A review on technological advancements in crowd management

Sharma, Deepak; Bhondekar, Amol P.; Shukla, Alok Kumar; Ghanshyam, C.

doi:10.1007/s12652-016-0432-x

Cited by 50 publications

(36 citation statements)

References 43 publications

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“…Data gathered from various sources are used to model the inflow and crowd dynamics. Sources can vary from CCTV video feed, social media activity to cellphones and other radio frequency based sensors (Sharma, Bhondekar, Shukla, & Ghanshyam, 2018). This helps save lives by preventing or mitigating the risk of stampedes.…”

Section: Strengthsmentioning

confidence: 99%

Analytics and Big Data: Emerging trends and their impact on our lives

Saha

2019

Journal of Public Affairs

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Companies are increasingly turning to Analytics to gain a competitive edge, providing decision makers with better insights. As they do, firms must resolve unique demands on their Information Technology resources and processes. This paper attempts to review the chronology of the adoption of Analytics. Next, it highlights how various economic sectors have incorporated Analytics and the resulting changes in the ways businesses interact with their customers. Further, the paper explores the cutting edge innovations in the Analytics domain. Subsequently, this paper tries to do an impact analysis on all these developments of our lives. Finally, the opportunities and threats, and how they may stand to affect our future, are discussed.

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Section: Strengthsmentioning

confidence: 99%

Analytics and Big Data: Emerging trends and their impact on our lives

Saha

2019

Journal of Public Affairs

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“…The accuracy of the detection of anomalies fluctuates for various methods, e.g., going to as low as 57% [36], which may negatively affect the accuracy of stampede analysis. Last but not least, vision-based detection techniques face privacy and security related issues [44] (which are conceptually similar to those based on GPS trackers even though a different technology is leveraged).…”

Section: Related Workmentioning

confidence: 99%

The impact of position errors on crowd simulation

Zhang

Lai

Miranskyy

2019

Simulation Modelling Practice and Theory

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In large crowd events, there is always a potential possibility that a stampede accident will occur. The accident may cause injuries or even death. Approaches for controlling crowd flows and predicting dangerous congestion spots would be a boon to on-site authorities to manage the crowd and to prevent fatal accidents. One of the most popular approaches is real-time crowd simulation based on position data from personal Global Positioning System (GPS) devices. However, the accuracy of spatial data varies for different GPS devices, and it is also affected by an environment in which an event takes place. In this paper, we would like to assess the effect of position errors on stampede prediction. We propose an Automatic Real-time dEtection of Stampedes (ARES) method to predict stampedes for large events. We implement three different stampede assessment methods in Menge framework and incorporate position errors. Our analysis suggests that the probability of simulated stampede changes significantly with the increase of the magnitude of position errors, which cannot be eliminated entirely with the help of classic techniques, such as the Kalman filter. Thus, it is our position that novel stampede assessment methods should be developed, focusing on the detection of position noise and the elimination of its effect. *

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“…Conclusions and future work are presented in Section 5. In [4], the authors presented a broad review on various crowd management and monitoring technologies that are based on vision (CCTV), Wireless/RF and Web/Social media technologies. It presented two of the most known examples of the crowd management, viz., the Hajj (pilgrimage) and the Kumbh Mela (in India).…”

Section: Introductionmentioning

confidence: 99%

“…www.ijacsa.thesai.orgII. BACKGROUNDLarge crowd management has been addressed in several works in the literature[4][5][6].…”

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confidence: 99%

A Service-Oriented Architecture for Optimal Service Selection and Positioning in Extremely Large Crowds

Abdeen¹

2020

IJACSA

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The problem of managing large crowds has many aspects and has been reported in the literature. One of these aspects is the distribution of supplies such as food and water in especially when the targeted region is overcrowded. Some of the challenges is to plan the locations of food and water supply centres in such a way to achieve multiple objective functions such as the type of food and the shortest distance to customer. A practical example of this problem is the food distribution and food cart location in the region of Mena (also known as Tent City, in Saudi Arabia) during the yearly pilgrimage season. In this work, we propose a Service Oriented Architecture (SOA) for positioning services in the region of Mena (Mecca-Saudi Arabia) that covers an area of approximately 20 square kilometres during the pilgrimage season. The architecture proposes an optimal service selection as well as a mobile food cart positioning algorithm based on client pre-set profiles to achieve multiple objective functions for the clients as well as the service providers. Some of these objective functions are the least waiting time to be served, the shortest distance to service, the lowest cost, and the maximum profit for the service provider.

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A review on technological advancements in crowd management

Cited by 50 publications

References 43 publications

Analytics and Big Data: Emerging trends and their impact on our lives

Analytics and Big Data: Emerging trends and their impact on our lives

The impact of position errors on crowd simulation

A Service-Oriented Architecture for Optimal Service Selection and Positioning in Extremely Large Crowds

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