful mechanism for doing online work and allows for collaboration. By now, in the media and in business on the Internet, crowdsourcing is recognized as an innovative form of value creation that needs taken seriously. This article provides a framework to propose the relation between crowds and tutorship; it considers the tutor of a crowd as a strategic professional figure in an online community. This is done by the consideration of the different roles, activities and tasks of a tutor through the field analysis of a platform of one company that uses crowdsourcing. This tut

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Kim, Eui Myoung, and Seung Chan Hong. "Crowd Density Analysis Using Crowd Simulation." Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography 43, no. 3 (2025): 297–304. https://doi.org/10.7848/ksgpc.2025.43.3.297.

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Denis, Stijn, Ben Bellekens, Abdil Kaya, Rafael Berkvens, and Maarten Weyn. "Large-Scale Crowd Analysis through the Use of Passive Radio Sensing Networks." Sensors 20, no. 9 (2020): 2624. http://dx.doi.org/10.3390/s20092624.

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The creation of an automatic crowd estimation system capable of providing reliable, real-time estimates of human crowd sizes would be an invaluable tool for organizers of large-scale events, particularly so in the context of safety management. We describe a set of experiments in which we installed a passive Radio Frequency (RF) sensor network in different environments containing thousands of human individuals and discuss the accuracy with which the resulting measurements can be used to estimate the sizes of these crowds. Depending on the selected training approach, a median crowd estimation er

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Borch, Christian. "Body to Body: On the Political Anatomy of Crowds." Sociological Theory 27, no. 3 (2009): 271–90. http://dx.doi.org/10.1111/j.1467-9558.2009.01348.x.

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This article challenges the negative image that, since the late 19th century, has been associated with crowds, and it does so by focusing on a number of bodily-anatomic aspects of crowd behavior. I first demonstrate that the work of one of the leading crowd psychologists, Gustave Le Bon, instigated a racist body politics. As a contrast to Le Bon's political program, I examine Walt Whitman's poetry and argue that the crowd may embody a democratic vision that emphasizes the social and political import of sexuality and body-to-body contact. Further, I dispute classical crowd theory's idea of an a

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Negied, Nermin Kamal Abdel-Wahab, Elsayed B. Hemayed, and Magda Fayek. "HSBS: A Human’s Heat Signature and Background Subtraction Hybrid Approach for Crowd Counting and Analysis." International Journal of Pattern Recognition and Artificial Intelligence 30, no. 08 (2016): 1655025. http://dx.doi.org/10.1142/s0218001416550259.

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This work presents a new approach for crowd counting and classification based upon human thermal and motion features. The technique is efficient for automatic crowd density estimation and type of motion determination. Crowd density is measured without any need for camera calibration or assumption of prior knowledge about the input videos. It does not need any human intervention so it can be used successfully in a fully automated crowd control systems. Two new features are introduced for crowd counting purpose: the first represents thermal characteristics of humans and is expressed by the ratio

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Obbo, Aggrey, Pius Ariho, and Evarist Nabaasa. "Towards People Crowd Detection Using Wireless Sensor Networks." European Journal of Technology 6, no. 2 (2022): 32–48. http://dx.doi.org/10.47672/ejt.1071.

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Objective: The objective of this study was to examine and propose the use of wireless sensor networks for people crowd detection in resource constrained environments such as developing economies. Methodology: A systematic review was carried out on current technological trends and application of Wireless Sensor Networks (WSNs) in crowd detection. For this study, focus was on WSN implementation in developing economies, where infrastructure is underdeveloped and people crowds are dynamic and spontaneous. Based on a requirement analysis and knowledge of the inherent challenges of WSNs, a WSN

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Nishiyama, Hidefumi. "Crowd surveillance: The (in)securitization of the urban body." Security Dialogue 49, no. 3 (2018): 200–216. http://dx.doi.org/10.1177/0967010617741436.

