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Hassanein, Hossam, Nizar Zorba, Shuai Han, Salil S. Kanhere, and Mutaz Shukair. "Crowd Management." IEEE Communications Magazine 57, no. 4 (April 2019): 18–19. http://dx.doi.org/10.1109/mcom.2019.8703458.
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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 (October 14, 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 heterogeneous knowledge in form of a variety of knowledge associations, individual crowd members tend to generate solutions that are more novel. In contrast to the brainstorming view that focuses on ideas as knowledge, the authors propose, test, find and elaborate on implications of crowd sharing of heterogeneous knowledge for the generation of innovation, i.e. novel ideas. The authors coded and analyzed all the posts in 20 innovation challenges leveraging online temporary crowds that were structured to foster knowledge sharing as part of the idea generation process. The analysis shows a positive relationship between the variety of knowledge associations contributed by the crowd and the generation of novel solutions by individuals in the crowd. Further, the variety of knowledge associations contributed by the crowd has a stronger relationship with novel solution generation than the number of associations generated by the crowd, i.e. variety of knowledge has a greater impact than either the quantity of knowledge or the number of solution-ideas shared. The authors offer four implications and several future directions for research on the new organizational form of online crowds. Design/methodology/approach The authors coded and analyzed all the posts in 20 innovation challenges. They also designed and ran these challenges in collaboration with corporate sponsors. The ideas in the challenge were rated by senior executive at each company using a creative forecasting method. Findings The variety of knowledge associations contributed by the crowd has a stronger relationship with novel solution generation than the number of associations generated by the crowd, i.e. variety of knowledge has a greater impact than either the quantity of knowledge or the number of solution-ideas shared. Research limitations/implications The authors offer four implications and several future directions for research on the new organizational form of online crowds. Practical implications The authors propose several ways in which companies running innovation challenges can moderate and encourage crowd to generate a variety of knowledge. Originality/value The authors believe that we are the first empirical paper to emphasize and show that associative variety of knowledge sharing in crowds has impact on novel idea generation by crowds. This view is counter to "electronic brainstorming" view where crowd is asked to just generate these ideas and often just submit their ideas to the sponsor. Their view also goes beyond knowledge refinement of ideas by crowds to more of knowledge integration by crowds.
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Premnath, Devi, and Dr C. Nateson Dr. C.Nateson. "Crowd Sourcing A New Management Mantra." Indian Journal of Applied Research 1, no. 5 (October 1, 2011): 136–37. http://dx.doi.org/10.15373/2249555x/feb2012/51.
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Templeton, Anne, John Drury, and Andrew Philippides. "Walking together: behavioural signatures of psychological crowds." Royal Society Open Science 5, no. 7 (July 2018): 180172. http://dx.doi.org/10.1098/rsos.180172.
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Research in crowd psychology has demonstrated key differences between the behaviour of physical crowds where members are in the same place at the same time, and the collective behaviour of psychological crowds where the entire crowd perceive themselves to be part of the same group through a shared social identity. As yet, no research has investigated the behavioural effects that a shared social identity has on crowd movement at a pedestrian level. To investigate the direction and extent to which social identity influences the movement of crowds, 280 trajectories were tracked as participants walked in one of two conditions: (1) a psychological crowd primed to share a social identity; (2) a naturally occurring physical crowd. Behaviour was compared both within and between the conditions. In comparison to the physical crowd, members of the psychological crowd (i) walked slower, (ii) walked further, and (iii) maintained closer proximity. In addition, pedestrians who had to manoeuvre around the psychological crowd behaved differently to pedestrians who had to manoeuvre past the naturally occurring crowd. We conclude that the behavioural differences between physical and psychological crowds must be taken into account when considering crowd behaviour in event safety management and computer models of crowds.
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Thawait, Shiwangi, Akshat Tiwari, Namita Sharma, Babita Bhandari, and Rakesh Patel. "Role of IoT in Crowd Management using Bidirectional Attendance Counter." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (May 31, 2023): 6509–11. http://dx.doi.org/10.22214/ijraset.2023.53265.
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Abstract: Crowd management is one of the most challenging tasks in public spaces like airports, train stations, and stadiums. The advent of the Internet of Things (IoT) has made it possible to automate the crowd management process. Bidirectional attendance counters are IoT devices that can help monitor the number of people entering and leaving a specific location. This paper discusses the role of IoT in crowd management using bidirectional attendance counters. The paper explains the design and working of the bidirectional attendance counter and how it can be used to manage crowds in public spaces.
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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 (September 28, 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 Economic Development of the Russian Federation, companies specializing in crowd-technologies were studied. The work used the methods of induction, comparative analysis, benchmarking of the best foreign and Russian practices of using crow- technologies in the field of HR-management and the method of conceptual and methodological modeling. The research conducted by the author made it possible to identify the socio-economic effects of the use of crowd staffing and crowd recruiting in the field of personnel search and selection, crowd training as a method of training employees, and also to propose a number of criteria and indicators for assessing the effectiveness of using these technologies in order to make effective decisions by management personnel.
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Zhou, Hui, Zhihao Zheng, Xuekai Cen, Zhiren Huang, and Pu Wang. "A Data-Driven Urban Metro Management Approach for Crowd Density Control." Journal of Advanced Transportation 2021 (March 30, 2021): 1–14. http://dx.doi.org/10.1155/2021/6675605.
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Large crowding events in big cities pose great challenges to local governments since crowd disasters may occur when crowd density exceeds the safety threshold. We develop an optimization model to generate the emergent train stop-skipping schemes during large crowding events, which can postpone the arrival of crowds. A two-layer transportation network, which includes a pedestrian network and the urban metro network, is proposed to better simulate the crowd gathering process. Urban smartcard data is used to obtain actual passenger travel demand. The objective function of the developed model minimizes the passengers’ total waiting time cost and travel time cost under the pedestrian density constraint and the crowd density constraint. The developed model is tested in an actual case of large crowding events occurred in Shenzhen, a major southern city of China. The obtained train stop-skipping schemes can effectively maintain crowd density in its safety range.
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Ammon, Rob, and Gil Fried. "Crowd Management Practices." Journal of Convention & Exhibition Management 1, no. 2-3 (June 1999): 119–50. http://dx.doi.org/10.1300/j143v01n02_05.
