Khalid A. Alissa¹, Mohammed Maray², Areej A. Malibari³, Sana Alazwari⁴, Hamed Alqahtani⁵, Mohamed K. Nour⁶, Marwa Obbaya⁷, Mohamed A. Shamseldin⁸, Mesfer Al Duhayyim^9,*

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5349-5367, 2023, DOI:10.32604/cmc.2023.033532

Abstract Emerging technologies such as edge computing, Internet of Things (IoT), 5G networks, big data, Artificial Intelligence (AI), and Unmanned Aerial Vehicles (UAVs) empower, Industry 4.0, with a progressive production methodology that shows attention to the interaction between machine and human beings. In the literature, various authors have focused on resolving security problems in UAV communication to provide safety for vital applications. The current research article presents a Circle Search Optimization with Deep Learning Enabled Secure UAV Classification (CSODL-SUAVC) model for Industry 4.0 environment. The suggested CSODL-SUAVC methodology is aimed at accomplishing two core objectives such as secure communication via image… More >

Muhammad Abrar¹, Ziyad M. Almohaimeed^2,*, Ushna Ajmal¹, Rizwan Akram², Rooha Masroor³, Muhammad Majid Hussain⁴

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4847-4860, 2023, DOI:10.32604/cmc.2023.030242

Abstract Mobile edge cloud networks can be used to offload computationally intensive tasks from Internet of Things (IoT) devices to nearby mobile edge servers, thereby lowering energy consumption and response time for ground mobile users or IoT devices. Integration of Unmanned Aerial Vehicles (UAVs) and the mobile edge computing (MEC) server will significantly benefit small, battery-powered, and energy-constrained devices in 5G and future wireless networks. We address the problem of maximising computation efficiency in U-MEC networks by optimising the user association and offloading indicator (OI), the computational capacity (CC), the power consumption, the time duration, and the optimal location planning simultaneously.… More >

Lin Yuan¹, Qimeng Yu¹, Yao Zhang^2,*, Xiaochang Wang³, Ouguan Xu¹, Wenjing Li¹

Phyton-International Journal of Experimental Botany, Vol.92, No.3, pp. 747-761, 2023, DOI:10.32604/phyton.2023.025502

Abstract Thosea sinensis Walker (TSW) rapidly spreads and severely damages the tea plants. Therefore, finding a reliable operational method for identifying the TSW-damaged areas via remote sensing has been a focus of a research community. Such methods also enable us to calculate the precise application of pesticides and prevent the subsequent spread of the pests. In this work, based on the unmanned aerial vehicle (UAV) platform, five band images of multispectral red-edge camera were obtained and used for monitoring the TSW in tea plantations. By combining the minimum redundancy maximum relevance (mRMR) with the selected spectral features, a comprehensive spectral selection… More >

Javed Rashid^1,2, Imran Khan¹, Ghulam Ali³, Shafiq ur Rehman⁴, Fahad Alturise⁵, Tamim Alkhalifah^5,*

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1235-1257, 2023, DOI:10.32604/cmc.2023.032005

Abstract The guava plant has achieved viable significance in subtropics and tropics owing to its flexibility to climatic environments, soil conditions and higher human consumption. It is cultivated in vast areas of Asian and Non-Asian countries, including Pakistan. The guava plant is vulnerable to diseases, specifically the leaves and fruit, which result in massive crop and profitability losses. The existing plant leaf disease detection techniques can detect only one disease from a leaf. However, a single leaf may contain symptoms of multiple diseases. This study has proposed a hybrid deep learning-based framework for the real-time detection of multiple diseases from a… More >

Mohamed Amine Ouamri^1,2, Reem Alkanhel^3,*, Cedric Gueguen¹, Manal Abdullah Alohali⁴, Sherif S. M. Ghoneim⁵

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 453-467, 2023, DOI:10.32604/cmc.2023.031450

Abstract With the rapid development of emerging 5G and beyond (B5G), Unmanned Aerial Vehicles (UAVs) are increasingly important to improve the performance of dense cellular networks. As a conventional metric, coverage probability has been widely studied in communication systems due to the increasing density of users and complexity of the heterogeneous environment. In recent years, stochastic geometry has attracted more attention as a mathematical tool for modeling mobile network systems. In this paper, an analytical approach to the coverage probability analysis of UAV-assisted cellular networks with imperfect beam alignment has been proposed. An assumption was considered that all users are distributed… More >

