Machine Learning Algorithms and Their Effects on Crop Production in Agriculture: A Review

Nada M. Khalil Al-Ani; Sadik Kamel Gharghan; Ziad Qais Al-Abbasi; Razan Alenezi; Muhammed Abdelhameed

doi:10.51173/jt.v8i1.2797

Authors

Nada M. Khalil Al-Ani Electrical Engineering Technical College-Baghdad, Middle Technical University, Baghdad, Iraq
Sadik Kamel Gharghan Technical Engineering College for Artificial Intelligence, Middle Technical University, Baghdad, Iraq
Ziad Qais Al-Abbasi Technical College-Baqubah, Middle Technical University, Baghdad, Iraq
Razan Alenezi College of Petroleum and Engineering, Kuwait University, Kuwait
Muhammed Abdelhameed College of Engineering, Gulf University, Sanad 26489, Kingdom of Bahrain

DOI:

https://doi.org/10.51173/jt.v8i1.2797

Keywords:

Agriculture, Collaborative System, Comprehensive System, ML

Abstract

Agricultural production faces challenges, such as water scarcity, climate change, and the rising demand for food to feed the growing global population. Incorporating wireless sensor networks (WSNs), Unmanned Aerial Vehicles (UAVs), and Machine Learning (ML) enables an efficient Synergistic approach for crop monitoring, predicting, and managing. WSNs prefer environmental data instantaneously, UAVs provide data collection for large-scale aerial, and ML processes this data to make actionable decisions. The primary objective of this review is to explore the comprehensive effect of WSNs, UAVs, and ML in the agriculture sector, emphasizing crop yield, environmental sustainability, and optimizing resources. In addition, this review aims to detail the benefits and limitations of ML technology and its impact on farming. Integrating state-of-the-art technologies has expressed several key areas of significant potential, such as crop health monitoring, precision irrigation, yield prediction, disease and pest detection, and resource efficiency. Hence, the collaboration of recent technologies in modern farming significantly enhances monitoring and management in real-time, improves productivity and sustainability, and addresses global food security challenges. At the same time, this would shape agriculture's future through innovative promotion and more sustainable farming practices.

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Author Biographies

Nada M. Khalil Al-Ani, Electrical Engineering Technical College-Baghdad, Middle Technical University, Baghdad, Iraq

NADA M. KHALIL AL-ANI received the B.Sc. and MSc. degrees in Computer Engineering Techniques (CET), Middle Technical University, Baghdad, Iraq, in 2000 and 2007, respectively. She worked as an employment in the Baghdad Governorate Office since 2008. She is currently pursuing to get PhD Degree in CET. Her research interests include wireless sensor network, MIMO, antenna, smartphone application, machine learning, drone, path loss modeling, and agriculture application. [email protected]

Sadik Kamel Gharghan, Technical Engineering College for Artificial Intelligence, Middle Technical University, Baghdad, Iraq

SADIK KAMEL GHARGHAN (Member, IEEE) received the B.Sc. degree in electrical and electronics engineering and the M.Sc. degree in communication engineering from the University of Technology, Iraq, in 1990 and 2005, respectively, and the Ph.D. degree in communication engineering from Universiti Kebangsaan Malaysia (UKM), Malaysia, in 2016. He is currently with the Department of Medical Instrumentation Techniques, Electrical Engineering Engineering Technical College, Middle Technical University, Baghdad, Iraq, as a Professor. His research interests include energy-efficient wireless sensor networks, biomedical sensors, microcontroller applications, WSN localization based on artificial intelligence techniques and optimization algorithms, indoor and outdoor path loss modeling, harvesting technique, wireless power transfer, machine learning-based disease diagnosis, and drone in medical and agricultural applications. [email protected]

Ziad Qais Al-Abbasi, Technical College-Baqubah, Middle Technical University, Baghdad, Iraq

Ziad Qais Al-Abbasi received the B.Sc. degree in communication engineering from the College of Engineering, University of Diyala, Diyala, Iraq, in 2008, and the M.Sc. degree in telecommunication engineering from the University of Technology, Baghdad, Iraq, in 2011. In 2017, he acquired his PhD in Telecommunication systems at the School of Electrical and Electronic Engineering, The University of Manchester, U.K. He is currently serving as the head of the electromechanical Systems department at Baqubah Technical College (BTC), the Middle Technical University (MTU), (Iraq). His research interests include wireless communication, radio resource allocation, non-orthogonal multiple access (NOMA) systems, LORA assisted Smart Agriculture systems, massive multiple-input multiple-output systems (massive-MIMO), 5G and 6G networks. [email protected]

Razan Alenezi, College of Petroleum and Engineering, Kuwait University, Kuwait

Muhammed Abdelhameed, College of Engineering, Gulf University, Sanad 26489, Kingdom of Bahrain

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