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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 specified assumptions that are highly… More >

  • Open Access


    Optimization of Resource Allocation in Unmanned Aerial Vehicles Based on Swarm Intelligence Algorithms

    Siling Feng1, Yinjie Chen1, Mengxing Huang1,2,*, Feng Shu1

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4341-4355, 2023, DOI:10.32604/cmc.2023.037154

    Abstract Due to their adaptability, Unmanned Aerial Vehicles (UAVs) play an essential role in the Internet of Things (IoT). Using wireless power transfer (WPT) techniques, an UAV can be supplied with energy while in flight, thereby extending the lifetime of this energy-constrained device. This paper investigates the optimization of resource allocation in light of the fact that power transfer and data transmission cannot be performed simultaneously. In this paper, we propose an optimization strategy for the resource allocation of UAVs in sensor communication networks. It is a practical solution to the problem of marine sensor networks that are located far from… More >

  • Open Access


    Low Altitude Satellite Constellation for Futuristic Aerial-Ground Communications

    Saifur Rahman Sabuj1, Mohammad Saadman Alam2, Majumder Haider2, Md Akbar Hossain3, Al-Sakib Khan Pathan4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1053-1089, 2023, DOI:10.32604/cmes.2023.024078

    Abstract This paper discusses the significance and prospects of low altitude small satellite aerial vehicles to ensure smooth aerial-ground communications for next-generation broadband networks. To achieve the generic goals of fifthgeneration and beyond wireless networks, the existing aerial network architecture needs to be revisited. The detailed architecture of low altitude aerial networks and the challenges in resource management have been illustrated in this paper. Moreover, we have studied the coordination between promising communication technologies and low altitude aerial networks to provide robust network coverage. We talk about the techniques that can ensure userfriendly control and monitoring of the low altitude aerial… More > Graphic Abstract

    Low Altitude Satellite Constellation for Futuristic Aerial-Ground Communications

  • Open Access


    Received Power Based Unmanned Aerial Vehicles (UAVs) Jamming Detection and Nodes Classification Using Machine Learning

    Waleed Aldosari*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1253-1269, 2023, DOI:10.32604/cmc.2023.036111

    Abstract This paper presents a machine-learning method for detecting jamming UAVs and classifying nodes during jamming attacks on Wireless Sensor Networks (WSNs). Jamming is a type of Denial of Service (DoS) attack and intentional interference where a malicious node transmits a high-power signal to increase noise on the receiver side to disrupt the communication channel and reduce performance significantly. To defend and prevent such attacks, the first step is to detect them. The current detection approaches use centralized techniques to detect jamming, where each node collects information and forwards it to the base station. As a result, overhead and communication costs… More >

  • Open Access


    Optimal Deep Learning Model Enabled Secure UAV Classification for Industry 4.0

    Khalid A. Alissa1, Mohammed Maray2, Areej A. Malibari3, Sana Alazwari4, Hamed Alqahtani5, Mohamed K. Nour6, Marwa Obbaya7, Mohamed A. Shamseldin8, Mesfer Al Duhayyim9,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5349-5367, 2023, DOI:10.32604/cmc.2023.033532

    Abstract Emerging technologies such as edge computing, Internet of Things (IoT), 5G networks, big data, Artificial Intelligence (AI), and Unmanned Aerial Vehicles (UAVs) empower, Industry 4.0, with a progressive production methodology that shows attention to the interaction between machine and human beings. In the literature, various authors have focused on resolving security problems in UAV communication to provide safety for vital applications. The current research article presents a Circle Search Optimization with Deep Learning Enabled Secure UAV Classification (CSODL-SUAVC) model for Industry 4.0 environment. The suggested CSODL-SUAVC methodology is aimed at accomplishing two core objectives such as secure communication via image… More >

  • Open Access


    3D Path Optimisation of Unmanned Aerial Vehicles Using Q Learning-Controlled GWO-AOA

    K. Sreelakshmy1, Himanshu Gupta1, Om Prakash Verma1, Kapil Kumar2, Abdelhamied A. Ateya3, Naglaa F. Soliman4,*

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2483-2503, 2023, DOI:10.32604/csse.2023.032737

