DESIGN, CONSTRUCTION AND EVALUATION OF AN AUTONOMOUS WI-FI CONTROLLED SEEDER
Abstract
Agricultural automation and the development of intelligent equipment have stood out as promising alternatives to increase operational efficiency, reduce costs, and improve the precision of mechanized field operations, especially in small-scale production systems. In this context, the objective of this study was to develop and evaluate, under laboratory conditions, a low-cost autonomous seeder prototype designed to integrate mobility, connectivity, and electronic control into the sowing process. The study comprised the stages of development, prototype manufacturing, and laboratory testing. Maximum displacement speed, seed metering rate, and energy consumption during operation were evaluated. The prototype reached a maximum displacement speed of 0.37 m s⁻¹ and a metering rate of up to 150 seeds min⁻¹, achieving 100% efficiency under the tested conditions. The maximum required power was 30.72 W, demonstrating low energy consumption. The control system was based on an Atmega328 microcontroller associated with the Arduino platform, allowing remote operation through a Wi-Fi network. The results demonstrate the technical feasibility of the prototype and indicate potential application in small-scale agricultural systems, especially on farms that require accessible and automated solutions.
References
ALRESHIDI, E. Smart Sustainable Agriculture (SSA) Solution Underpinned by Internet of Things (IoT) and Artificial Intelligence (AI). International Journal of Advanced Computer Science and applications, v.10, n.5, p.93-102, 2019. https://doi.org/10.48550/arXiv.1906.03106 DOI: https://doi.org/10.14569/IJACSA.2019.0100513
ARAÚJO, S. A. de.; LIBRANTZ, A. F. H. Visão e inteligência computacionais aplicadas a navegação autônoma de robôs. Exacta, v.4, n.2, p.343-352, 2006. Disponível em: https://uninove.emnuvens.com.br/exacta/article/view/768/671 Acesso em: 19 mai. 2026. DOI: https://doi.org/10.5585/exacta.v4i2.768
BAI, y.; ZHANG, B.; XU, N.; ZHOU, J.; SHI, J.; DIAO, Z. Vision-based navigation and guidance for agricultural autonomous vehicles and robots: A review. Computers and Electronics in Agriculture, v.2025, 107584, 2023. https://doi.org/10.1016/j.compag.2022.107584 DOI: https://doi.org/10.1016/j.compag.2022.107584
BARROS, Felipe Bonfati de. Identificação de perigos e riscos para tomada de decisão em operações de semeadoras autônomas. 2025. Dissertação (Mestrado em Engenharia Agrícola) – Faculdade de Engenharia Agrícola, Universidade Estadual de Campinas, Campinas, São Paulo, 2025. Disponível em: https://hdl.handle.net/20.500.12733/41408 Acesso em: 10 abr. 2026.
BERNHARDT, H.; BOZKURT, M.; BRUNSCH, R.; COLANGELO, E.; HERRMANN, A.; HORSTMANN, J.; KRAFT, M.; MARQUERING, J.; STECKEL, T.; TAPKEN, H.; WELTZIEN, C.; WESTERKAMP, C. Challenges for agriculture through industry 4.0. Agronomy, v.11, n.10, p.1935. 2021. https://doi.org/10.3390/agronomy11101935 DOI: https://doi.org/10.3390/agronomy11101935
DE MATTOS, E.; WALBER, M. Desenvolvimento do conceito de uma semeadora de precisão. Brazilian Journal of Development, v. 8, n. 7, p.51985-52003, 2022. https://doi.org/10.34117/bjdv8n7-218 DOI: https://doi.org/10.34117/bjdv8n7-218
FINCH-SAVAGE, W. E.; BASSEL, G. W. Seed vigour and crop establishment: extending performance beyond adaptation. Journal of Experimental Botany, v.67, n.3, p.567-591, 2016.
https://doi.org/10.1093/jxb/erv490 DOI: https://doi.org/10.1093/jxb/erv490
FUJINAGA, T. Autonomous navigation method for agricultural robots in high-bed cultivation environments. Computers and Electronics in Agriculture, v. 231, p.110001, 2025.
