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  • Open Access

    ARTICLE

    Submarine Hunter: Efficient and Secure Multi-Type Unmanned Vehicles

    Halah Hasan Mahmoud1, Marwan Kadhim Mohammed Al-Shammari1, Gehad Abdullah Amran2,3,*, Elsayed Tag eldin4,*, Ala R. Alareqi5, Nivin A. Ghamry6, Ehaa ALnajjar7, Esmail Almosharea8

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 573-589, 2023, DOI:10.32604/cmc.2023.039363

    Abstract Utilizing artificial intelligence (AI) to protect smart coastal cities has become a novel vision for scientific and industrial institutions. One of these AI technologies is using efficient and secure multi-environment Unmanned Vehicles (UVs) for anti-submarine attacks. This study’s contribution is the early detection of a submarine assault employing hybrid environment UVs that are controlled using swarm optimization and secure the information in between UVs using a decentralized cybersecurity strategy. The Dragonfly Algorithm is used for the orientation and clustering of the UVs in the optimization approach, and the Re-fragmentation strategy is used in the Network… More >

  • Open Access

    ARTICLE

    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

    ARTICLE

    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… More >

  • Open Access

    ARTICLE

    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… More >

  • Open Access

    ARTICLE

    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… More >

  • Open Access

    ARTICLE

    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 More >

  • Open Access

    ARTICLE

    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… More >

  • Open Access

    ARTICLE

    Optimal Deep Learning Enabled Communication System for Unmanned Aerial Vehicles

    Anwer Mustafa Hilal1,*, Jaber S. Alzahrani2, Dalia H. Elkamchouchi3, Majdy M. Eltahir4, Ahmed S. Almasoud5, Abdelwahed Motwakel1, Abu Sarwar Zamani1, Ishfaq Yaseen1

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 955-969, 2023, DOI:10.32604/csse.2023.030132

    Abstract Recently, unmanned aerial vehicles (UAV) or drones are widely employed for several application areas such as surveillance, disaster management, etc. Since UAVs are limited to energy, efficient coordination between them becomes essential to optimally utilize the resources and effective communication among them and base station (BS). Therefore, clustering can be employed as an effective way of accomplishing smart communication systems among multiple UAVs. In this aspect, this paper presents a group teaching optimization algorithm with deep learning enabled smart communication system (GTOADL-SCS) technique for UAV networks. The proposed GTOADL-SCS model encompasses a two stage process… More >

  • Open Access

    ARTICLE

    Feature Selection with Stacked Autoencoder Based Intrusion Detection in Drones Environment

    Heba G. Mohamed1, Saud S. Alotaibi2, Majdy M. Eltahir3, Heba Mohsen4, Manar Ahmed Hamza5,*, Abu Sarwar Zamani5, Ishfaq Yaseen5, Abdelwahed Motwakel5

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5441-5458, 2022, DOI:10.32604/cmc.2022.031887

    Abstract The Internet of Drones (IoD) offers synchronized access to organized airspace for Unmanned Aerial Vehicles (known as drones). The availability of inexpensive sensors, processors, and wireless communication makes it possible in real time applications. As several applications comprise IoD in real time environment, significant interest has been received by research communications. Since IoD operates in wireless environment, it is needed to design effective intrusion detection system (IDS) to resolve security issues in the IoD environment. This article introduces a metaheuristics feature selection with optimal stacked autoencoder based intrusion detection (MFSOSAE-ID) in the IoD environment. The… More >

  • Open Access

    ARTICLE

    Efficient UAV-Based MEC Using GPU-Based PSO and Voronoi Diagrams

    Mohamed H. Mousa1,2,*, Mohamed K. Hussein2

    CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.2, pp. 413-434, 2022, DOI:10.32604/cmes.2022.020639

    Abstract Mobile-Edge Computing (MEC) displaces cloud services as closely as possible to the end user. This enables the edge servers to execute the offloaded tasks that are requested by the users, which in turn decreases the energy consumption and the turnaround time delay. However, as a result of a hostile environment or in catastrophic zones with no network, it could be difficult to deploy such edge servers. Unmanned Aerial Vehicles (UAVs) can be employed in such scenarios. The edge servers mounted on these UAVs assist with task offloading. For the majority of IoT applications, the execution… More >

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