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Winiarski, Jaroslaw. "Crowd Logistics: Sharing Economy in Supply Chain Management." Socio-Economic Analyses 14, no. 1 (June 30, 2022): 138–48. http://dx.doi.org/10.54664/bczo3563.
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The purpose of this paper is to define crowd logistics, a relatively recent phenomenon in the sharing economy. Despite their increasing popularity, such projects have not been the topic of much research, with only a few pieces addressing the problems. The mission of crowd logistics is to connect market participants who have unique logistical capabilities with those who report logistical needs. This is done to prevent unproductive resource usage and to activate underutilized capabilities. An experimental strategy was used to study solutions used in practice, which was based on a survey of 77 active crowd logistics efforts. These projects are categorized into groups in this article, and the key differences between crowd logistics and regular business logistics are highlighted. Furthermore, efforts are made to ascertain future development directions, as well as the potential influence of crowd logistics on traditional firms. This research is based on an examination of secondary sources, including articles, consulting firm reports, and case studies published in branch publications, company websites, and provided by the firms themselves as part of webinars.
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Husman, Muhammad Afif, Waleed Albattah, Zulkifli Zainal Abidin, Yasir Mohd Mustafah, Kushsairy Kadir, Shabana Habib, Muhammad Islam, and Sheroz Khan. "Unmanned Aerial Vehicles for Crowd Monitoring and Analysis." Electronics 10, no. 23 (November 29, 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 crowd analysis reasons, relieving the relevant authorities of the venues’ inadequacies and of concerns of inaccessible locations and situation. This paper reviews existing literature sources regarding the use of aerial vehicles for crowd monitoring and analysis purposes. Vehicle specifications, onboard sensors, power management, and an analysis algorithm are critically reviewed and discussed. In addition, ethical and privacy issues surrounding the use of this technology are presented.
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Aziz, Muhammad Waqar, Farhan Naeem, Muhammad Hamad Alizai, and Khan Bahadar Khan. "Automated Solutions for Crowd Size Estimation." Social Science Computer Review 36, no. 5 (September 11, 2017): 610–31. http://dx.doi.org/10.1177/0894439317726510.
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The crowd phenomenon frequently occurs in dense urban living environments. Crowd counting or estimation helps to develop management strategies such as designing safe public places and evacuation plan for emergencies. These strategies are different depending upon the type of event such as political and public demonstrations, sports, and religious events. However, estimating the number of people in crowds at closed or open environments is quite challenging because of the dynamics involved in the process. In addition, crowd estimation itself poses challenges due to randomness in crowd behavior, motion, and an area’s geometric specifications. Crowd behavior as well as the area parameters is studied before suggesting any possible technological solution for managing a crowd. This article presents a theoretical understanding of the major crowd size estimation approaches that cannot be achieved through the study of existing survey papers in this area, because the existing survey papers focus on particular technologies/specific areas with no or brief description of the involved steps. Besides, this article also highlights the strength and weakness of crowd size estimation solutions and their possible applications. It is, therefore, believed that the provided information would assist in developing an intelligent system for crowd management.
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Wang, Soon-Joo. "Survey of Crowd Crush Disasters and Countermeasures." Prehospital and Disaster Medicine 38, S1 (May 2023): s78. http://dx.doi.org/10.1017/s1049023x2300225x.
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Introduction:On the night of October 29, 2022, a crowd crush occurred during Halloween festivities in the Itaewon neighborhood of Seoul, Korea. At least 156 people were killed and at least 173 others were injured. In this study, the author tried to learn a lesson by investigating the worldwide crowd crush disaster and analyzing the differences and results.Method:First, the crowd crush disasters were investigated and summarized through literature and internet searches. Second, based on this, the prevention and management of crowd crush disasters, emergency medical response, and necessary research/development contents were derived through a Delphi survey of experts.Results:Crowd crush disasters have been experienced from developed countries to developing countries since the 1800s. Commonly the crowd density was high, and the crowds continued to move and then the crowd collapsed above a certain limit. The biggest casualty occurred during a pilgrimage to Mecca in Saudi Arabia in 2015, but the theme of the event, such as concerts, sporting events, and funerals, was varied. Experts survey was that the manager's efforts not to increase the crowd density, and efforts to maintain order and prevent contingencies were important. They said that it is important to comply with the principles of disaster medicine, but it is difficult to access the patient in the crowd crush state, so the management of the crowd may be more important. They said that it is necessary to establish a realistic guideline and a real-time crowd density monitoring system using CCTV or drones.Conclusion:Crowd crush disasters can occur in any type of crowd gathering events where the crowd density increases, and prevention through crowd management and real-time crowd density monitoring should be implemented.
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Aiello, Lucia. "Digital Skill Evolution in an Industrial Relationship." International Journal of R&D Innovation Strategy 1, no. 1 (January 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 tutor is examined based on the middle-of-the-road theoretical positioned from Porter and Kramer, the value creation, and Suermann and Franzoni, the crows science user contribution patterns. The recently evolution of crowd platforms considers the interaction between companies and crowds based on a “Community of Practice” model of Zucchermaglio and Talamo. Value analysis also considers the differences in roles and tasks in relation to where crowd activity is placed into the value chain of company. In crowdsourcing, “digital people” live in a digital society where every individual has a role and operates in an online community, and those have force points and weakness points. The tutor cans also monitor these points, and push interaction and activities of the crowd. The main theoretical contribution is the looking gap in literature and contributing work to this. Through a qualitative analysis, this article provides evidence of the main activities and the role of digital tutors in an online community. The method utilized is netnography through an online participation and observation of a researcher. In this work, professional figures and new technologies are weighed, and human resource management must consider this as it creates value. This article concludes that a tutor of crowds has a positive behavior, they can stimulate crowds. These positive and active behaviors effect crowd attitudes about the benefits of the community, their expectations, and opinions all of which are fundamental for the growth of online community.
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Powell, Walter W. "A sociologist looks at crowds: Innovation or invention?" Strategic Organization 15, no. 2 (April 27, 2016): 289–97. http://dx.doi.org/10.1177/1476127016644642.