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The recent proliferation of the securitization of crowded places has led to a growth in the development of technologies of crowd behaviour analysis. However, despite the emerging prominence of crowd surveillance in emergency planning, its impacts on our understanding of security and surveillance have received little discussion. Using the case of crowd surveillance in Tokyo, this article examines the ways in which crowds are simulated, monitored and secured through the technology of crowd behaviour analysis, and discusses the implications on the politics of security. It argues that crowd survei

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Chen, Jun, Huan Tan, Katrien Van Nimmen, and Peter Van den Broeck. "Data-Driven Synchronization Analysis of a Bouncing Crowd." Shock and Vibration 2019 (June 11, 2019): 1–23. http://dx.doi.org/10.1155/2019/8528763.

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Vibration serviceability problems concerning lightweight, flexible long-span floors and cantilever structures such as grandstands generally arise from crowd-induced loading, in particular due to bouncing or jumping activities. Predicting the dynamic responses of these structures induced by bouncing and jumping crowds has therefore become a critical aspect of vibration serviceability design. Although accurate models describing the load induced by a single person are available, essential information on the level of synchronization within the crowd is missing. In answer to this lack of informatio

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Dobryshev, Ruslan Ye. "Tasks of visual crowd analysis in intelligent video surveillance systems." Informatics. Culture. Technology 1, no. 1 (2024): 212–20. http://dx.doi.org/10.15276/ict.01.2024.32.

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Modern urban population growth creates challenges for public safety, in particular due to crowds. This stimulates the development of new crowd management methods that require automated analysis. Visual crowd analysis based on computer vision technologies is a key tool for solving these problems. The development of deep learning has significantly improved the monitoring systems used for urban surveillance, social distancing control, transportation and event management. However, crowd analysis remains challenging due to occlusions, scale variations, unpredictable movement patterns, and complex b

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Malhotra, Arvind, and Ann Majchrzak. "Greater associative knowledge variety in crowdsourcing platforms leads to generation of novel solutions by crowds." Journal of Knowledge Management 23, no. 8 (2019): 1628–51. http://dx.doi.org/10.1108/jkm-02-2019-0094.

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Purpose The purpose of this study is to offer implications and future research directions related to new organizational forms like crowds. Organizations are increasingly relying on online crowds to innovate through mechanisms such as crowdsourcing, open innovation, innovation challenges and tournaments. To leverage the "wisdom of crowds", crowdsourcing platforms that enable heterogeneous knowledge sharing in crowds lead to novel solution generation by individuals in the crowd. Based on the associative variety memory model of creativity, the authors hypothesize that when a crowd contributes a h

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Sonkar, Riddhi, Sadhana Rathod, Renuka Jadhav, and Deepali Patil. "CROWD ABNORMAL BEHAVIOUR DETECTION USING DEEP LEARNING." ITM Web of Conferences 32 (2020): 03040. http://dx.doi.org/10.1051/itmconf/20203203040.

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Crowd analysis has become an extremely famous research point in the territory of computer vision. Computerized examination of group exercises utilizing reconnaissance recordings is a significant issue for public security since it permits the identification of hazardous groups and where they’re going. We all see how many problems are faced because of the crowd. In our country, many terrorists are there. They plant a bomb in a crowded area which causes a lot of injuries. Thieves are mostly found or always leave in crowded areas so they can easily get an advantage of the crowd. In that situation,

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Cao, Dong, Zuanfeng Pan, and Yu Fang. "Dynamic Response Analysis of the Floor Structure under Random Crowd Excitation." Shock and Vibration 2024 (January 10, 2024): 1–19. http://dx.doi.org/10.1155/2024/1451839.

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The popularity of new structural systems and prestressing technology has led to the widespread use of the large-space floor structures in large buildings such as high-speed rail terminals, conference centers, and sports stadiums. The reduction of nonessential load-bearing elements and the increase in span of the structure result in a reduction in the natural frequency and damping ratio of the floor structure, while the floor is a crowded area with disorderly flow between people, which may lead to human-induced vibration problems. In order to assess the dynamic performance of the large-span flo

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BHUIYAN, MD ROMAN, Dr Junaidi Abdullah, Dr Noramiza Hashim, et al. "Crowd density estimation using deep learning for Hajj pilgrimage video analytics." F1000Research 10 (January 14, 2022): 1190. http://dx.doi.org/10.12688/f1000research.73156.2.

