Zhijian Liu^*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3787-3803, 2024, DOI:10.32604/cmc.2024.048998

Abstract Considering the variations in imaging sizes of the unmanned aerial vehicles (UAV) at different aerial photography heights, as well as the influence of factors such as light and weather, which can result in missed detection and false detection of the model, this paper presents a comprehensive detection model based on the improved lightweight You Only Look Once version 8s (YOLOv8s) algorithm used in natural light and infrared scenes (L_YOLO). The algorithm proposes a special feature pyramid network (SFPN) structure and substitutes most of the neck feature extraction module with the Special deformable convolution feature extraction module (SDCN). Moreover, the model… More >

Usman Khan¹, Muhammad Khalid Khan¹, Muhammad Ayub Latif¹, Muhammad Naveed^1,2,*, Muhammad Mansoor Alam^2,3,4, Salman A. Khan¹, Mazliham Mohd Su’ud^2,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 2967-3000, 2024, DOI:10.32604/cmc.2024.045101

Abstract Recently, there has been a notable surge of interest in scientific research regarding spectral images. The potential of these images to revolutionize the digital photography industry, like aerial photography through Unmanned Aerial Vehicles (UAVs), has captured considerable attention. One encouraging aspect is their combination with machine learning and deep learning algorithms, which have demonstrated remarkable outcomes in image classification. As a result of this powerful amalgamation, the adoption of spectral images has experienced exponential growth across various domains, with agriculture being one of the prominent beneficiaries. This paper presents an extensive survey encompassing multispectral and hyperspectral images, focusing on their… More >

Asifa Mehmood Qureshi¹, Naif Al Mudawi², Mohammed Alonazi³, Samia Allaoua Chelloug⁴, Jeongmin Park^5,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3683-3701, 2024, DOI:10.32604/cmc.2024.043611

Abstract Road traffic monitoring is an imperative topic widely discussed among researchers. Systems used to monitor traffic frequently rely on cameras mounted on bridges or roadsides. However, aerial images provide the flexibility to use mobile platforms to detect the location and motion of the vehicle over a larger area. To this end, different models have shown the ability to recognize and track vehicles. However, these methods are not mature enough to produce accurate results in complex road scenes. Therefore, this paper presents an algorithm that combines state-of-the-art techniques for identifying and tracking vehicles in conjunction with image bursts. The extracted frames… More >

Peng Geng^1,*, Annan Yang², Yan Liu³

Journal on Artificial Intelligence, Vol.6, pp. 43-52, 2024, DOI:10.32604/jai.2024.047642

Abstract This article presents a real-time localization method for Unmanned Aerial Vehicles (UAVs) based on continuous image processing. The proposed method employs the Scale Invariant Feature Transform (SIFT) algorithm to identify key points in multi-scale space and generate descriptor vectors to match identical objects across multiple images. These corresponding points in the image provide pixel positions, which can be combined with transformation equations, allow for the calculation of the UAV’s actual ground position. Additionally, the physical coordinates of matching points in the image can be obtained, corresponding to the UAV’s physical coordinates. The method achieves real-time positioning and tracking during UAV… More >

Ruochen Wang^1,#, Jianjun Dong^2,#, Lishan Jin³, Yuyan Sun³, Taogetao Baoyin², Xiumei Wang^*

Phyton-International Journal of Experimental Botany, Vol.93, No.2, pp. 387-411, 2024, DOI:10.32604/phyton.2024.047573

Abstract Grassland biomass is an important parameter of grassland ecosystems. The complexity of the grassland canopy vegetation spectrum makes the long-term assessment of grassland growth a challenge. Few studies have explored the original spectral information of typical grasslands in Inner Mongolia and examined the influence of spectral information on aboveground biomass (AGB) estimation. In order to improve the accuracy of vegetation index inversion of grassland AGB, this study combined ground and Unmanned Aerial Vehicle (UAV) remote sensing technology and screened sensitive bands through ground hyperspectral data transformation and correlation analysis. The narrow band vegetation indices were calculated, and ground and airborne… More >