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Crowd-based organizational models are purported to be more open and participatory than traditional organizational forms. But are they novel inventions or permutations of forms that have existed previously? This essay examines the wide array of innovations pursued under the umbrella label of crowd phenomena and asks whether they have altered traditional ways of organizing. The ramifications of crowds for both workers and consumers are also discussed. Central features of crowd organizing include spot transactions, short-term relations, demand-based pricing, heterogeneous demand, and reputations established through feedback mechanisms. Security and formality appear to have been replaced by openness and precariousness. The essay concludes with a call for further study of the contents of crowd-generated products and services.
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Hassan, Rasha, and Yasser Ibrahim. "An adaptive media strategy for influencing crowd behaviour." Journal of Humanities and Applied Social Sciences 2, no. 1 (November 21, 2019): 56–76. http://dx.doi.org/10.1108/jhass-07-2019-0013.
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Purpose Media has always been used as a key manipulator of public agendas, political beliefs and individuals’ attitudes. The purpose of this study is to investigate the impact of three adaptive media strategies on the pattern and dynamics of potential crowds. Design/methodology/approach An agent-based approach is used to simulate the three adaptive media strategies on the pattern and dynamics of potential crowds. During the experiments, the media broadcast is intensified to gather momentum for crowd movements or is lessened to maintain the budget. Findings The results show that a slight change in the media management strategy could lead to a radical different impact on the crowd dynamics. The results also show that a quite smart media strategy could outperform a strategy with an unlimited budget. Finally, the structure of the society shows a significant influence on the crowd dynamics than it could be inferred. Originality/value The model presents an explanatory toolkit for the crowd complexity. The results provide deep insights into the crowd formation and a basis for understanding the influence of media and the impact of its strategies on the crowd dynamics.
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Borch, Christian. "Crowd theory and the management of crowds: A controversial relationship." Current Sociology 61, no. 5-6 (July 11, 2013): 584–601. http://dx.doi.org/10.1177/0011392113486443.
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Radianti, Jaziar, Ole-Christoffer Granmo, Noureddine Bouhmala, Parvaneh Sarshar, and Jose J. Gonzalez. "Comparing Different Crowd Emergency Evacuation Models Based on Human Centered Sensing Criteria." International Journal of Information Systems for Crisis Response and Management 6, no. 3 (July 2014): 53–70. http://dx.doi.org/10.4018/ijiscram.2014070104.
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Emergency evacuation of crowds is a fascinating phenomenon that has attracted researchers from various fields. Better understanding of this class of crowd behavior opens up for improving evacuation policies and smarter design of buildings, increasing safety. Recently, a new class of disruptive technology has appeared: Human-centered sensing which allows crowd behavior to be monitored in real-time, and provides the basis for real-time crowd control. The question then becomes: to what degree can previous crowd models incorporate this development, and what areas need further research? In this paper, the authors provide a survey that describes some widely used crowd models and discuss the advantages and shortages from the angle of human-centered sensing. Their review reveals important research opportunities that may contribute to an improved and more robust emergency management.
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Sun, Yao, Philipp Tuertscher, Ann Majchrzak, and Arvind Malhotra. "Pro-socially motivated interaction for knowledge integration in crowd-based open innovation." Journal of Knowledge Management 24, no. 9 (August 24, 2020): 2127–47. http://dx.doi.org/10.1108/jkm-04-2020-0303.
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Purpose The purpose of this paper is to study how the online temporary crowd shares knowledge in a way that fosters the integration of their diverse knowledge. Having the crowd integrate its knowledge to offer solution-ideas to ill-structured problems posed by organizations is one of the desired outcomes of crowd-based open innovation because, by integrating others’ knowledge, the ideas are more likely to consider the many divergent issues related to solving the ill-structured problem. Unfortunately, the diversity of knowledge content offered by heterogeneous specialists in the online temporary crowd makes integration difficult, and the lean social context of the crowd makes extensive dialogue to resolve integration issues impractical. The authors address this issue by exploring theoretically how the manner in which interaction is organically conducted during open innovation challenges enables the generation of integrative ideas. The authors hypothesize that, as online crowds organically share knowledge based upon successful pro-socially motivated interaction, they become more productive in generating integrative ideas. Design/methodology/approach Using a multilevel mixed-effects model, this paper analyzed 2,244 posts embedded in 747 threads with 214 integrative ideas taken from 10 open innovation challenges. Findings Integrative ideas were more likely to occur after pro-socially motivated interactions. Research limitations/implications Ideas that integrate knowledge about the variety of issues that relate to solving an ill-structured problem are desired outcomes of crowd-based open innovation challenges. Given that members of the crowd in open innovation challenges rarely engage in dialogue, a new theory is needed to explain why integrative ideas emerge at all. The authors’ adaptation of pro-social motivation interaction theory helps to provide such a theoretical explanation. Practitioners of crowd-based open innovation should endeavor to implement systems that encourage the crowd members to maintain a high level of activeness in pro-socially motivated interaction to ensure that their knowledge is integrated as solutions are generated. Originality/value The present study extends the crowd-based open innovation literature by identifying new forms of social interaction that foster more integrated ideas from the crowd, suggesting the mitigating role of pro-socially motivated interaction in the negative relationship between knowledge diversity and knowledge integration. This study fills in the research gap in knowledge management research describing a need for conceptual frameworks explaining how to manage the increasing complexity of knowledge in the context of crowd-based collaboration for innovation.
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Jitendra Trivedi , Dr. Hina Khan, Jitendra Trivedi ,. Dr Hina Khan. "The Function of Statement in Crowd Management and Crowd Control." International Journal of Business Management & Research 9, no. 4 (2019): 1–8. http://dx.doi.org/10.24247/ijbmraug20191.
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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 (April 26, 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 provide intelligent monitoring of outdoor crowd density. The proposed system can detect and intelligently analyze the pattern of crowd activity to implement contingency plans, reducing accidents, ensuring public safety, and establishing a smart city. The experimental results demonstrate the feasibility of the proposed model in detecting crowd density status in real-time. It can effectively assist with crowd management tasks such as monitoring, guiding, and managing crowds to ensure safety. In addition, the proposed algorithm provides acceptable performance.
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Jadhav, Sayali. "Implementation on- Crowd Wisdom Management." International Journal for Research in Applied Science and Engineering Technology V, no. IV (March 25, 2017): 91–92. http://dx.doi.org/10.22214/ijraset.2017.4016.
