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  • Open Access


    Toward Optimal Periodic Crowd Tracking via Unmanned Aerial Vehicle

    Khalil Chebil1,2, Skander Htiouech3, Mahdi Khemakhem1,2,4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 233-263, 2023, DOI:10.32604/cmes.2023.026476

    Abstract Crowd management and analysis (CMA) systems have gained a lot of interest in the vulgarization of unmanned aerial vehicles (UAVs) use. Crowd tracking using UAVs is among the most important services provided by a CMA. In this paper, we studied the periodic crowd-tracking (PCT) problem. It consists in using UAVs to follow-up crowds, during the life-cycle of an open crowded area (OCA). Two criteria were considered for this purpose. The first is related to the CMA initial investment, while the second is to guarantee the quality of service (QoS). The existing works focus on very… More >

  • Open Access


    Sparrow Search Optimization with Transfer Learning-Based Crowd Density Classification

    Mohammad Yamin1,*, Mishaal Mofleh Almutairi2, Saeed Badghish3, Saleh Bajaba4

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4965-4981, 2023, DOI:10.32604/cmc.2023.033705

    Abstract Due to the rapid increase in urbanization and population, crowd gatherings are frequently observed in the form of concerts, political, and religious meetings. HAJJ is one of the well-known crowding events that takes place every year in Makkah, Saudi Arabia. Crowd density estimation and crowd monitoring are significant research areas in Artificial Intelligence (AI) applications. The current research study develops a new Sparrow Search Optimization with Deep Transfer Learning based Crowd Density Detection and Classification (SSODTL-CD2C) model. The presented SSODTL-CD2C technique majorly focuses on the identification and classification of crowd densities. To attain this, SSODTL-CD2C… More >

  • Open Access


    Tracking and Analysis of Pedestrian’s Behavior in Public Places

    Mahwish Pervaiz1, Mohammad Shorfuzzaman2, Abdulmajeed Alsufyani2, Ahmad Jalal3, Suliman A. Alsuhibany4, Jeongmin Park5,*

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 841-853, 2023, DOI:10.32604/cmc.2023.029629

    Abstract Crowd management becomes a global concern due to increased population in urban areas. Better management of pedestrians leads to improved use of public places. Behavior of pedestrian’s is a major factor of crowd management in public places. There are multiple applications available in this area but the challenge is open due to complexity of crowd and depends on the environment. In this paper, we have proposed a new method for pedestrian’s behavior detection. Kalman filter has been used to detect pedestrian’s using movement based approach. Next, we have performed occlusion detection and removal using region More >

  • Open Access


    Human Faces Detection and Tracking for Crowd Management in Hajj and Umrah

    Riad Alharbey1, Ameen Banjar1, Yahia Said2,3,*, Mohamed Atri4, Abdulrahman Alshdadi1, Mohamed Abid5

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6275-6291, 2022, DOI:10.32604/cmc.2022.024272

    Abstract Hajj and Umrah are two main religious duties for Muslims. To help faithfuls to perform their religious duties comfortably in overcrowded areas, a crowd management system is a must to control the entering and exiting for each place. Since the number of people is very high, an intelligent crowd management system can be developed to reduce human effort and accelerate the management process. In this work, we propose a crowd management process based on detecting, tracking, and counting human faces using Artificial Intelligence techniques. Human detection and counting will be performed to calculate the number… More >

  • Open Access


    Sparse Crowd Flow Analysis of Tawaaf of Kaaba During the COVID-19 Pandemic

    Durr-e-Nayab1, Ali Mustafa Qamar2,*, Rehan Ullah Khan3, Waleed Albattah3, Khalil Khan4, Shabana Habib3, Muhammad Islam5

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5581-5601, 2022, DOI:10.32604/cmc.2022.022153

    Abstract The advent of the COVID-19 pandemic has adversely affected the entire world and has put forth high demand for techniques that remotely manage crowd-related tasks. Video surveillance and crowd management using video analysis techniques have significantly impacted today's research, and numerous applications have been developed in this domain. This research proposed an anomaly detection technique applied to Umrah videos in Kaaba during the COVID-19 pandemic through sparse crowd analysis. Managing the Kaaba rituals is crucial since the crowd gathers from around the world and requires proper analysis during these days of the pandemic. The Umrah… More >

  • Open Access


    Identification of Anomalous Behavioral Patterns in Crowd Scenes

    Muhammad Asif Nauman*, Muhammad Shoaib

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 925-939, 2022, DOI:10.32604/cmc.2022.022147

    Abstract Real time crowd anomaly detection and analyses has become an active and challenging area of research in computer vision since the last decade. The emerging need of crowd management and crowd monitoring for public safety has widen the countless paths of deep learning methodologies and architectures. Although, researchers have developed many sophisticated algorithms but still it is a challenging and tedious task to manage and monitor crowd in real time. The proposed research work focuses on detection of local and global anomaly detection of crowd. Fusion of spatial-temporal features assist in differentiation of feature trained… More >

  • Open Access


    A Modelling and Scheduling Tool for Crowd Movement in Complex Network

    Emad Felemban1, Faizan Ur Rehman2,*, Akhlaq Ahmad2, Muhamad Felemban3

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1361-1375, 2022, DOI:10.32604/iasc.2022.020235

    Abstract Managing events pose a unique challenge to the stakeholders and authorities to control the crowd in all three phases of the event (pre, during and post), ensuring crowd safety. One of the fundamental keys to provide crowd safety is to consider the mobility infrastructure hosting the crowd, i.e., routes, areas, entrances and exits. During Hajj, where millions of pilgrims worldwide fulfil the annual event’s rites, mina encampment incorporates pilgrims performing recurring stoning ritual conducted over multi-level Jamarat bridge. Pilgrims mobility through the available complex road network, to and back from the Jamarat bridge, forces upon More >

  • Open Access


    A Novel Cultural Crowd Model Toward Cognitive Artificial Intelligence

    Fatmah Abdulrahman Baothman*, Osama Ahmed Abulnaja, Fatima Jafar Muhdher

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3337-3363, 2021, DOI:10.32604/cmc.2021.017637

    Abstract Existing literature shows cultural crowd management has unforeseen issues due to four dynamic elements; time, capacity, speed, and culture. Cross-cultural variations are increasing the complexity level because each mass and event have different characteristics and challenges. However, no prior study has employed the six Hofstede Cultural Dimensions (HCD) for predicting crowd behaviors. This study aims to develop the Cultural Crowd-Artificial Neural Network (CC-ANN) learning model that considers crowd’s HCD to predict their physical (distance and speed) and social (collectivity and cohesion) characteristics. The model was developed towards a cognitive intelligent decision support tool where the… More >

  • Open Access


    Hajj Crowd Management Using CNN-Based Approach

    Waleed Albattah1,*, Muhammad Haris Kaka Khel2, Shabana Habib1, Muhammad Islam3, Sheroz Khan3,4, Kushsairy Abdul Kadir2

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 2183-2197, 2021, DOI:10.32604/cmc.2020.014227

    Abstract Hajj as the Muslim holy pilgrimage, attracts millions of humans to Mecca every year. According to statists, the pilgrimage has attracted close to 2.5 million pilgrims in 2019, and at its peak, it has attracted over 3 million pilgrims in 2012. It is considered as the world’s largest human gathering. Safety makes one of the main concerns with regards to managing the large crowds and ensuring that stampedes and other similar overcrowding accidents are avoided. This paper presents a crowd management system using image classification and an alarm system for managing the millions of crowds… More >

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