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Background: This paper focuses on advances in crowd control study with an emphasis on high-density crowds, particularly Hajj crowds. Video analysis and visual surveillance have been of increasing importance in order to enhance the safety and security of pilgrimages in Makkah, Saudi Arabia. Hajj is considered to be a particularly distinctive event, with hundreds of thousands of people gathering in a small space, which does not allow a precise analysis of video footage using advanced video and computer vision algorithms. This research proposes an algorithm based on a Convolutional Neural Network

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Shukla, Shivang, Bernard Tiddeman, and Helen C. Miles. "A Wide Area Multiview Static Crowd Estimation System Using UAV and 3D Training Simulator." Remote Sensing 13, no. 14 (2021): 2780. http://dx.doi.org/10.3390/rs13142780.

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Crowd size estimation is a challenging problem, especially when the crowd is spread over a significant geographical area. It has applications in monitoring of rallies and demonstrations and in calculating the assistance requirements in humanitarian disasters. Therefore, accomplishing a crowd surveillance system for large crowds constitutes a significant issue. UAV-based techniques are an appealing choice for crowd estimation over a large region, but they present a variety of interesting challenges, such as integrating per-frame estimates through a video without counting individuals twice. Larg

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Vahid, Behtaji Siahkal Mahalleh, Selamat Hazlina, and Sandhu Fargham. "Review on Psychological Crowd Model Based on LeBon's Theory." TELKOMNIKA Telecommunication, Computing, Electronics and Control 15, no. 2 (2017): 763–70. https://doi.org/10.12928/TELKOMNIKA.v15i2.6114.

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Irrational crowds tend to adapt herd mentality, having group behaviour and high suggestion through interaction. It is important to see how an irrational crowd can be controlled to prevent undesirable crowd attitude. This paper reviews existing models and the controllers to provide a comprehensive study for crowd control. It focuses on a comprehensive analysis of the control of psychological crowd, modelled using LeBon’s theory; which defines the crowd behaviour in terms of crowd attitude. The crowd attitude is defined in terms of suggestibility and prestige and the crowd interaction is d

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Cecaj, Alket, Marco Lippi, Marco Mamei, and Franco Zambonelli. "Sensing and Forecasting Crowd Distribution in Smart Cities: Potentials and Approaches." IoT 2, no. 1 (2021): 33–49. http://dx.doi.org/10.3390/iot2010003.

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The possibility of sensing and predicting the movements of crowds in modern cities is of fundamental importance for improving urban planning, urban mobility, urban safety, and tourism activities. However, it also introduces several challenges at the level of sensing technologies and data analysis. The objective of this survey is to overview: (i) the many potential application areas of crowd sensing and prediction; (ii) the technologies that can be exploited to sense crowd along with their potentials and limitations; (iii) the data analysis techniques that can be effectively used to forecast cr

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Cecaj, Alket, Marco Lippi, Marco Mamei, and Franco Zambonelli. "Sensing and Forecasting Crowd Distribution in Smart Cities: Potentials and Approaches." IoT 2, no. 1 (2021): 33–49. http://dx.doi.org/10.3390/iot2010003.

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The possibility of sensing and predicting the movements of crowds in modern cities is of fundamental importance for improving urban planning, urban mobility, urban safety, and tourism activities. However, it also introduces several challenges at the level of sensing technologies and data analysis. The objective of this survey is to overview: (i) the many potential application areas of crowd sensing and prediction; (ii) the technologies that can be exploited to sense crowd along with their potentials and limitations; (iii) the data analysis techniques that can be effectively used to forecast cr

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Xu, Han, Xiangxia Ren, Weiguo Song, Jun Zhang, and Rayyan Saidahmed. "Spatial and temporal analysis of the bottleneck flow under different walking states with a moving obstacle." Journal of Statistical Mechanics: Theory and Experiment 2023, no. 1 (2023): 013401. http://dx.doi.org/10.1088/1742-5468/aca2a2.