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Sapkal , Pankaj Subhash. "CROWD MANAGEMENT SYSTEM USING IOT." International Journal of Advance Scientific Research and Engineering Trends 5, no. 12 (December 15, 2020): 38–47. http://dx.doi.org/10.51319/2456-0774.2020.0002.
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Haas, Daniel, and Michael Franklin. "Cioppino: Multi-Tenant Crowd Management." Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 5 (September 21, 2017): 41–50. http://dx.doi.org/10.1609/hcomp.v5i1.13298.
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Embedding human computation in systems for data analysis improves the quality of the analysis, but can significantly impact the end-to-end cost and performance of the system. Recent work in crowdsourcing systems attempts to optimize for performance, but focuses on single applications running homogeneous tasks. In this work, we introduce Cioppino, a system that accounts for human factors that can affect performance when running multiple applications in parallel. Cioppino uses a queueing model to represent the pool of workers, and leverages techniques for autoscaling used in cloud computing to adaptively adjust the pool size. Its model also accounts for worker abandonment, and automatically shifts workers between applications to improve performance and match workers with tasks they enjoy most. Our evaluation of Cioppino in simulation on traces extracted from a realtime crowd system running on Amazon’s Mechanical Turk demonstrates a 19X reduction in cost, a 20% increase in throughput, and a 2X increase in worker preference for assigned tasks as compared to state-of-the-art crowd management strategies.
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Moore, Tony. "Crowd Management: Learning from History." Police Journal: Theory, Practice and Principles 65, no. 2 (April 1992): 99–108. http://dx.doi.org/10.1177/0032258x9206500203.
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Major, Mark David, Alan Penn, Georgia Spiliopoulou, Natasa Spende, Maria Doxa, and Polly Fong. "Following the crowd: spatial layout and crowd behaviour." Architectural Research Quarterly 4, no. 3 (September 2000): 257–64. http://dx.doi.org/10.1017/s1359135500000282.
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In preparation for the Millennium Eve celebrations, a study was undertaken to predict crowd movement. The objectives were: to identify characteristics of crowd movement and congregation, and how this might be related to spatial layout; to evaluate, in consultation with risk management experts, how this might affect public safety; and to help develop and prepare effective crowd management measures. The study demonstrates how the observational techniques of space syntax have evolved to enable the investigation of the effect, if any, of spatial layout on crowd behaviour.
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Donya Abdel-Aziz Ayyad, Donya Abdel-Aziz Ayyad. "The Role of E-Management in Improving the Crowd Management from the Perspective of the Employees in the Hajj and Umrah System: دور الإدارة الإلكترونية في تحسين إدارة الحشود من وجهة نظر العاملين في منظومة الحج والعمرة." مجلة العلوم الإقتصادية و الإدارية و القانونية 6, no. 6 (February 28, 2022): 116–48. http://dx.doi.org/10.26389/ajsrp.n140721.
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This descriptive study aimed to identify the role of the e-management at improving the crowd management of the Hajj Operations: e-planning, e-organizing, e-guidance, and e-monitoring) from the perspective of the employees in the Hajj. The study included (n = 250) of the employees in the Hajj and the Rahman guests who responded to the survey. The findings indicated that the practice of e-administration by the employees in the Hajj was high. The electronic crowd monitoring appeared with the highest average of (3.62). The degree of e-administration improvement for the crowd management, was high, with average (4.40). The part of electronic organizing in crowd management was found to be the highest, with an average of (4.43). Moreover, the study showed a statistically significant correlation between the degree of employees' practices of the Hajj, the e-administration, and all the areas of improvement in the crowd managements, at the level of significance (α ≤ 0.01). Finally, the satisfaction level of the Rahman guests about the crowd management was significantly high, with average (4.33). The study suggested increasing the attending of the technical courses for the employees in the Hajj, and providing free internet in the holy sites during the seasons of Hajj. Moreover, the study recommended conducting a study on the application of e-administration in the field of Umrah, and conducting a study on crowd management in the Prophet's Mosque in Madinah.
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Abalkhail, Asma Abdulaziz Abdullah, and Sumiah Mashraf Abdullah Al Amri. "Saudi Arabia’s Management of the Hajj Season through Artificial Intelligence and Sustainability." Sustainability 14, no. 21 (October 29, 2022): 14142. http://dx.doi.org/10.3390/su142114142.
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High-density gatherings have the potential to turn from a peaceful mass into a human disaster unless they are managed in an organized manner. Saudi Arabia’s Ministry of Hajj implemented an integrated system based on artificial intelligence. The Kingdom of Saudi Arabia (KSA) was eager to take advantage of the techniques of artificial intelligence to conduct its strategic plan, considering limited pilgrims who would be allowed to perform the Hajj rites during these exceptional circumstances. In this study, the experience of the KSA in crowd management using artificial intelligence during the Hajj was examined to create a model for similar circumstances. This study employed the descriptive analytical method. The program Arc Gis Pro 2.9.2 was used to produce maps related to the study. A strategic analysis was also conducted regarding the experience of the KSA in crowd management using SWOT analysis concerning the study area. This study found that the KSA has become a leader in crowd management and a reference and role model in managing crowds through an expanded use of artificial intelligence during the COVID-19 pandemic. It undertook all necessary precautionary measures to protect the pilgrims, and no injuries were reported.
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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 (May 4, 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 error of 184 people could be obtained for a large scale environment which contained 3227 people at its peak. Additionally, we look into the potential benefits of dividing one of our experimental environments into multiple subregions and open up a potentially interesting new topic of research regarding the estimation of crowd flows. Finally, we investigate the combination of our measurements with another sources of crowd-related data: sales data from drink stands within the environment. In doing so, we aim to integrate the concept of an automatic RF-based crowd estimation system into the broader domain of crowd analysis.
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Barbosu, Sandra, and Joshua S. Gans. "Storm crowds: Evidence from Zooniverse on crowd contribution design." Research Policy 51, no. 1 (January 2022): 104414. http://dx.doi.org/10.1016/j.respol.2021.104414.
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Hutton, Alison, Kathryn Zeitz, Steve Brown, and Paul Arbon. "Assessing the Psychosocial Elements of Crowds at Mass Gatherings." Prehospital and Disaster Medicine 26, no. 6 (December 2011): 414–21. http://dx.doi.org/10.1017/s1049023x12000155.
