In-Depth Survey to Detect, Monitor and Manage Crowd

Abstract

Crowd management is a flourishing, active research area and must be given attention due to the potential losses, disasters, and accidents that could occur if it were neglected. For the last decade, the crowd management field has witnessed significant advancements; however, more investigative work is still needed. The integration of different crowd detection and monitoring techniques can enhance the control and the performance compared to those of more limited stand-alone techniques. Crowd management encompasses an entire process, from the monitoring stage through the decision support system stage. This sector involves accessing and interpreting information sources, predicting crowd behavior, and deciding on the use of a range of possible interventions based on context. This paper shows a fresh conclusive review of the concept of the crowd, discussing it from several perspectives in light of its defining characteristics, its risks, and tragedies, which may occur due to challenges faced during crowd management, where these conclusions are based on a massive number of scholarly articles that were newly published. Besides, a systematic discussion is shown concerning the steps of managing a crowd, including crowd detection, in which several new methods are reviewed, followed by illustrating both direct and indirect approaches to crowd monitoring and tracking monitoring. The primary purpose of this review is to establish a comprehensive understanding of crowdrelated processes. Moreover, it aims to find research gaps to overcome the limitations of using stand-alone techniques in each process and provide support to other researchers' future work.

Problem Solving in Crowd Management Using Heuristic Approach

“…Heuristics methods were mainly used in simulation and crowd modeling [69]. Human crowds display a wide variety of collective behaviors that support an efficient motion under conditions such as collision avoidance and pushing, bypassing, backward motion, and not touching other pedestrians.…”

“…This section will concentrate on the applications of heuristics in crowd management. Crowd management includes crowd recognition, tracking, simulation, and prediction [69]. From a heuristic perspective, tracking is a kind of recognition and prediction results from simulation.…”

“…This recognition is also used to detect any abnormal behavior of the crowd, which extends crowd recognition to crowd management. It will also help to develop a crowd risk index (CRI) and decision support systems (DSS) for crowd management [69]. The issue of selecting the optimal method and architecture for crowd detection belongs to the polymerization problem, which may refer to the simplest, the fastest, the most accurate, or the most efficient at producing accuracy while minimizing computational complexity.…”

Analysis of Rail Passenger Flow in a Rail Station Concourse Prior to and During the COVID-19 Pandemic Using Event-Based Simulation Models and Scenarios

“…Another opportunity to examine the effectiveness of crowd management is through the use of technology. As suggested by Al-Shaery et al [1], during public events and mass gatherings, crowd detection and monitoring techniques could be used to control and track the crowd behaviour in order to mitigate the risk of incidents and tragedies. This is achieved through the use of automated technology tools such as radio-frequency identification (RFID), Wi-Fi and Bluetooth to detect and monitor the crowd.…”

Evaluating COVID-19 control measures in mass gathering events with vaccine inequalities

“…Tools for assessing effective control strategies are essential for determining the right combination of measures 15 . Agent-based models (ABM) have been proposed to study the effect of control measures such as face masks, screening, and population control 16 .…”