Zain Anwar Ali^1,2,*, Dingnan Deng¹, Muhammad Kashif Shaikh³, Raza Hasan⁴, Muhammad Aamir Khan²

Computer Systems Science and Engineering, Vol.48, No.1, pp. 1-34, 2024, DOI:10.32604/csse.2023.041866

Abstract Technological advances in unmanned aerial vehicles (UAVs) pursued by artificial intelligence (AI) are improving remote sensing applications in smart agriculture. These are valuable tools for monitoring and disease identification of plants as they can collect data with no damage and effects on plants. However, their limited carrying and battery capacities restrict their performance in larger areas. Therefore, using multiple UAVs, especially in the form of a swarm is more significant for monitoring larger areas such as crop fields and forests. The diversity of research studies necessitates a literature review for more progress and contribution in the agricultural field. In this… More >

Lianghao Hua^1,2, Jianfeng Zhang^1,*, Dejie Li³, Xiaobo Xi¹

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2129-2157, 2024, DOI:10.32604/cmes.2023.030535

Abstract With the increasing prevalence of high-order systems in engineering applications, these systems often exhibit significant disturbances and can be challenging to model accurately. As a result, the active disturbance rejection controller (ADRC) has been widely applied in various fields. However, in controlling plant protection unmanned aerial vehicles (UAVs), which are typically large and subject to significant disturbances, load disturbances and the possibility of multiple actuator faults during pesticide spraying pose significant challenges. To address these issues, this paper proposes a novel fault-tolerant control method that combines a radial basis function neural network (RBFNN) with a second-order ADRC and leverages a… More > Graphic Abstract

Baofeng Ji^1,2,3,*, Ying Wang^1,2,3, Weixing Wang¹, Shahid Mumtaz⁴, Charalampos Tsimenidis⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1885-1905, 2024, DOI:10.32604/cmes.2023.030872

Abstract The utilization of mobile edge computing (MEC) for unmanned aerial vehicle (UAV) communication presents a viable solution for achieving high reliability and low latency communication. This study explores the potential of employing intelligent reflective surfaces (IRS) and UAVs as relay nodes to efficiently offload user computing tasks to the MEC server system model. Specifically, the user node accesses the primary user spectrum, while adhering to the constraint of satisfying the primary user peak interference power. Furthermore, the UAV acquires energy without interrupting the primary user’s regular communication by employing two energy harvesting schemes, namely time switching (TS) and power splitting… More >

Ying Zhang¹, Weiming Niu², Supu Xiu^1,3, Guangchen Mu^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1865-1884, 2024, DOI:10.32604/cmes.2023.030114

Abstract In this paper, we investigate the energy efficiency maximization for mobile edge computing (MEC) in intelligent reflecting surface (IRS) assisted unmanned aerial vehicle (UAV) communications. In particular, UAV can collect the computing tasks of the terrestrial users and transmit the results back to them after computing. We jointly optimize the users’ transmitted beamforming and uploading ratios, the phase shift matrix of IRS, and the UAV trajectory to improve the energy efficiency. The formulated optimization problem is highly non-convex and difficult to be solved directly. Therefore, we decompose the original problem into three sub-problems. We first propose the successive convex approximation… More >

Ping Li¹, Kefeng Guo^2,*, Feng Zhou¹, Xueling Wang³, Yuzhen Huang⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1849-1864, 2024, DOI:10.32604/cmes.2023.029801

Abstract Integrated satellite unmanned aerial vehicle relay networks (ISUAVRNs) have become a prominent topic in recent years. This paper investigates the average secrecy capacity (ASC) for reconfigurable intelligent surface (RIS)-enabled ISUAVRNs. Especially, an eve is considered to intercept the legitimate information from the considered secrecy system. Besides, we get detailed expressions for the ASC of the regarded secrecy system with the aid of the reconfigurable intelligent. Furthermore, to gain insightful results of the major parameters on the ASC in high signal-to-noise ratio regime, the approximate investigations are further gotten, which give an efficient method to value the secrecy analysis. At last,… More >