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Abstract The regulation of a moving obstacle on crowd movement offers the possibility to enhance evacuation efficiency in emergency situations. In this paper, a series of controlled experiments are conducted to study the effect of the moving obstacle on crowd dynamics for pedestrians in three different competitive levels, which respectively correspond to three different walking states. The enhancement effects of the moving obstacle on evacuation efficiency for the crowd in the dual-task and high-motivated walking states are confirmed, and the positions of the moving obstacle are crucial. It is

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Xue, Yiran, Peng Liu, Ye Tao, and Xianglong Tang. "Abnormal Prediction of Dense Crowd Videos by a Purpose–Driven Lattice Boltzmann Model." International Journal of Applied Mathematics and Computer Science 27, no. 1 (2017): 181–94. http://dx.doi.org/10.1515/amcs-2017-0013.

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Abstract In the field of intelligent crowd video analysis, the prediction of abnormal events in dense crowds is a well-known and challenging problem. By analysing crowd particle collisions and characteristics of individuals in a crowd to follow the general trend of motion, a purpose-driven lattice Boltzmann model (LBM) is proposed. The collision effect in the proposed method is measured according to the variation in crowd particle numbers in the image nodes; characteristics of the crowd following a general trend are incorporated by adjusting the particle directions. The model predicts dense cr

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Hu, Xinyu, Yifan Ren, Ying Tan, and Yi Shi. "Research on the Spatial and Temporal Dynamics of Crowd Activities in Commercial Streets and Their Relationship with Formats—A Case Study of Lao Men Dong Commercial Street in Nanjing." Sustainability 15, no. 24 (2023): 16838. http://dx.doi.org/10.3390/su152416838.

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Crowd activity is an important indicator of commercial streets’ attractiveness and developmental potential. The development of positioning technologies such as GPS and mobile signal tracking has provided a large amount of trajectory data for studying crowd activities on commercial streets. These data can not only be used for the statistics, extraction, and visualization of crowd information, but they also facilitate the exploration of deeper insights into dynamic behaviors, choices, trajectories, and other details of crowd activities. Based on this, this article proposes a new framework for an

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Muhammed Anees, V., and G. Santhosh Kumar. "Identification of crowd behaviour patterns using stability analysis." Journal of Intelligent & Fuzzy Systems 42, no. 4 (2022): 2829–43. http://dx.doi.org/10.3233/jifs-200667.

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Crowd behaviour analysis and management have become a significant research problem for the last few years because of the substantial growth in the world population and their security requirements. There are numerous unsolved problems like crowd flow modelling and crowd behaviour detection, which are still open in this area, seeking great attention from the research community. Crowd flow modelling is one of such problems, and it is also an integral part of an intelligent surveillance system. Modelling of crowd flow has now become a vital concern in the development of intelligent surveillance sy

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BHUIYAN, MD ROMAN, Dr Junaidi Abdullah, Dr Noramiza Hashim, et al. "Crowd density estimation using deep learning for Hajj pilgrimage video analytics." F1000Research 10 (November 24, 2021): 1190. http://dx.doi.org/10.12688/f1000research.73156.1.

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Background: This paper focuses on advances in crowd control study with an emphasis on high-density crowds, particularly Hajj crowds. Video analysis and visual surveillance have been of increasing importance in order to enhance the safety and security of pilgrimages in Makkah, Saudi Arabia. Hajj is considered to be a particularly distinctive event, with hundreds of thousands of people gathering in a small space, which does not allow a precise analysis of video footage using advanced video and computer vision algorithms. This paper aims to propose an algorithm based on a Convolutional Neural Net

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Liu, L., and S. Zlatanova. "TOWARDS PEDESTRIAN ACCESSIBILITY ANALYSIS IN INDOOR ENVIRONMENTS WITH CROWDS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-1/W2-2023 (December 13, 2023): 657–63. http://dx.doi.org/10.5194/isprs-archives-xlviii-1-w2-2023-657-2023.

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Abstract. Except in emergency cases, indoor crowds could also decrease the walking speed of pedestrians in daily life. To investigate daily-based accessibility of locations to a pedestrian in the presence of crowds, this paper proposes a method of indoor accessibility analysis. We adopt a hierarchical spatial model to represent indoor environments and evaluate the varied accessibility to a user. The first level refers to a door network representing door connectivity. On the second level, spaces are gridified so that crowd density can be readily measured, and its obstruction to pedestrians can

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Polyakova, Yu M. "Human Resource Management Based on Modern Crowd Technologies: Crowd Staffing, Crowd Recruiting and Crowd Training." Scientific Research of Faculty of Economics. Electronic Journal 12, no. 3 (2020): 16–30. http://dx.doi.org/10.38050/2078-3809-2020-12-3-16-30.

