Citation

Ahmad, Wasim and Ali, Farman and Ullah, Yasir and Khan, Muhammad Asghar and Khan, Mansoor and Khan, Salabat and Khan, Muhammad Attique and Ali, Aitizaz and Almansour, Shahad (2025) IoUT and Collaborative Cloud Computing based UAV Channel Modeling for Agriculture Communication. IEEE Transactions on Consumer Electronics. p. 1. ISSN 0098-3063

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Abstract

gricultural systems using unmanned aerial vehicles (UAVs) for communication face significant challenges in channel modeling and resource management, particularly in dynamic environments. Traditional frameworks overlook factors such as terrain variability, vegetation growth, and atmospheric conditions, leading to unreliable signal propagation and inefficient network performance. Moreover, UAV operations are constrained by limited energy, and conventional optimization methods fail to address the adaptive allocation of resources in heterogeneous networks (HetNets). This paper proposes a novel framework for UAV channel modeling in agriculture communication systems, applying the Internet of UAV Things (IoUT) and collaborative cloud computing to improve communication reliability and efficiency. The framework dynamically models signal propagation by using machine learning-based predictive algorithms, incorporating terrain features, vegetation density, and weather conditions. A genetic algorithm-long short-term memory network (GA-LSTM) optimization technique further enhances UAV operations, balancing coverage, energy efficiency, and system reliability for smarter and sustainable agricultural networks. The mathematical derivations are performed for channel modeling, UAV mobility, coverage, and IoUT-based cloud computing. Next, the virtual scenario is designed to enhance the accuracy of IoUT-based agriculture communication.

Item Type:	Article
Uncontrolled Keywords:	Agriculture Communication
Subjects:	S Agriculture > S Agriculture (General)
Divisions:	Faculty of Engineering and Technology (FET) Faculty of Artificial Intelligence & Engineering (FAIE)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	27 Aug 2025 05:11
Last Modified:	27 Aug 2025 05:11
URII:	http://shdl.mmu.edu.my/id/eprint/14464

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