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AbstractIntroduction: The environmental aspects of mass gatherings that can affect the health and safety of the crowd have been well described. Although it has been recognized that the nature of the crowd will directly impact the health and safety of the crowd, the majority of research focuses on crowd behavior in a negative context such as violence or conflict. Within the mass gathering literature, there is no agreement on what crowd behavior, crowd mood and crowd type actually mean. At the same time, these elements have a number of applications, including event management and mass gathering medicine. These questions are worthy of exploration.Methods: This paper will report on a pilot project undertaken to evaluate how effective current crowd assessment tools are in understanding the psychosocial domain of a mass gathering event.Results: The pilot project highlighted the need for a more consistent descriptive data set that focuses on crowd behavior.Conclusions: The descriptive data collected in this study provide a beginning insight into the science of understanding crowds at a mass gathering event. This pilot has commenced a process of quantifying the psychosocial nature of an event. To maximize the value of this work, future research is required to understand the interplay among the three domains of mass gatherings (physical, environmental and psychological), along with the effects of each element within the domains on safety and health outcomes for participants at mass gatherings.
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Lauto, Giancarlo, and Finn Valentin. "How preference markets assist new product idea screening." Industrial Management & Data Systems 116, no. 3 (April 11, 2016): 603–19. http://dx.doi.org/10.1108/imds-07-2015-0320.
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Purpose – The purpose of this paper is to examine the different heuristics adopted by a crowd and a management committee to evaluate new product proposals, and whether, in assessing the value of proposals, they emphasize different features. Design/methodology/approach – The study takes a quantitative analysis approach to study an internal innovation contest held by the biotechnology company Novozymes. The contest generated 201 proposals that were evaluated by 109 research and development professionals by means of a virtual preference market, and by a management committee. Findings – The crowd and the committees’ assessments of the value of the proposals were based on different features. The committee emphasized experience and inventors’ seniority; the crowd set more store on informative idea descriptions but penalized overly complex and lengthy proposals. Research limitations/implications – The design of the innovation contest does not allow full comparison of the preference functions of crowd and committee. The findings from this case study cannot be generalized. The early stage of new product development seems fruitful for investigating crowdsourcing and knowledge management. Practical implications – Firms should consider adopting preference markets for idea screening and evaluation since they appraise ideas from different angles compared to managers. However, they complement, rather than substitute managerial evaluation, especially in the case of more detailed proposals. Originality/value – This is one of the first attempts to identify differences in the decision-making processes of crowds and committees. The paper identifies their strengths as evaluators of new product ideas and finds that the “wisdom of crowds” has some limitations in relation to the ability to process complex information.
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Zhang, Jin, Sheng Chen, Sen Tian, Wenan Gong, Guoshan Cai, and Ying Wang. "A Crowd Counting Framework Combining with Crowd Location." Journal of Advanced Transportation 2021 (February 17, 2021): 1–14. http://dx.doi.org/10.1155/2021/6664281.
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In the past ten years, crowd detection and counting have been applied in many fields such as station crowd statistics, urban safety prevention, and people flow statistics. However, obtaining accurate positions and improving the performance of crowd counting in dense scenes still face challenges, and it is worthwhile devoting much effort to this. In this paper, a new framework is proposed to resolve the problem. The proposed framework includes two parts. The first part is a fully convolutional neural network (CNN) consisting of backend and upsampling. In the first part, backend uses the residual network (ResNet) to encode the features of the input picture, and upsampling uses the deconvolution layer to decode the feature information. The first part processes the input image, and the processed image is input to the second part. The second part is a peak confidence map (PCM), which is proposed based on an improvement over the density map (DM). Compared with DM, PCM can not only solve the problem of crowd counting but also accurately predict the location of the person. The experimental results on several datasets (Beijing-BRT, Mall, Shanghai Tech, and UCF_CC_50 datasets) show that the proposed framework can achieve higher crowd counting performance in dense scenarios and can accurately predict the location of crowds.
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Bain, Nicolas, and Denis Bartolo. "Dynamic response and hydrodynamics of polarized crowds." Science 363, no. 6422 (January 3, 2019): 46–49. http://dx.doi.org/10.1126/science.aat9891.
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Modeling crowd motion is central to situations as diverse as risk prevention in mass events and visual effects rendering in the motion picture industry. The difficulty of performing quantitative measurements in model experiments has limited our ability to model pedestrian flows. We use tens of thousands of road-race participants in starting corrals to elucidate the flowing behavior of polarized crowds by probing its response to boundary motion. We establish that speed information propagates over system-spanning scales through polarized crowds, whereas orientational fluctuations are locally suppressed. Building on these observations, we lay out a hydrodynamic theory of polarized crowds and demonstrate its predictive power. We expect this description of human groups as active continua to provide quantitative guidelines for crowd management.
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Moon, Junseob. "A Study on Crowd Management and Crowd Control and Crowd Behavior in Multi-crowd Gathering Events - Based on Literature Research -." Korean Police Studies Review 21, no. 4 (December 31, 2022): 53–74. http://dx.doi.org/10.38084/2022.21.4.3.
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Suteddy, Wirmanto, Dastin Aryo Atmanto, Rizki Nuriman, and Afila Ansori. "PROTOTYPE APPLICATION OF CROWD DETECTION SYSTEM FOR TRADITIONAL MARKET VISITOR BASED ON IOT USING RFID MFRC522." Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) 7, no. 1 (April 30, 2022): 23–30. http://dx.doi.org/10.20527/jtiulm.v7i1.117.
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Crowds of people are the government's concern in dealing with the COVID-19 pandemic because the virus transfers unwittingly from one person to another and transmits it to the closest environment. One of the locations where crowds are difficult to avoid is a traditional market and is thought to be one of the places that have the potential to become the center of the spread of COVID-19. Various efforts made by the government in suppressing crowds have yielded results, but not a few violations that occur are carried out intentionally or unintentionally, one of the efforts to prevent crowd violations is the traditional market visitor detection monitoring system by market management so that market visitors do not violate health protocols and crowds that occur in an area can be avoided. In this study, an IoT-based crowd detection system application prototype uses an RFID sensor MFRC522 as a crowd indicator based on data on the number of visitors entering a kiosk that is recorded in the database and then displayed on the application, this data becomes an indicator of which kiosk other visitors want to go to so that the crowd can be avoided. System functionality testing was carried out with 4 scenarios and system reliability testing through data transmission was carried out 10 times with test data in the form of kiosk id and visitor id sent via a single Transmission Control Protocol (TCP) with a full-duplex communication channel. The test results show that crowd indications can be detected in the application with data transmission speeds reaching 875 KB/s with an average delay of 231.4 ms and a standard deviation of 215 ± 313 ms.