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The rapidly changing conditions of the struggle for talented personnel in the context of mass digitalization require a revision of the methods of personnel management in modern organizations. The aim of the study is to determine the role of crowd-technologies in increasing the efficiency of search, selection and development of personnel in Russian organizations, as well as to develop a system of criteria and indicators for assessing the effectiveness of this type technologies. The scientific works of domestic and foreign scientists, reports of international organizations, the Ministry of Econo

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Wang, Qi, Bo Liu, and Jianzhe Lin. "Crowd understanding and analysis." IET Image Processing 15, no. 14 (2021): 3411–13. http://dx.doi.org/10.1049/ipr2.12379.

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Montejo-Ráez, A., M. C. Díaz-Galiano, F. Martínez-Santiago, and L. A. Ureña-López. "Crowd explicit sentiment analysis." Knowledge-Based Systems 69 (October 2014): 134–39. http://dx.doi.org/10.1016/j.knosys.2014.05.007.

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Zhan, Beibei, Dorothy N. Monekosso, Paolo Remagnino, Sergio A. Velastin, and Li-Qun Xu. "Crowd analysis: a survey." Machine Vision and Applications 19, no. 5-6 (2008): 345–57. http://dx.doi.org/10.1007/s00138-008-0132-4.

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Livshits, Benjamin, and Todd Mytkowicz. "Saving Money While Polling with InterPoll Using Power Analysis." Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 2 (September 5, 2014): 159–70. http://dx.doi.org/10.1609/hcomp.v2i1.13168.

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Crowd-sourcing is increasingly being used for providing responses to polls and surveys on a large scale. Companies such as SurveyMonkey and Instant.ly are attempting to make crowd-sourced surveys commonplace, by making it easy to pose survey questions using an easy-to-use UI and retrieve results with a relatively low latency by having dedicated crowds at their disposal. In this paper we argue that the ease with which polls can be created conceals an inherent difficulty: the survey maker does not know how many workers to hire for their survey. Asking too few may lead to samples sizes that `"do

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Alamri, Abdullah. "Cloud of Things in Crowd Engineering: A Tile-Map-Based Method for Intelligent Monitoring of Outdoor Crowd Density." Sensors 22, no. 9 (2022): 3328. http://dx.doi.org/10.3390/s22093328.

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Managing citizen and community safety is one of the most essential services that future cities will require. Crowd analysis and monitoring are also a high priority in the current COVID-19 pandemic scenario, especially because large-scale gatherings can significantly increase the risk of infection transmission. However, crowd tracking presents several complex technical challenges, including accurate people counting and privacy preservation. In this study, using a tile-map-based method, a new intelligent method is proposed which is integrated with the cloud of things and data analytics to provid

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Zhao, Rongyong, Ping Jia, Yan Wang, Cuiling Li, Yunlong Ma, and Zhishu Zhang. "Acceleration-critical density time-delay model for crowd stability analysis based on Lyapunov theory." MATEC Web of Conferences 355 (2022): 03019. http://dx.doi.org/10.1051/matecconf/202235503019.

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Crowd stability analysis is one of research hotspots to alleviate the severe situation of stampede accidents worldwide. Different from the conventional analysis models for crowd stability based on pedestrian density, this study analyses the characteristics of external disturbances and internal obstacle disturbance based on Lyapunov's theory. The critical range of crowd acceleration in crowd evacuation is obtained, a crowd merging acceleration-critical density time delay model is established, and a stability criterion of acceleration vector based on Lyapunov is obtained based on Lyapunov stabil

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CHERNOV, G.YU. "Crowd control: main principles and technological methods." Society and Power, no. 1 (June 5, 2011): 76–79. https://doi.org/10.5281/zenodo.13354528.

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Wong, Vivian W. H., and Kincho H. Law. "Fusion of CCTV Video and Spatial Information for Automated Crowd Congestion Monitoring in Public Urban Spaces." Algorithms 16, no. 3 (2023): 154. http://dx.doi.org/10.3390/a16030154.

