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  • Open Access

    ARTICLE

    Rice Spike Identification and Number Prediction in Different Periods Based on UAV Imagery and Improved YOLOv8

    Fuheng Qu1, Hailong Li1,*, Ping Wang2, Sike Guo2, Lu Wang2, Xiaofeng Li3,*

    CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3911-3925, 2025, DOI:10.32604/cmc.2025.063820 - 03 July 2025

    Abstract Rice spike detection and counting play a crucial role in rice yield research. Automatic detection technology based on Unmanned Aerial Vehicle (UAV) imagery has the advantages of flexibility, efficiency, low cost, safety, and reliability. However, due to the complex field environment and the small target morphology of some rice spikes, the accuracy of detection and counting is relatively low, and the differences in phenotypic characteristics of rice spikes at different growth stages have a significant impact on detection results. To solve the above problems, this paper improves the You Only Look Once v8 (YOLOv8) model,… More >

  • Open Access

    ARTICLE

    Collaborative Trajectory Planning for Stereoscopic Agricultural Multi-UAVs Driven by the Aquila Optimizer

    Xinyu Liu#, Longfei Wang#, Yuxin Ma, Peng Shao*

    CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 1349-1376, 2025, DOI:10.32604/cmc.2024.058294 - 03 January 2025

    Abstract Stereoscopic agriculture, as an advanced method of agricultural production, poses new challenges for multi-task trajectory planning of unmanned aerial vehicles (UAVs). To address the need for UAVs to perform multi-task trajectory planning in stereoscopic agriculture, a multi-task trajectory planning model and algorithm (IEP-AO) that synthesizes flight safety and flight efficiency is proposed. Based on the requirements of stereoscopic agricultural geomorphological features and operational characteristics, the multi-task trajectory planning model is ensured by constructing targeted constraints at five aspects, including the path, slope, altitude, corner, energy and obstacle threat, to improve the effectiveness of the trajectory… More >

  • Open Access

    ARTICLE

    Context-Aware Feature Extraction Network for High-Precision UAV-Based Vehicle Detection in Urban Environments

    Yahia Said1,*, Yahya Alassaf2, Taoufik Saidani3, Refka Ghodhbani3, Olfa Ben Rhaiem4, Ali Ahmad Alalawi1

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4349-4370, 2024, DOI:10.32604/cmc.2024.058903 - 19 December 2024

    Abstract The integration of Unmanned Aerial Vehicles (UAVs) into Intelligent Transportation Systems (ITS) holds transformative potential for real-time traffic monitoring, a critical component of emerging smart city infrastructure. UAVs offer unique advantages over stationary traffic cameras, including greater flexibility in monitoring large and dynamic urban areas. However, detecting small, densely packed vehicles in UAV imagery remains a significant challenge due to occlusion, variations in lighting, and the complexity of urban landscapes. Conventional models often struggle with these issues, leading to inaccurate detections and reduced performance in practical applications. To address these challenges, this paper introduces CFEMNet,… More >

  • Open Access

    ARTICLE

    Integrated Energy-Efficient Distributed Link Stability Algorithm for UAV Networks

    Altaf Hussain1, Shuaiyong Li2, Tariq Hussain3, Razaz Waheeb Attar4, Farman Ali5,*, Ahmed Alhomoud6, Babar Shah7

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2357-2394, 2024, DOI:10.32604/cmc.2024.056694 - 18 November 2024

    Abstract Ad hoc networks offer promising applications due to their ease of use, installation, and deployment, as they do not require a centralized control entity. In these networks, nodes function as senders, receivers, and routers. One such network is the Flying Ad hoc Network (FANET), where nodes operate in three dimensions (3D) using Unmanned Aerial Vehicles (UAVs) that are remotely controlled. With the integration of the Internet of Things (IoT), these nodes form an IoT-enabled network called the Internet of UAVs (IoU). However, the airborne nodes in FANET consume high energy due to their payloads and… More >

  • Open Access

    REVIEW

    AI-Based UAV Swarms for Monitoring and Disease Identification of Brassica Plants Using Machine Learning: A Review