A. K. Z Rasel Rahman¹, S. M. Nabil Sakif¹, Niloy Sikder¹, Mehedi Masud², Hanan Aljuaid³, Anupam Kumar Bairagi^1,*

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3259-3277, 2023, DOI:10.32604/iasc.2023.030142

Abstract Disasters may occur at any time and place without little to no presage in advance. With the development of surveillance and forecasting systems, it is now possible to forebode the most life-threatening and formidable disasters. However, forest fires are among the ones that are still hard to anticipate beforehand, and the technologies to detect and plot their possible courses are still in development. Unmanned Aerial Vehicle (UAV) image-based fire detection systems can be a viable solution to this problem. However, these automatic systems use advanced deep learning and image processing algorithms at their core and can be tuned to provide… More >

Mohamed H. Mousa^1,2,*, Mohamed K. Hussein²

CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.2, pp. 413-434, 2022, DOI:10.32604/cmes.2022.020639

Abstract Mobile-Edge Computing (MEC) displaces cloud services as closely as possible to the end user. This enables the edge servers to execute the offloaded tasks that are requested by the users, which in turn decreases the energy consumption and the turnaround time delay. However, as a result of a hostile environment or in catastrophic zones with no network, it could be difficult to deploy such edge servers. Unmanned Aerial Vehicles (UAVs) can be employed in such scenarios. The edge servers mounted on these UAVs assist with task offloading. For the majority of IoT applications, the execution times of tasks are often… More >

Binbin Lv, Jun Zha, Kaichun Zeng^*, Hongtao Guo, Li Yu and Peng Zhang

CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.1, pp. 1-29, 2022, DOI:10.32604/cmes.2022.020572

Abstract The high-performance morphing aircraft has become a research focus all over the world. The morphing aircraft, unlike regular unmanned aerial vehicles (UAVs), has more complicated aerodynamic characteristics, making itmore difficultto conduct its design, model analysis, and experimentation. This paper reviews the recent process and the current status of aeroelastic issues, numerical simulations, and wind tunnel test of morphing aircrafts. The evaluation of aerodynamic characteristics, mechanism, and relevant unsteady dynamic aerodynamic modeling throughout the morphing process are the primary technological bottlenecks formorphing aircrafts. The unstable aerodynamic forces have a significant impact on the aircraft handling characteristics, control law design, and flight… More >

Rania M Tawfik¹, Hazem A. A. Nomer², M. Saeed Darweesh^1,*, Ali Wagdy Mohamed^3,4, Hassan Mostafa^5,6

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5999-6013, 2022, DOI:10.32604/cmc.2022.028234

Abstract Unmanned Aerial Vehicles (UAVs) provide a reliable and energy-efficient solution for data collection from the Narrowband Internet of Things (NB-IoT) devices. However, the UAV’s deployment optimization, including locations of the UAV’s stop points, is a necessity to minimize the energy consumption of the UAV and the NB-IoT devices and also to conduct the data collection efficiently. In this regard, this paper proposes Gaining-Sharing Knowledge (GSK) algorithm for optimizing the UAV’s deployment. In GSK, the number of UAV’s stop points in the three-dimensional space is encapsulated into a single individual with a fixed length representing an entire deployment. The superiority of… More >

Fawad Salam Khan^1,4, Mohd Norzali Haji Mohd^1,*, Saiful Azrin B. M. Zulkifli², Ghulam E Mustafa Abro², Suhail Kazi³, Dur Muhammad Soomro¹

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5741-5759, 2022, DOI:10.32604/cmc.2022.024927

Abstract The evident change in the design of the autopilot system produced massive help for the aviation industry and it required frequent upgrades. Reinforcement learning delivers appropriate outcomes when considering a continuous environment where the controlling Unmanned Aerial Vehicle (UAV) required maximum accuracy. In this paper, we designed a hybrid framework, which is based on Reinforcement Learning and Deep Learning where the traditional electronic flight controller is replaced by using 3D hand gestures. The algorithm is designed to take the input from 3D hand gestures and integrate with the Deep Deterministic Policy Gradient (DDPG) to receive the best reward and take… More >