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  • Open Access

    ARTICLE

    Artificial Intelligence-Enabled Cooperative Cluster-Based Data Collection for Unmanned Aerial Vehicles

    R. Rajender1, C. S. S. Anupama2, G. Jose Moses3, E. Laxmi Lydia4, Seifedine Kadry5, Sangsoon Lim6,*

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3351-3365, 2022, DOI:10.32604/cmc.2022.030229

    Abstract In recent times, sixth generation (6G) communication technologies have become a hot research topic because of maximum throughput and low delay services for mobile users. It encompasses several heterogeneous resource and communication standard in ensuring incessant availability of service. At the same time, the development of 6G enables the Unmanned Aerial Vehicles (UAVs) in offering cost and time-efficient solution to several applications like healthcare, surveillance, disaster management, etc. In UAV networks, energy efficiency and data collection are considered the major process for high quality network communication. But these procedures are found to be challenging because… More >

  • Open Access

    ARTICLE

    Rice Bacterial Infection Detection Using Ensemble Technique on Unmanned Aerial Vehicles Images

    Sathit Prasomphan*

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 991-1007, 2023, DOI:10.32604/csse.2023.025452

    Abstract Establishing a system for measuring plant health and bacterial infection is critical in agriculture. Previously, the farmers themselves, who observed them with their eyes and relied on their experience in analysis, which could have been incorrect. Plant inspection can determine which plants reflect the quantity of green light and near-infrared using infrared light, both visible and eye using a drone. The goal of this study was to create algorithms for assessing bacterial infections in rice using images from unmanned aerial vehicles (UAVs) with an ensemble classification technique. Convolution neural networks in unmanned aerial vehicles image… More >

  • Open Access

    ARTICLE

    Autonomous Unmanned Aerial Vehicles Based Decision Support System for Weed Management

    Ashit Kumar Dutta1,*, Yasser Albagory2, Abdul Rahaman Wahab Sait3, Ismail Mohamed Keshta1

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 899-915, 2022, DOI:10.32604/cmc.2022.026783

    Abstract Recently, autonomous systems become a hot research topic among industrialists and academicians due to their applicability in different domains such as healthcare, agriculture, industrial automation, etc. Among the interesting applications of autonomous systems, their applicability in agricultural sector becomes significant. Autonomous unmanned aerial vehicles (UAVs) can be used for suitable site-specific weed management (SSWM) to improve crop productivity. In spite of substantial advancements in UAV based data collection systems, automated weed detection still remains a tedious task owing to the high resemblance of weeds to the crops. The recently developed deep learning (DL) models have… More >

  • Open Access

    ARTICLE

    Intelligent Deep Data Analytics Based Remote Sensing Scene Classification Model

    Ahmed Althobaiti1, Abdullah Alhumaidi Alotaibi2, Sayed Abdel-Khalek3, Suliman A. Alsuhibany4, Romany F. Mansour5,*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1921-1938, 2022, DOI:10.32604/cmc.2022.025550

    Abstract Latest advancements in the integration of camera sensors paves a way for new Unmanned Aerial Vehicles (UAVs) applications such as analyzing geographical (spatial) variations of earth science in mitigating harmful environmental impacts and climate change. UAVs have achieved significant attention as a remote sensing environment, which captures high-resolution images from different scenes such as land, forest fire, flooding threats, road collision, landslides, and so on to enhance data analysis and decision making. Dynamic scene classification has attracted much attention in the examination of earth data captured by UAVs. This paper proposes a new multi-modal fusion… More >

  • Open Access

    ARTICLE

    Object Tracking-Based “Follow-Me” Unmanned Aerial Vehicle (UAV) System

    Olubukola D. Adekola1,*, Onyedikachi Kenny Udekwu2, Oluwatobi Tolulope Saliu2, Damilola Williams Dada2, Stephen O. Maitanmi1, Victor Odumuyiwa3, Olujimi Alao2, Monday Eze2, Funmilayo Abibat Kasali4, Ayokunle Omotunde2

    Computer Systems Science and Engineering, Vol.41, No.3, pp. 875-890, 2022, DOI:10.32604/csse.2022.021029

    Abstract The applications of information technology (IT) tools and techniques have, over the years, simplified complex problem solving procedures. But the power of automation is inhibited by the technicality in manning advanced equipment. To this end, tools deliberately combating this inhibition and advancing technological growth are the Unmanned Aerial Vehicles (UAVs). UAVs are rapidly taking over major industries such as logistics, security, and cinematography. Among others, this is a very efficient way of carrying out missions unconventional to humans. An application area of this technology is the local film industry which is not producing quality movies… More >