    Abstract Unmanned Aerial Vehicles (UAVs) or drones introduced for military applications are gaining popularity in several other fields as well such as security and surveillance, due to their ability to perform repetitive and tedious tasks in hazardous environments. Their increased demand created the requirement for enabling the UAVs to traverse independently through the Three Dimensional (3D) flight environment consisting of various obstacles which have been efficiently addressed by metaheuristics in past literature. However, not a single optimization algorithms can solve all kind of optimization problem effectively. Therefore, there is dire need to integrate metaheuristic for general acceptability. To address this issue,… More >

  • Open Access


    Monitoring Thosea sinensis Walker in Tea Plantations Based on UAV Multi-Spectral Image

    Lin Yuan1, Qimeng Yu1, Yao Zhang2,*, Xiaochang Wang3, Ouguan Xu1, Wenjing Li1

    Phyton-International Journal of Experimental Botany, Vol.92, No.3, pp. 747-761, 2023, DOI:10.32604/phyton.2023.025502

    Abstract Thosea sinensis Walker (TSW) rapidly spreads and severely damages the tea plants. Therefore, finding a reliable operational method for identifying the TSW-damaged areas via remote sensing has been a focus of a research community. Such methods also enable us to calculate the precise application of pesticides and prevent the subsequent spread of the pests. In this work, based on the unmanned aerial vehicle (UAV) platform, five band images of multispectral red-edge camera were obtained and used for monitoring the TSW in tea plantations. By combining the minimum redundancy maximum relevance (mRMR) with the selected spectral features, a comprehensive spectral selection… More >

  • Open Access


    Secrecy Outage Probability for Two-Way Integrated Satellite Unmanned Aerial Vehicle Relay Networks with Hardware Impairments

    Xiaoting Ren1, Kefeng Guo2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2515-2530, 2023, DOI:10.32604/cmes.2023.024857

    Abstract In this paper, we investigate the secrecy outage performance for the two-way integrated satellite unmanned aerial vehicle relay networks with hardware impairments. Particularly, the closed-form expression for the secrecy outage probability is obtained. Moreover, to get more information on the secrecy outage probability in a high signal-to-noise regime, the asymptotic analysis along with the secrecy diversity order and secrecy coding gain for the secrecy outage probability are also further obtained, which presents a fast method to evaluate the impact of system parameters and hardware impairments on the considered network. Finally, Monte Carlo simulation results are provided to show the efficiency… More >

  • Open Access


    Modeling and Analysis of UAV-Assisted Mobile Network with Imperfect Beam Alignment

    Mohamed Amine Ouamri1,2, Reem Alkanhel3,*, Cedric Gueguen1, Manal Abdullah Alohali4, Sherif S. M. Ghoneim5

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 453-467, 2023, DOI:10.32604/cmc.2023.031450

    Abstract With the rapid development of emerging 5G and beyond (B5G), Unmanned Aerial Vehicles (UAVs) are increasingly important to improve the performance of dense cellular networks. As a conventional metric, coverage probability has been widely studied in communication systems due to the increasing density of users and complexity of the heterogeneous environment. In recent years, stochastic geometry has attracted more attention as a mathematical tool for modeling mobile network systems. In this paper, an analytical approach to the coverage probability analysis of UAV-assisted cellular networks with imperfect beam alignment has been proposed. An assumption was considered that all users are distributed… More >

  • Open Access


    Unmanned Aerial Vehicle Assisted Forest Fire Detection Using Deep Convolutional Neural Network

    A. K. Z Rasel Rahman1, S. M. Nabil Sakif1, Niloy Sikder1, Mehedi Masud2, Hanan Aljuaid3, Anupam Kumar Bairagi1,*

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3259-3277, 2023, DOI:10.32604/iasc.2023.030142

    Abstract Disasters may occur at any time and place without little to no presage in advance. With the development of surveillance and forecasting systems, it is now possible to forebode the most life-threatening and formidable disasters. However, forest fires are among the ones that are still hard to anticipate beforehand, and the technologies to detect and plot their possible courses are still in development. Unmanned Aerial Vehicle (UAV) image-based fire detection systems can be a viable solution to this problem. However, these automatic systems use advanced deep learning and image processing algorithms at their core and can be tuned to provide… More >

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