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Meng, Xiaolong. "SENetCount: An Optimized Encoder-Decoder Architecture with Squeeze-and-Excitation for Crowd Counting." Wireless Communications and Mobile Computing 2022 (June 20, 2022): 1–13. http://dx.doi.org/10.1155/2022/2964683.
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Crowd management is critical to preventing stampedes and directing crowds, especially in India and China, where there are more than one billion people. With the continuous growth of the population, crowded events caused by rallies, parades, tourism, and other reasons occur from time to time. Crowd count estimation is the linchpin of the crowd management system and has become an increasingly important task and challenging research direction. This work proposes an optimized encoder-decoder architecture with the squeeze-and-excitation block for crowd counting, called SENetCount, which includes SE-ResNetCount and SE-ResNeXtCount. The deeper and stronger backbone network increases the quality of feature representations. The squeeze-and-excitation block utilizes global information to impress worthy informative feature representations and suppress unworthy ones selectively. The encoder-decoder architecture with the dense atrous spatial pyramid pooling module recovers the spatial information and captures the contextual information at multiple scales. The modified loss function considers the local consistency measure compared with the foregoing Euclidean loss function. The experiments on challenging datasets prove that our approach is competitive compared to thoughtful approaches, and analyses show that our architecture is extensible and robust.
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Still, Keith, Marina Papalexi, Yiyi Fan, and David Bamford. "Place crowd safety, crowd science? Case studies and application." Journal of Place Management and Development 13, no. 4 (April 15, 2020): 385–407. http://dx.doi.org/10.1108/jpmd-10-2019-0090.
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Purpose This paper aims to explore the development and application of place crowd safety management tools for areas of public assembly and major events, from a practitioner perspective. Design/methodology/approach The crowd safety risk assessment model is known as design, information, management-ingress, circulation, egress (DIM-ICE) (Still, 2009) is implemented to optimise crowd safety and potentially throughput. Three contrasting case studies represent examples of some of the world’s largest and most challenging crowd safety projects. Findings The paper provides some insight into how the DIM-ICE model can be used to aid strategic planning at major events, assess potential crowd risks and to avoid potential crowd safety issues. Practical implications It provides further clarity to what effective place management practice is. Evidence-based on the case studies demonstrates that the application of the DIM-ICE model is useful for recognising potential place crowd safety issues and identifying areas for require improvement. Originality/value Crowd science is an emerging field of research, which is primarily motivated by place crowd safety issues in congested places; the application and reporting of an evidence-based model (i.e. DIM-ICE model) add to this. The paper addresses a research gap related to the implementation of analytic tools in characterising place crowd dynamics.
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Guo, Hui, Ying-Hua Song, Wei Lv, Xin-Yao Guo, and Zhi-Wu Lei. "Study on Critical Density of Percolation in Crowds in Public Areas." International Journal of Pattern Recognition and Artificial Intelligence 34, no. 13 (April 30, 2020): 2059044. http://dx.doi.org/10.1142/s0218001420590442.
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The percolation model is an effective tool to solve the problem of fluid flow in the pores; the situation of outsiders crossing the crowd is similar. This paper verifies the obvious percolation phenomenon in the randomly distributed crowd by [Formula: see text] simulation and reveals several characteristics and laws of the crowd percolation phenomena. Studies have shown that sites with different spatial dimensions have different densities of crowd percolation: when the actual density of the crowd is greater than the critical density of the crowd percolation, the outsider is difficult to pass through the crowd; otherwise, the outsider can pass through the crowd easily. Therefore, the critical density of crowd percolation can be one of the indicators of crowd management in public areas, which will provide important guidance for the design of public areas, site selection of public activities and crowd management.
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Shalash, Wafaa M., Aliaa Al Hazimi, and Basma Al Zahrani. "A Mobile Based Crowd Management System." IJARCCE 6, no. 6 (June 30, 2017): 205–15. http://dx.doi.org/10.17148/ijarcce.2017.6638.
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Sefu, Bikorimana, Manirakiza Jean Felix, Ntihinyurwa Jean Bosco, Tuyisenge Jean Claude, Mugabe Jean Paul, Kanyarwanda Daniel, and Kwizera Fidele. "Passengers Crowd Management System in Kigali." Academic Society for Appropriate Technology 8, no. 1 (April 20, 2022): 10–16. http://dx.doi.org/10.37675/jat.2022.8.1.10.
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A safe and effective transportation system is a key factor for national development. To achieve sustainable development goals, technology needs to be used in transportation sector. The authors noticed that the country economy is affected by some factors such as the time wasted by passengers on long queue waiting for the bus to come. Also, the mass gathering contribute in a rapid spread of COVID-19 among passengers. In this study, an effective system for booking bus ticket and tracking bus location was developed. The system uses web- based application that allows the user to check the bus availability, its location and pay ticket on line. The system was developed using ESP8266 a WiFi based microcontroller to provide communication between bus officials and clients, GPS for tracking bus location, LCD for displaying the availability of passengers on a particular bus station, bus official application for receiving the client request and client application for service request and make a follow up. The study was achieved by presenting system circuit diagram and process flow chart. Also, implementation of a physical prototype linked with developed web applications was done. The system enables passenger to easily track the bus location in its real time position, to save time for manual reservation of bus ticket. The passenger crowd management system (PCMS) is secured and can be used by administrator (companies) of buses due to its efficiency in monitoring both buses and passengers.
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Kingshott, Brian F. "Crowd Management: Understanding Attitudes and Behaviors." Journal of Applied Security Research 9, no. 3 (July 3, 2014): 273–89. http://dx.doi.org/10.1080/19361610.2014.913229.
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Pin, Soo Chin, Fazilah Haron, Siamak Sarmady, Abdullah Zawawi Talib, and Ahamad Tajudin Khader. "Applying TRIZ principles in crowd management." Safety Science 49, no. 2 (February 2011): 286–91. http://dx.doi.org/10.1016/j.ssci.2010.09.002.
