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Advancements in Industry-Agriculture 5.0: Utilizing Unmanned Ground and Aerial Vehicles for Sustainable Precision Agriculture Cover

Advancements in Industry-Agriculture 5.0: Utilizing Unmanned Ground and Aerial Vehicles for Sustainable Precision Agriculture

Open Access
|Dec 2025

Abstract

In this study, we underscore the significance of incorporating Unmanned Ground Vehicles (UGVs) and Unmanned Aerial Vehicles (UAVs) in agricultural practices, highlighting their potential to mitigate environmental impact, preserve resources, and fortify food security. The research explores the challenges and future possibilities associated with this technology, aiming to contribute to a more sustainable and productive agricultural sector. The integration of UGVs and UAVs into Industry-Agriculture 5.0 marks a transition towards a data-driven and environmentally conscious farming approach, promising a more sustainable future for agriculture.

The study also involves the development and testing of a prototype agricultural robot equipped with sensing capabilities. The integration encompasses mechanical, electronic, and software components, with the design crafted using Autodesk Inventor and SolidWorks. Electronic circuits are precisely designed in Proteus, and software development is carried out in Matlab and Visual C++. The chassis is constructed from aluminum and steel, and rigorous testing has been conducted at Aydin Adnan Menderes University and Manisa Viticulture Research Institute. The robot operates on electrical power, offering an 8-hour working capacity with a 49-minute recharge time. Notably, it features individual motors for each wheel, employs a differential drive method, and boasts 34.85 horsepower.

DOI: https://doi.org/10.14313/jamris-2025-034 | Journal eISSN: 2080-2145 | Journal ISSN: 1897-8649
Language: English
Page range: 35 - 51
Submitted on: Oct 16, 2023
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Accepted on: Dec 4, 2023
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Published on: Dec 24, 2025
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2025 Ismail Bogrekci, Pinar Demircioglu, published by Łukasiewicz Research Network – Industrial Research Institute for Automation and Measurements PIAP
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.