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  • Open Access

    ARTICLE

    Multi-UAV Collaborative Mission Planning Method for Self-Organized Sensor Data Acquisition

    Shijie Yang1, Jiateng Yuan1, Zhipeng Zhang1, Zhibo Chen1,2, Hanchao Zhang4, Xiaohui Cui1,2,3,*

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1529-1563, 2024, DOI:10.32604/cmc.2024.055402 - 15 October 2024

    Abstract In recent years, sensor technology has been widely used in the defense and control of sensitive areas in cities, or in various scenarios such as early warning of forest fires, monitoring of forest pests and diseases, and protection of endangered animals. Deploying sensors to collect data and then utilizing unmanned aerial vehicle (UAV) to collect the data stored in the sensors has replaced traditional manual data collection as the dominant method. The current strategies for efficient data collection in above scenarios are still imperfect, and the low quality of the collected data and the excessive… More >

  • Open Access

    ARTICLE

    Border Sensitive Knowledge Distillation for Rice Panicle Detection in UAV Images

    Anitha Ramachandran, Sendhil Kumar K.S.*

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 827-842, 2024, DOI:10.32604/cmc.2024.054768 - 15 October 2024

    Abstract Research on panicle detection is one of the most important aspects of paddy phenotypic analysis. A phenotyping method that uses unmanned aerial vehicles can be an excellent alternative to field-based methods. Nevertheless, it entails many other challenges, including different illuminations, panicle sizes, shape distortions, partial occlusions, and complex backgrounds. Object detection algorithms are directly affected by these factors. This work proposes a model for detecting panicles called Border Sensitive Knowledge Distillation (BSKD). It is designed to prioritize the preservation of knowledge in border areas through the use of feature distillation. Our feature-based knowledge distillation method More >

  • Open Access

    ARTICLE

    Task Offloading and Trajectory Optimization in UAV Networks: A Deep Reinforcement Learning Method Based on SAC and A-Star

    Jianhua Liu*, Peng Xie, Jiajia Liu, Xiaoguang Tu

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1243-1273, 2024, DOI:10.32604/cmes.2024.054002 - 27 September 2024

    Abstract In mobile edge computing, unmanned aerial vehicles (UAVs) equipped with computing servers have emerged as a promising solution due to their exceptional attributes of high mobility, flexibility, rapid deployment, and terrain agnosticism. These attributes enable UAVs to reach designated areas, thereby addressing temporary computing swiftly in scenarios where ground-based servers are overloaded or unavailable. However, the inherent broadcast nature of line-of-sight transmission methods employed by UAVs renders them vulnerable to eavesdropping attacks. Meanwhile, there are often obstacles that affect flight safety in real UAV operation areas, and collisions between UAVs may also occur. To solve… More >

  • Open Access

    ARTICLE

    Unknown Environment Measurement Mapping by Unmanned Aerial Vehicle Using Kalman Filter-Based Low-Cost Estimated Parallel 8-Beam LIDAR

    Mohamed Rabik Mohamed Ismail1, Muthuramalingam Thangaraj1,*, Khaja Moiduddin2,*, Zeyad Almutairi2,3, Mustufa Haider Abidi2

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4263-4279, 2024, DOI:10.32604/cmc.2024.055271 - 12 September 2024

    Abstract The measurement and mapping of objects in the outer environment have traditionally been conducted using ground-based monitoring systems, as well as satellites. More recently, unmanned aerial vehicles have also been employed for this purpose. The accurate detection and mapping of a target such as buildings, trees, and terrains are of utmost importance in various applications of unmanned aerial vehicles (UAVs), including search and rescue operations, object transportation, object detection, inspection tasks, and mapping activities. However, the rapid measurement and mapping of the object are not currently achievable due to factors such as the object’s size,… More >

  • Open Access

    ARTICLE

    Enhanced UAV Pursuit-Evasion Using Boids Modelling: A Synergistic Integration of Bird Swarm Intelligence and DRL

    Weiqiang Jin1,#, Xingwu Tian1,#, Bohang Shi1, Biao Zhao1,*, Haibin Duan2, Hao Wu3

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3523-3553, 2024, DOI:10.32604/cmc.2024.055125 - 12 September 2024

    Abstract The UAV pursuit-evasion problem focuses on the efficient tracking and capture of evading targets using unmanned aerial vehicles (UAVs), which is pivotal in public safety applications, particularly in scenarios involving intrusion monitoring and interception. To address the challenges of data acquisition, real-world deployment, and the limited intelligence of existing algorithms in UAV pursuit-evasion tasks, we propose an innovative swarm intelligence-based UAV pursuit-evasion control framework, namely “Boids Model-based DRL Approach for Pursuit and Escape” (Boids-PE), which synergizes the strengths of swarm intelligence from bio-inspired algorithms and deep reinforcement learning (DRL). The Boids model, which simulates collective… More >