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Tian, Boquan, Yongbo Yuan, Hengyu Zhou, and Zhen Yang. "Pavement Management Utilizing Mobile Crowd Sensing." Advances in Civil Engineering 2020 (June 23, 2020): 1–16. http://dx.doi.org/10.1155/2020/4192602.
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Pavement management, which is vital in road transportation and maintenance, is facing some troubles, such as high costs of labors and machineries, low detecting efficiency, and low update rate of pavement conditions by means of traditional detection ways. Benefiting from the development of mobile communication, mobile computing, and mobile sensing techniques, the intelligence of mobile crowd sensing (MCS), which mainly relies on ubiquitous mobile smart devices in people’s daily lives, has overcome the above drawbacks to a large extent as one new effective and simple measure for pavement management. As a platform for data collection, processing, and visualization, a common smart device can utilize inertial sensor data, photos, videos, subjective reports, and location information to involve the public in pavement anomalies detection. This paper systematically reviewed the studies in this field from 2008 to 2018 to establish an overall knowledge. Through literature collection and screening, a database of studies was set up for analysis. As a result, the year profile of publications and distribution of research areas indicate that there has been a constant attention from researchers in various disciplines. Meanwhile, the distribution of research topic shows that inertial sensors embedded in smartphones have been the most popular data source. Therefore, the process of pavement anomalies detection based on inertial data was reviewed in detail, including preparatory, data collection, and processing phases of the previous experiments. However, some of the key issues in the experimental phases were investigated by previous studies, while some other challenges were not tackled or noticed. Hence, the challenges in both experiment and implementation stages were discussed to improve the studies and practice. Furthermore, several directions for future research are summarized from the main issues and challenges to offer potential opportunities for more relevant research studies and applications in pavement management.
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Zhang, Ying, Farhad Ali, Kunhao Wang, Shah Nazir, and Zeqi Leng. "Utilizing Virtual Crowd for Global Software Development." Scientific Programming 2021 (July 15, 2021): 1–9. http://dx.doi.org/10.1155/2021/2259594.
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Software firms are interested in outsourcing and developing of software globally to the virtual crowd for minimizing the product cost and for increasing the software quality. Developments in information technology (IT) have changed the organizational working environment from centralized to disperse development working practices. As a result, companies have recognized the value of virtual world networks that offer benefits such as efficient time management, lower cost of growth, reduced travel costs, and access to larger competent team members to select the right skilled individual. With the wide spread of Web 3.0 applications and improvements in cloud computation technologies, multinational, multiskilled, and diverse crowds carry out the software developmental process. The aim of this research is to select the effective virtual crowd for the development of quality software. The proposed “characteristic-based virtual crowd selection (CBVCS)” method will select the crowd according to their unique characteristics such as their skills, experiences, expertise, and knowledge.
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Gong, Vincent X., Winnie Daamen, Alessandro Bozzon, and Serge P. Hoogendoorn. "Crowd characterization for crowd management using social media data in city events." Travel Behaviour and Society 20 (July 2020): 192–212. http://dx.doi.org/10.1016/j.tbs.2020.03.011.
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Abbas, Tahir, Vassilis-Javed Khan, Ujwal Gadiraju, Emilia Barakova, and Panos Markopoulos. "Crowd of Oz: A Crowd-Powered Social Robotics System for Stress Management." Sensors 20, no. 2 (January 20, 2020): 569. http://dx.doi.org/10.3390/s20020569.
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Coping with stress is crucial for a healthy lifestyle. In the past, a great deal of research has been conducted to use socially assistive robots as a therapy to alleviate stress and anxiety related problems. However, building a fully autonomous social robot which can deliver psycho-therapeutic solutions is a very challenging endeavor due to limitations in artificial intelligence (AI). To overcome AI’s limitations, researchers have previously introduced crowdsourcing-based teleoperation methods, which summon the crowd’s input to control a robot’s functions. However, in the context of robotics, such methods have only been used to support the object manipulation, navigational, and training tasks. It is not yet known how to leverage real-time crowdsourcing (RTC) to process complex therapeutic conversational tasks for social robotics. To fill this gap, we developed Crowd of Oz (CoZ), an open-source system that allows Softbank’s Pepper robot to support such conversational tasks. To demonstrate the potential implications of this crowd-powered approach, we investigated how effectively, crowd workers recruited in real-time can teleoperate the robot’s speech, in situations when the robot needs to act as a life coach. We systematically varied the number of workers who simultaneously handle the speech of the robot (N = 1, 2, 4, 8) and investigated the concomitant effects for enabling RTC for social robotics. Additionally, we present Pavilion, a novel and open-source algorithm for managing the workers’ queue so that a required number of workers are engaged or waiting. Based on our findings, we discuss salient parameters that such crowd-powered systems must adhere to, so as to enhance their performance in response latency and dialogue quality.
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Nafea, Ibtehal Talal. "Simulation of crowd management using deep learning algorithm." International Journal of Web Information Systems 17, no. 4 (July 8, 2021): 321–32. http://dx.doi.org/10.1108/ijwis-04-2021-0045.