    Zain Anwar Ali1,2,*, 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 - 26 January 2024

    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… More >

  • Open Access

    ARTICLE

    Fractional Gradient Descent RBFNN for Active Fault-Tolerant Control of Plant Protection UAVs

    Lianghao Hua1,2, Jianfeng Zhang1,*, Dejie Li3, Xiaobo Xi1

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2129-2157, 2024, DOI:10.32604/cmes.2023.030535 - 15 December 2023

    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 More > Graphic Abstract

    Fractional Gradient Descent RBFNN for Active Fault-Tolerant Control of Plant Protection UAVs

  • Open Access

    REVIEW

    A Survey on Sensor- and Communication-Based Issues of Autonomous UAVs

    Pavlo Mykytyn1,2,*, Marcin Brzozowski1, Zoya Dyka1,2, Peter Langendoerfer1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1019-1050, 2024, DOI:10.32604/cmes.2023.029075 - 17 November 2023

    Abstract The application field for Unmanned Aerial Vehicle (UAV) technology and its adoption rate have been increasing steadily in the past years. Decreasing cost of commercial drones has enabled their use at a scale broader than ever before. However, increasing the complexity of UAVs and decreasing the cost, both contribute to a lack of implemented security measures and raise new security and safety concerns. For instance, the issue of implausible or tampered UAV sensor measurements is barely addressed in the current research literature and thus, requires more attention from the research community. The goal of this… More >

  • Open Access

    Time-Efficient Blockchain Framework for Improved Data Transmission in Autonomous Systems

    Abdulrahman M. Abdulghani, Wilbur L. Walters, Khalid H. Abed*

    Journal of Blockchain and Intelligent Computing, Vol.1, pp. 1-13, 2023, DOI:10.32604/jbic.2023.041340 - 29 September 2023

    Abstract Blockchain technology is increasingly used to design trustworthy and reliable platforms for sharing information in a plethora of industries. It is a decentralized system that acts as an immutable record for storing data. It has the potential to disrupt a range of fields that rely on data, including autonomous systems like Unmanned Aerial Vehicles (UAVs). In this paper, we propose a framework based on blockchain and distributed ledger technology to improve transmission time and provide a secured and trusted method for UAVs to transfer data to the consumer efficiently while maintaining data reliability. The results More >

  • Open Access

    ARTICLE

    Enhancement of UAV Data Security and Privacy via Ethereum Blockchain Technology

    Sur Singh Rawat1,*, Youseef Alotaibi2, Nitima Malsa1, Vimal Gupta1

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1797-1815, 2023, DOI:10.32604/cmc.2023.039381 - 30 August 2023

    Abstract Unmanned aerial vehicles (UAVs), or drones, have revolutionized a wide range of industries, including monitoring, agriculture, surveillance, and supply chain. However, their widespread use also poses significant challenges, such as public safety, privacy, and cybersecurity. Cyberattacks, targeting UAVs have become more frequent, which highlights the need for robust security solutions. Blockchain technology, the foundation of cryptocurrencies has the potential to address these challenges. This study suggests a platform that utilizes blockchain technology to manage drone operations securely and confidentially. By incorporating blockchain technology, the proposed method aims to increase the security and privacy of drone… More >

  • Open Access

    ARTICLE

    RO-SLAM: A Robust SLAM for Unmanned Aerial Vehicles in a Dynamic Environment

    Jingtong Peng*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2275-2291, 2023, DOI:10.32604/csse.2023.039272 - 28 July 2023

    Abstract When applied to Unmanned Aerial Vehicles (UAVs), existing Simultaneous Localization and Mapping (SLAM) algorithms are constrained by several factors, notably the interference of dynamic outdoor objects, the limited computing performance of UAVs, and the holes caused by dynamic objects removal in the map. We proposed a new SLAM system for UAVs in dynamic environments to solve these problems based on ORB-SLAM2. We have improved the Pyramid Scene Parsing Network (PSPNet) using Depthwise Separable Convolution to reduce the model parameters. We also incorporated an auxiliary loss function to supervise the hidden layer to enhance accuracy. Then… More >

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