Precision Agriculture 4.0: Implementation of IoT, AI, and Sensor Networks for Tomato Crop Prediction

Authors

  • Miguel Ángel Giménez Pérez Polytechnic University of Cartagena
  • Antonio Guerrero González Polytechnic University of Cartagena https://orcid.org/0000-0002-1485-4758
  • Francisco Javier Cánovas Rodríguez Polytechnic University of Cartagena
  • Inocencia María Martínez Leon Polytechnic University of Cartagena
  • Francisco Antonio Lloret Abrisqueta Polytechnic University of Cartagena https://orcid.org/0009-0001-3345-6069

DOI:

https://doi.org/10.12928/biste.v6i2.10954

Keywords:

Agriculture, Internet of Things, Artificial Intelligence, Sensor Networks, Prediction

Abstract

Precision agriculture introduces an innovative approach to farm management by involving the use of technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), and sensor networks to optimize resources and increase crop yields. In this context, the present study aimed to develop a tomato crop prediction system using IoT, AI, and sensor networks. A system architecture was designed, including distributed sensors, IoT gateways, and a cloud platform running AI models based on recurrent neural networks. These AI models were trained with environmental data and validated using actual harvest data. The results showed up that the model could predict weekly harvest volumes with an average error of 3.2% during the best 4-week period. The integration of IoT, AI, and sensor networks proved to be effective for accurate crop prediction and has potential for other applications in precision agriculture.

Author Biographies

Miguel Ángel Giménez Pérez, Polytechnic University of Cartagena

Mechanical Engineer and Master's in Industry 4.0 from the Polytechnic University of Cartagena, completing studies in 2024. He specializes in the application of 4.0 technologies in various industrial sectors, with a notable focus on agriculture.

Antonio Guerrero González, Polytechnic University of Cartagena

Associate Professor at the Department of Automation, Electrical Engineering, and Electronic Technology, and coordinates the master’s degree in Industry 4.0. He is a member of the Electrical Engineering and Renewable Energy Group, where he is dedicated to research and teaching in advanced technologies applied to automation and Industry 4.0. He contributes to the training of future engineers and the development of innovative projects in the field of Industry 4.0.

Francisco Javier Cánovas Rodríguez, Polytechnic University of Cartagena

Associate Professor at the Department of Automation, Electrical Engineering, and Electronic Technology, and coordinator of University Entrance Exams. He is part of the Agronomic and Marine Engineering Group, specializing in the application of advanced technologies in automation and the marine sector. His teaching and research work focuses on integrating innovative and sustainable solutions in engineering, significantly contributing to the academic and professional development of his students.

Inocencia María Martínez Leon, Polytechnic University of Cartagena

Associate Professor, Coordinator of Equality at the Vice-Rectorate of Faculty, and Degree Coordinator. In her role as an associate professor, María is dedicated to teaching and research, providing valuable knowledge and experiences to her students. As Equality Coordinator, she works to promote and ensure gender equity and inclusion within the university. Additionally, in her role as Degree Coordinator, she ensures the quality and achievement of the academic objectives of the study programs, contributing to the comprehensive and professional development of the university community.

Francisco Antonio Lloret Abrisqueta, Polytechnic University of Cartagena

Industrial and Automatic Electronic Engineer from the Polytechnic University of Cartagena (UPCT), currently pursuing a Master's in Industry 4.0 at the same institution, expected to graduate in 2024. Specialized in artificial intelligence, working as a researcher at UPCT.

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Published

2024-07-11

How to Cite

[1]
M. Ángel G. Pérez, A. G. González, F. J. C. Rodríguez, I. M. M. . Leon, and F. A. L. Abrisqueta, “Precision Agriculture 4.0: Implementation of IoT, AI, and Sensor Networks for Tomato Crop Prediction”, Buletin Ilmiah Sarjana Teknik Elektro, vol. 6, no. 2, pp. 172–181, Jul. 2024.

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Vol. 6 No. 2 (2024): June

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Copyright (c) 2024 Miguel Ángel Giménez Pérez, Antonio Guerrero González, Francisco Javier Cánovas Rodríguez, Inocencia María Martínez Leon, Francisco Antonio Lloret Abrisqueta

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