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Purpose This study aims to propose a new simulation approach for a real-life large and complex crowd management which takes into account deep learning algorithm. Moreover, the proposed model also determines the crowd level and also sends an alarm to avoid the crowd from exceeding its limit. Also, the model estimates crowd density in the pictures through which the study evaluates the deep learning algorithm approach to address the problem of crowd congestion. Furthermore, the suggested model comprises of two main components. The first takes the images of the moving crowd and classifies them into five categories such as “heavily crowded, crowded, semi-crowded, light crowded and normal,” whereas the second one comprises of colour warnings (five). The colour of these lights depends upon the results of the process of classification. The paper is structured as follows. Section 2 describes the theoretical background; Section 3 suggests the proposed approach followed by convolutional neural network (CNN) algorithm in Section 4. Sections 5 and 6 explain the data set and parameters as well as modelling network. Experiment, results and simulation evaluation are explained in Sections 7 and 8. Finally, this paper ends with conclusion which is Section 9 of this paper. Design/methodology/approach This paper addresses the issue of large-scale crowd management by exploiting the techniques and algorithms of simulation and deep learning. It focuses on a real-life case study of Hajj pilgrimage in Saudi Arabia that exhibits intricate pattern of crowd management. Hajj pilgrimage includes performing Umrah along with hajj that involves several steps which is a sacred prayer of Muslims performed at different time span of the year. Muslims from all over the world visit the holy city of Mecca to perform Tawaf that is one of the stages included in the performance of Hajj or Umrah, it is an obligatory step in prayer. Accordingly, all pilgrims require visiting Mataf to perform Tawaf. It is essential to control the crowd performing Tawaf systematically in a constrained place to avoid any mishap. This study proposed a model for crowd management system by using image classification and a system of alarm to manage millions of people during Hajj. This proposed system highly depends on the adequate data set used to train CNN which is a deep learning technique and has recently drawn the attention of the research community as well as the industry in changing applications of image classification and the recognition of speed. The purpose is to train the model with mapped image data, making it available to be used in classifying the crowd into five categories like crowded, heavily crowded, semi-crowded, normal and light-crowded. The results produce adequate signals as they prove to be helpful in terms of monitoring the pilgrims which shows its usefulness. Findings After the first attempt of adding the first convolutional layer with 32 filters, the accuracy is not good and stands out at about 55%. Therefore, the algorithm is further improved by adding the second layer with 64 filters. This attempt is a success as it gives more improved results with an accuracy of 97%. After using the dropout fraction as a 0.5 to prevent overfitting, the test and training accuracy of 98% is achieved which is acceptable training and testing accuracy. Originality/value This study has proposed a model to solve the problem related to estimation of the level of congestion to avoid any accidents from happening because of it. This can be applied to the monitoring schemes that are used during Hajj, especially in crowd management during Tawaf. The model works as such that it activates an alarm when the default crowd limit exceeds. In this way, chances of the crowd reaching a dangerous level are reduced which minimizes the potential accidents that might take place. The model has a traffic light system, the appearance of red light means that the number of pilgrims in a particular area has exceeded its default limit and then it alerts to stop the migration of people to that particular area. The yellow light indicates that the number of pilgrims entering and leaving a particular area has equalized, then the pilgrims are suggested to slower their pace. Finally, the green light shows that the level of the crowd in a particular area is low and that the pilgrims can move freely in that area. The proposed model is simple and user friendly as it uses the most common traffic light system which makes it easier for the pilgrims to understand and follow accordingly.
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Jabbari, Abdoh, Khalid Almalki, Baek-Young Choi, and Sejun Song. "ICE-MoCha: Intelligent Crowd Engineering using Mobility Characterization and Analytics." Sensors 19, no. 5 (February 28, 2019): 1025. http://dx.doi.org/10.3390/s19051025.
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Human injuries and casualties at entertaining, religious, or political crowd events often occur due to the lack of proper crowd safety management. For instance, for a large scale moving crowd, a minor accident can create a panic for the people to start stampede. Although many smart video surveillance tools, inspired by the recent advanced artificial intelligence (AI) technology and machine learning (ML) algorithms, enable object detection and identification, it is still challenging to predict the crowd mobility in real-time for preventing potential disasters. In this paper, we propose an intelligent crowd engineering platform using mobility characterization and analytics named ICE-MoCha. ICE-MoCha is to assist safety management for mobile crowd events by predicting and thus helping to prevent potential disasters through real-time radio frequency (RF) data characterization and analysis. The existing video surveillance based approaches lack scalability thus have limitations in its capability for wide open areas of crowd events. Via effectively integrating RF signal analysis, our approach can enhance safety management for mobile crowd. We particularly tackle the problems of identification, speed, and direction detection for the mobile group, among various crowd mobility characteristics. We then apply those group semantics to track the crowd status and predict any potential accidents and disasters. Taking the advantages of power-efficiency, cost-effectiveness, and ubiquitous availability, we specifically use and analyze a Bluetooth low energy (BLE) signal. We have conducted experiments of ICE-MoCha in a real crowd event as well as controlled indoor and outdoor lab environments. The results show the feasibility of ICE-MoCha detecting the mobile crowd characteristics in real-time, indicating it can effectively help the crowd management tasks to avoid potential crowd movement related incidents.
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Ms. Seema and Dr. Geeta Sachdeva. "Knowledge Management Driven Crowd Sourcing Platforms Facilitating Moonlighting Practices Of Workforce." Restaurant Business 118, no. 11 (November 27, 2019): 637–44. http://dx.doi.org/10.26643/rb.v118i11.11787.
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Crowd sourcing platforms are rapidly replacing the traditional knowledge management systems now-a-days. Computer savvy workforce has been practicing crowd sourcing for a considerable amount of time now and mostly those people who do or want to do double jobbing, are working with these crowd sourcing platforms. Crowd workers are mostly those people who perform skill based and short term assignments for various organisations. They mostly practice double or multiple jobbing at the same time. Double jobbing is being practised by the middle class working population since time immemorial and in a variety of occupations. This is also called moonlighting in the business language.
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Wen, Rong, and Wenjing Yan. "Vessel Crowd Movement Pattern Mining for Maritime Traffic Management." LOGI – Scientific Journal on Transport and Logistics 10, no. 2 (November 1, 2019): 105–15. http://dx.doi.org/10.2478/logi-2019-0020.
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Abstract The goal of maritime traffic management is to provide a safe and efficient maritime environment for different type of vessels facilitating port logistics and supply chain business. However, current maritime traffic management mainly relies on the massive individual vessel’s data for decision making. Lack of macro-level understanding of vessel crowd movement around port challenges maritime safety and traffic efficiency. In this paper, we describe a spatio-temporal data mining method to discover crowd movement patterns of vessels from their short-term history data. The method first captures vessels’ crowd movement features by building vessels’ tracklets with their speed and location. A movement vector clustering algorithm is developed to find different travel behaviors for different group of vessels. With nonparametric regression on the classified vessel movement vectors which represent the crowd travel behaviors, an overall vessel movement pattern can then be discovered. In this research, we tested real trajectory data of vessels near Singapore ports. Comparing with the actual massive vessel movement data, we found that this method was able to extract vessels’ crowd movement information. The hotspots on risk area in terms of vessel traffic and speed can be identified. The method can be used to provide decision-making support for maritime traffic management.