Automated Solutions for Crowd Size Estimation

Author:

Aziz Muhammad Waqar12,Naeem Farhan3,Alizai Muhammad Hamad4,Khan Khan Bahadar2

Affiliation:

1. Umm Al-Qura University, Makkah, Saudi Arabia

2. CECOS University of IT and Emerging Sciences, Peshawar, Pakistan

3. University of Engineering and Technology, Peshawar, Pakistan

4. Lahore University of Management Sciences (LUMS), Lahore, Pakistan

Abstract

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.

Publisher

SAGE Publications

Subject

Law,Library and Information Sciences,Computer Science Applications,General Social Sciences

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1. Population Density Estimation using Single Shot Detection Algorithm;2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS);2023-06-14

2. People Counting System Using OpenCV Algorithms and Edge Computing for Safety Management;2023 IEEE International Conference on Smart Information Systems and Technologies (SIST);2023-05-04

3. Student Detection and People Counting System Based on Apriori Algorithm;2022 International Conference on Education, Network and Information Technology (ICENIT);2022-09

4. Application of Cellular Automata with Improved Dynamic Analysis in Evacuation Management of Sports Events;Journal of Sensors;2022-02-23

5. Single Convolutional Neural Network With Three Layers Model for Crowd Density Estimation;IEEE Access;2022

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