https://doi.org/10.1016/j.compag.2025.110001 DOI: https://doi.org/10.1016/j.compag.2025.110001
HAN, J.H.; PARK, C-H.; KWON, J. H.; LEE, J.; KIM, T. S.; JANG, Y. Y. Performance evaluation of autonomous driving control algorithm for a crawler-type agricultural vehicle based on low-cost multi sensor fusion positioning. Applied Sciences, v.10, n.13, p.4667, 2020. https://doi.org/10.3390/app10134667 DOI: https://doi.org/10.3390/app10134667
HASAN, MD. M.; ISLAM, U. M.; SADEQ, M. J. Towards technological adaptation of advanced farming through AI, IoT, and robotics: A comprehensive overview. In: Artificial Intelligence and Smart Agriculture Tecnology Book, Chapter 2. 2022, 27p. Disponível em: https://arxiv.org/pdf/2202.10459 Acesso em: 19 mai. 2026.
HUSSAIN, S.; CHEN, Y.; YU, X.; FARID, M. U.; GHAFOOR, A.; ALSHAMALI, S. J.; MUNIR, T.; HU, J. Design optimization and aerodynamic investigations of air suction seed metering devices system through CFD-DEM approach. Smart Agricultural Technology, v.12, p.101082, 2025.
https://doi.org/10.1016/j.atech.2025.101082 DOI: https://doi.org/10.1016/j.atech.2025.101082
MARTINS, F. F.; CARVALHO, T. M.; CELECIA, A.; OLIVEIRA, A. I. S.; BARBOSA, G. B. P.; VELLASCO, M. M. B.; CAARLS, W.; FIGUEIREDO, K.; LEITE, A. C. Sistema de navegação autônoma para o robô agrícola Soybot. In: XV Simpósio Brasileiro de Automação Inteligente. Sociedade Brasileira de Automática, v.1, n.1, 7p. Disponível em: https://wouter.caarls.org/files/martins2021.pdf https://doi.org/10.20906/sbai.v1i1.2646 Acesso em: 19 mai. 2026. DOI: https://doi.org/10.20906/sbai.v1i1.2646
PADHIARY M.; SAHA D.; KUMAR R.; SETHI L.N.; KUMAR A. Enhancing precision agriculture: A comprehensive review of machine learning and AI vision applications in all-terrain vehicle for farm automation. Smart Agricultural Technology, v.8, p.100483, 2024. https://doi.org/10.1016/j.atech.2024.100483 DOI: https://doi.org/10.1016/j.atech.2024.100483
PAHL, Gerhand.; BEITZ, Wolfgang.; FELDHUSEN, Jorg.; GROTE, H. Karl-Heinrich. Projeto na Engenharia. São Paulo: Edgard Blucher, 2005.
SCHNÉ, T.; JASKO, S. 3D printing in agriculture - review. Georgikon for Agriculture, v.27, n.2, p.45–54, 2023. Disponível em: https://journal.uni-mate.hu/index.php/gfa/article/view/4986 Acesso em: 20 fev. 2025.
QIN, W.; LI, Y.; QIAN, C.; FAN, Z.; YAN, D.; ZOU, G.; LIU, S.; WANG, Z.; ZANG, Y.; ZHANG, M. The development of an air suction precision seed-metering device for rice plot breeding. Agronomy, v.15, n.7, p.1642, 2025. https://doi.org/10.3390/agronomy15071642 DOI: https://doi.org/10.3390/agronomy15071642
YAN, J.; ZHANG, W.; LIU, Y.; PAN, W.; HOU, X.; LIU, Z. Autonomous trajectory tracking control method for an agricultural robotic vehicle. International Journal of Agricultural and Biological Engineering, v.17, n.1, p. 215–224, 2024. Disponível em: https://ijabe.org/index.php/ijabe/article/view/7296 Acesso em: 10 abr. 2026. DOI: https://doi.org/10.25165/j.ijabe.20241701.7296
ZHA, X.; LI, J.; ZHAO, H.; CHEN, L.; YANG, W.; YANG, R.; LIU, W. Design optimization of an air-suction type seeder for rice breeding plots based on the discrete element method (DEM). Smart Agricultural Technology, v.12, p.101658, 2025. https://doi.org/10.1016/j.atech.2025.101658 DOI: https://doi.org/10.1016/j.atech.2025.101658
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