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 >

Mohamed Rabik Mohamed Ismail¹, Muthuramalingam Thangaraj^1,*, Khaja Moiduddin^2,*, Zeyad Almutairi^2,3, 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 >

Weiqiang Jin^1,#, Xingwu Tian^1,#, Bohang Shi¹, Biao Zhao^1,*, 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 >

Sagar Kavaiya¹, Hiren Mewada^2,*, 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 >

Syed Kamran Haider^1,2, Abbas Ahmed², Noman Mujeeb Khan², Ali Nauman^3,*, Sung Won Kim^3,*

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 >

Oumaima Ameslek^1,*, 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 >

Tong Gan¹, Shuo Dong¹, Shiyou Wang¹, Jiaxin Li^2,*

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 >

Liang Zeng^1,2, Mai Hu¹, Chenning Zhang¹, Quan Yuan¹, Shanshan Wang^1,2,*

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 >

Jingyu Wang¹, Ping Jiang^1,*, Jianjun Qi²

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1889-1918, 2024, DOI:10.32604/cmes.2024.049813 - 20 May 2024

Abstract The unmanned aerial vehicle (UAV) swarm plays an increasingly important role in the modern battlefield, and the UAV swarm operational test is a vital means to validate the combat effectiveness of the UAV swarm. Due to the high cost and long duration of operational tests, it is essential to plan the test in advance. To solve the problem of planning UAV swarm operational test, this study considers the multi-stage feature of a UAV swarm mission, composed of launch, flight and combat stages, and proposes a method to find test plans that can maximize mission reliability.… More >

Xiangyan Tang^1,2, Chengchun Ruan^1,2,*, Xiulai Li^2,3, Binbin Li^1,2, Cebin Fu^1,2

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 983-1003, 2024, DOI:10.32604/cmc.2024.047541 - 25 April 2024

Abstract Accurately identifying small objects in high-resolution aerial images presents a complex and crucial task in the field of small object detection on unmanned aerial vehicles (UAVs). This task is challenging due to variations in UAV flight altitude, differences in object scales, as well as factors like flight speed and motion blur. To enhance the detection efficacy of small targets in drone aerial imagery, we propose an enhanced You Only Look Once version 7 (YOLOv7) algorithm based on multi-scale spatial context. We build the MSC-YOLO model, which incorporates an additional prediction head, denoted as P2, to… More >