  • Open Access

    ARTICLE

    IoT-Cloud Empowered Aerial Scene Classification for Unmanned Aerial Vehicles

    K. R. Uthayan1,*, G. Lakshmi Vara Prasad2, V. Mohan3, C. Bharatiraja4, Irina V. Pustokhina5, Denis A. Pustokhin6, Vicente García Díaz7

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5161-5177, 2022, DOI:10.32604/cmc.2022.021300

    Abstract Recent trends in communication technologies and unmanned aerial vehicles (UAVs) find its application in several areas such as healthcare, surveillance, transportation, etc. Besides, the integration of Internet of things (IoT) with cloud computing environment offers several benefits for the UAV communication. At the same time, aerial scene classification is one of the major research areas in UAV-enabled MEC systems. In UAV aerial imagery, efficient image representation is crucial for the purpose of scene classification. The existing scene classification techniques generate mid-level image features with limited representation capabilities that often end up in producing average results.… More >

  • Open Access

    ARTICLE

    A Secure Key Agreement Scheme for Unmanned Aerial Vehicles-Based Crowd Monitoring System

    Bander Alzahrani1, Ahmed Barnawi1, Azeem Irshad2, Areej Alhothali1, Reem Alotaibi1, Muhammad Shafiq3,*

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6141-6158, 2022, DOI:10.32604/cmc.2022.020774

    Abstract Unmanned aerial vehicles (UAVs) have recently attracted widespread attention in civil and commercial applications. For example, UAVs (or drone) technology is increasingly used in crowd monitoring solutions due to its wider air footprint and the ability to capture data in real time. However, due to the open atmosphere, drones can easily be lost or captured by attackers when reporting information to the crowd management center. In addition, the attackers may initiate malicious detection to disrupt the crowd-sensing communication network. Therefore, security and privacy are one of the most significant challenges faced by drones or the… More >

  • Open Access

    ARTICLE

    Optimal Path Planning for Intelligent UAVs Using Graph Convolution Networks

    Akshya Jothi, P. L. K. Priyadarsini*

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1577-1591, 2022, DOI:10.32604/iasc.2022.020974

    Abstract Unmanned Aerial Vehicles (UAVs) are in use for surveillance services in the geographic areas, that are very hard and sometimes not reachable by humans. Nowadays, UAVs are being used as substitutions to manned operations in various applications. The intensive utilization of autonomous UAVs has given rise to many new challenges. One of the vital problems that arise while deploying UAVs in surveillance applications is the Coverage Path Planning(CPP) problem. Given a geographic area, the problem is to find an optimal path/tour for the UAV such that it covers the entire area of interest with minimal… More >

  • Open Access

    ARTICLE

    Real-Time and Intelligent Flood Forecasting Using UAV-Assisted Wireless Sensor Network

    Shidrokh Goudarzi1,2,*, Seyed Ahmad Soleymani2,3, Mohammad Hossein Anisi4, Domenico Ciuonzo5, Nazri Kama6, Salwani Abdullah1, Mohammad Abdollahi Azgomi2, Zenon Chaczko7, Azri Azmi6

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 715-738, 2022, DOI:10.32604/cmc.2022.019550

    Abstract The Wireless Sensor Network (WSN) is a promising technology that could be used to monitor rivers’ water levels for early warning flood detection in the 5G context. However, during a flood, sensor nodes may be washed up or become faulty, which seriously affects network connectivity. To address this issue, Unmanned Aerial Vehicles (UAVs) could be integrated with WSN as routers or data mules to provide reliable data collection and flood prediction. In light of this, we propose a fault-tolerant multi-level framework comprised of a WSN and a UAV to monitor river levels. The framework is… More >

  • Open Access

    ARTICLE

    A Secure Communication Protocol for Unmanned Aerial Vehicles

    Navid Ali Khan1, N. Z. Jhanjhi1,*, Sarfraz Nawaz Brohi2, Abdulwahab Ali Almazroi3, Abdulaleem Ali Almazroi4

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 601-618, 2022, DOI:10.32604/cmc.2022.019419

    Abstract Mavlink is a lightweight and most widely used open-source communication protocol used for Unmanned Aerial Vehicles. Multiple UAVs and autopilot systems support it, and it provides bi-directional communication between the UAV and Ground Control Station. The communications contain critical information about the UAV status and basic control commands sent from GCS to UAV and UAV to GCS. In order to increase the transfer speed and efficiency, the Mavlink does not encrypt the messages. As a result, the protocol is vulnerable to various security attacks such as Eavesdropping, GPS Spoofing, and DDoS. In this study, we… More >

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