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Crowd congestion is one of the main causes of modern public safety issues such as stampedes. Conventional crowd congestion monitoring using closed-circuit television (CCTV) video surveillance relies on manual observation, which is tedious and often error-prone in public urban spaces where crowds are dense, and occlusions are prominent. With the aim of managing crowded spaces safely, this study proposes a framework that combines spatial and temporal information to automatically map the trajectories of individual occupants, as well as to assist in real-time congestion monitoring and prediction.

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Saglietto, Laurence. "Bibliometric analysis of sharing economy logistics and crowd logistics." International Journal of Crowd Science 5, no. 1 (2021): 31–54. http://dx.doi.org/10.1108/ijcs-07-2020-0014.

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Purpose This study aims to review the literature on sharing economy logistics and crowd logistics to answer the three following questions: How is the literature on sharing economy logistics structured? What are the main trends in sharing economy logistics and crowd logistics? What are the future research options? Design/methodology/approach Bibliometric analysis is used to evaluate 85 articles published over the past 12 years; it identifies the top academic journals, authors and research topics contributing to the field. Findings The sharing economy logistics and crowd logistics literature is

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Altowairqi, Sarah, Suhuai Luo, Peter Greer, and Shan Chen. "Efficient Crowd Anomaly Detection Using Sparse Feature Tracking and Neural Network." Applied Sciences 14, no. 9 (2024): 3928. http://dx.doi.org/10.3390/app14093928.

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Crowd anomaly detection is crucial in enhancing surveillance and crowd management. This paper proposes an efficient approach that combines spatial and temporal visual descriptors, sparse feature tracking, and neural networks for efficient crowd anomaly detection. The proposed approach utilises diverse local feature extraction methods, including SIFT, FAST, and AKAZE, with a sparse feature tracking technique to ensure accurate and consistent tracking. Delaunay triangulation is employed to represent the spatial distribution of features in an efficient way. Visual descriptors are categorised into

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Faisel, G. Mohammed, F. Nori Abbas, and N. Thamer Noor. "A Comprehensive Literature Survey for Crowd Scene Analysis techniques." International Journal of Contemporary Research in Multidisciplinary 2, no. 6 (2023): 16–23. https://doi.org/10.5281/zenodo.10407309.

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Understanding how people behave in crowded places is an important endeavor with several uses, like controlling the spread of COVID-19 or other diseases that spread through contact. An in-depth study of crowd scene analysis methods, including both crowd counting and crowd activity detection, is included in this survey article. This article fills the gap by exhaustively examining the spectrum up to contemporary deep learning techniques, whereas current studies frequently focus primarily on certain aspects or traditional approaches. The paper proposes the innovative idea of Crowd Divergence (CD)

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Mladenow, Andreas, Christine Bauer, and Christine Strauss. "“Crowd logistics”: the contribution of social crowds in logistics activities." International Journal of Web Information Systems 12, no. 3 (2016): 379–96. http://dx.doi.org/10.1108/ijwis-04-2016-0020.

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Purpose The paper aims to provide the necessary basis for a novel interdisciplinary research field. Various types and implementations of crowdsourcing have emerged in the market; many of them are related to logistics. While we can identify plenty of crowd logistics applications using information technology capabilities and information sharing in practice, theories behind this phenomenon have received only limited attention. This paper accounts for filling this research gap by analyzing the crowd’s contributions in logistics of goods and information. Design/methodology/approach This paper is pa

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Astriyani, Erna, Oleh Soleh, Adisa Lahmania Putri, and Fachry Riziq Huseini. "Implementation of The YOLOv5 Model For Crowd Detection : Model Analysis." CCIT Journal 17, no. 2 (2024): 138–54. https://doi.org/10.33050/ccit.v17i2.2602.

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One of several deep learning object detection model ideas is YOLO. High-level characteristics obtained by Convolutional Neural Networks (CNN) can be used to overcome the challenges of prior assumptions. Because of the inherent complexity of the human crowd, prominent places in a high-density crowd may exhibit characteristics that differ from those in a normal density crowd. The most efficient deep learning model architecture for use in real-time video applications is provided by YOLO. The CrowdHuman dataset is annotated by researchers using the Roboflow platform. The outcomes are annotated fil

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Korbut, Andrei M. "Social Order and Practical Wisdom of Walking in a Crowd." Sociological Journal 24, no. 4 (2018): 8–29. http://dx.doi.org/10.19181/socjour.2018.24.4.6095.