  • Open Access

    ARTICLE

    Physical Layer Security of 6G Vehicular Networks with UAV Systems: First Order Secrecy Metrics, Optimization, and Bounds

    Sagar Kavaiya1, Hiren Mewada2,*, Sagarkumar Patel3, Dharmendra Chauhan3, Faris A. Almalki4, Hana Mohammed Mujlid4

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3685-3711, 2024, DOI:10.32604/cmc.2024.053587 - 12 September 2024

    Abstract The mobility and connective capabilities of unmanned aerial vehicles (UAVs) are becoming more and more important in defense, commercial, and research domains. However, their open communication makes UAVs susceptible to undesirable passive attacks such as eavesdropping or jamming. Recently, the inefficiency of traditional cryptography-based techniques has led to the addition of Physical Layer Security (PLS). This study focuses on the advanced PLS method for passive eavesdropping in UAV-aided vehicular environments, proposing a solution to complement the conventional cryptography approach. Initially, we present a performance analysis of first-order secrecy metrics in 6G-enabled UAV systems, namely hybrid… More >

  • Open Access

    ARTICLE

    AI-Driven Energy Optimization in UAV-Assisted Routing for Enhanced Wireless Sensor Networks Performance

    Syed Kamran Haider1,2, Abbas Ahmed2, Noman Mujeeb Khan2, Ali Nauman3,*, Sung Won Kim3,*

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4085-4110, 2024, DOI:10.32604/cmc.2024.052997 - 12 September 2024

    Abstract In recent advancements within wireless sensor networks (WSN), the deployment of unmanned aerial vehicles (UAVs) has emerged as a groundbreaking strategy for enhancing routing efficiency and overall network functionality. This research introduces a sophisticated framework, driven by computational intelligence, that merges clustering techniques with UAV mobility to refine routing strategies in WSNs. The proposed approach divides the sensor field into distinct sectors and implements a novel weighting system for the selection of cluster heads (CHs). This system is primarily aimed at reducing energy consumption through meticulously planned routing and path determination. Employing a greedy algorithm More >

  • Open Access

    ARTICLE

    Cartographie Automatique et Comptage des Arbres Oliviers A Partir de L’Imagerie de Drone par Un Reseau de Neurones Covolutionnel

    Oumaima Ameslek1,*, Hafida Zahir2, Soukaina Mitro2, El Mostafa Bachaoui1

    Revue Internationale de Géomatique, Vol.33, pp. 321-340, 2024, DOI:10.32604/rig.2024.054838 - 03 September 2024

    Abstract L’agriculture de précision (AP) est une stratégie de gestion agricole fondée sur l’observation, la mesure et la réponse à la variabilité des cultures inter/intra-champ. Il comprend des avancées en matière de collecte, d’analyse et de gestion des données, ainsi que des développements technologiques en matière de stockage et de récupération de données, de positionnement précis, de surveillance des rendements et de télédétection. Cette dernière offre une résolution spatiale, spectrale et temporelle sans précédent, mais peut également fournir des informations détaillées sur la hauteur de la végétation et diverses observations. Aujourd’hui, le succès des nouvelles technologies… More >

  • Open Access

    ARTICLE

    Distributed Resource Allocation in Dispersed Computing Environment Based on UAV Track Inspection in Urban Rail Transit

    Tong Gan1, Shuo Dong1, Shiyou Wang1, Jiaxin Li2,*

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 643-660, 2024, DOI:10.32604/cmc.2024.051408 - 18 July 2024

    Abstract With the rapid development of urban rail transit, the existing track detection has some problems such as low efficiency and insufficient detection coverage, so an intelligent and automatic track detection method based on UAV is urgently needed to avoid major safety accidents. At the same time, the geographical distribution of IoT devices results in the inefficient use of the significant computing potential held by a large number of devices. As a result, the Dispersed Computing (DCOMP) architecture enables collaborative computing between devices in the Internet of Everything (IoE), promotes low-latency and efficient cross-wide applications, and… More >

  • Open Access

    ARTICLE

    A Multi-Strategy-Improved Northern Goshawk Optimization Algorithm for Global Optimization and Engineering Design

    Liang Zeng1,2, Mai Hu1, Chenning Zhang1, Quan Yuan1, Shanshan Wang1,2,*

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1677-1709, 2024, DOI:10.32604/cmc.2024.049717 - 18 July 2024

    Abstract Optimization algorithms play a pivotal role in enhancing the performance and efficiency of systems across various scientific and engineering disciplines. To enhance the performance and alleviate the limitations of the Northern Goshawk Optimization (NGO) algorithm, particularly its tendency towards premature convergence and entrapment in local optima during function optimization processes, this study introduces an advanced Improved Northern Goshawk Optimization (INGO) algorithm. This algorithm incorporates a multifaceted enhancement strategy to boost operational efficiency. Initially, a tent chaotic map is employed in the initialization phase to generate a diverse initial population, providing high-quality feasible solutions. Subsequently, after… More >

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