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The article suggests returning to the “crowd” as an object of sociological analysis. Crowds have attracted early sociologists because crowds were visual embodiments of social forces that surpass individuals and also served as a symbol of the profound social transformations which were taking place in the late 19th and early 20th centuries. Analyzing crowds allowed for the first sociologists (G. Simmel, R. Park, M. Weber, E. Durkheim) to oppose the psychological interpretation of mass social phenomena with a purely sociological approach. However, in the second half of the 20th century sociologis

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Huang, Shaonian, Dongjun Huang, and Mansoor Ahmed Khuhro. "Crowd Motion Analysis Based on Social Force Graph with Streak Flow Attribute." Journal of Electrical and Computer Engineering 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/492051.

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Over the past decades, crowd management has attracted a great deal of attention in the area of video surveillance. Among various tasks of video surveillance analysis, crowd motion analysis is the basis of numerous subsequent applications of surveillance video. In this paper, a novel social force graph with streak flow attribute is proposed to capture the global spatiotemporal changes and the local motion of crowd video. Crowd motion analysis is hereby implemented based on the characteristics of social force graph. First, the streak flow of crowd sequence is extracted to represent the global cr

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Kefan, Xie, Yu Song, Sishi Liu, and Jia Liu. "Analysis of crowd stampede risk mechanism." Kybernetes 48, no. 1 (2019): 124–42. http://dx.doi.org/10.1108/k-11-2017-0415.

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Purpose The purpose of this paper is to analyze the crowd stampede risk mechanism from the perspective of systems thinking. Design/methodology/approach Causal loop diagram is drawn to outline the non-linear interactions among complex factors across the whole system and dissect the contributory factors of crowd stampede accident. To systematically construct the theoretical framework and find fundamental solutions, co-word analysis with Citespace is used to get the critical data. An agent-based simulation using Pathfinder is conducted to develop a spatial model for the Shanghai Stampede Accident

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Ravi Saharan. "Analysis of Crowd using CNN with Physical distance Status." Journal of Information Systems Engineering and Management 10, no. 38s (2025): 41–49. https://doi.org/10.52783/jisem.v10i38s.6820.

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Crowd analysis plays a critical role in public safety, resource allocation, and effective crowd management during large gatherings. This paper presents an enhanced convolutional neural network (CNN)-based model for crowd estimation that incorporates physical distance status, a key parameter for post-pandemic safety requirements. The proposed approach performs crowd density classification and individual count estimation, categorizing crowd levels into four classes based on count and proximity. The model is evaluated on the NWPU-Crowd dataset using standard performance metrics including accuracy

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Sun, Libo, and Norman Badler. "Exploring the Consequences of Crowd Compression Through Physics-Based Simulation." Sensors 18, no. 12 (2018): 4149. http://dx.doi.org/10.3390/s18124149.

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Statistical analysis of accidents in recent years shows that crowd crushes have become significant non-combat, non-environmental public disasters. Unlike common accidents such as fires, crowd crushes may occur without obvious external causes, and may arise quickly and unexpectedly in otherwise normal surroundings. We use physics-based simulations to understand the processes and consequences of compressive forces on high density static crowds consisting of up to 400 agents in a restricted space characterized by barriers to free movement. According to empirical observation and experimentation by

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Li, Zhouxia, Zhiwen Pan, Xiaoni Wang, Wen Ji, and Feng Yang. "Intelligence level analysis for crowd networks based on business entropy." International Journal of Crowd Science 3, no. 3 (2019): 249–66. http://dx.doi.org/10.1108/ijcs-05-2019-0014.

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Purpose Intelligence level of a crowd network is defined as the expected reward of the network when completing the latest tasks (e.g. last N tasks). The purpose of this paper is to improve the intelligence level of a crowd network by optimizing the profession distribution of the crowd network. Design/methodology/approach Based on the concept of information entropy, this paper introduces the concept of business entropy and puts forward several factors affecting business entropy to analyze the relationship between the intelligence level and the profession distribution of the crowd network. This

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