Creación de un sistema de información sobre cultivos apoyado en Inteligencia Artificial e IOT

Raúl Rosique de Dios; Livi Desi Alor Salaya; Karina Almeyda Vázquez; Nicolas Galindo Cruz; Ana Ruth Ulloa Pimienta

doi:10.61117/ipsumtec.v9i1.450

Authors

Raúl Rosique de Dios National Technological Institute of Mexico https://orcid.org/0009-0007-3314-0674
Livi Desi Alor Salaya National Technological Institute of Mexico https://orcid.org/0009-0003-3462-8349
Karina Almeyda Vázquez National Technological Institute of Mexico
Nicolas Galindo Cruz National Technological Institute of Mexico
Ana Ruth Ulloa Pimienta National Technological Institute of Mexico https://orcid.org/0000-0003-1375-4736

DOI:

https://doi.org/10.61117/ipsumtec.v9i1.450

Keywords:

Agriculture 4.0, Sustainable Development, Artificial Intelligence, Internet of Things, LoRaWAN, Computer Vision

Abstract

Currently, not only Mexico, but many other countries face significant agricultural challenges stemming from climate change, the emergence of pests, and low levels of automation in production processes. Given this scenario, this research proposes the creation of a crop information system supported by artificial intelligence, with the aim of promoting rural innovation and strengthening food security through accessible and scalable technological solutions. Agricultural activity continues to rely on traditional, unsustainable methods, which limits the adoption of modern tools and hinders the transition to more efficient practices.

The study was developed using a three-phase methodology: the first phase involves the design of the IoT hardware, the second phase the development of the machine vision software, and the final phase the interpretation of the data for decision-making. The system proposes the development of an IoT transmitter-receiver device capable of transmitting analog and digital sensor data via LoRa radio communication, complemented by a YOLOv8-based machine vision system for detecting crop health. The integration of these technologies aims to optimize water use and advance agricultural sustainability. Python is also used to implement artificial intelligence algorithms that identify plant diseases and activate irrigation systems only when soil moisture requires it, reducing water waste. This approach contributes to building a more sustainable, efficient, and resilient agricultural model, capable of responding to the sector's current and future needs, positioning technological innovation as a strategic pillar for rural development and food security in Mexico.

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Author Biographies

Raúl Rosique de Dios , National Technological Institute of Mexico

Computer systems engineer, master's student in artificial intelligence and industrial engineering, teacher-researcher at TecNM/ITS in Villa la Venta. Member of the State System of Researchers and the Register of Mentors for New Talent. Experience in software development, IoT prototypes, and computer vision.

Livi Desi Alor Salaya, National Technological Institute of Mexico

With a degree in Administration, she works in the English department, where she contributes to strengthening the relationship between the educational institution and its academic and productive environment. She is currently pursuing a Master's Degree in Industrial Engineering with a research focus on SME improvement. Her academic training is oriented toward process optimization, continuous improvement, and increasing organizational competitiveness.

Karina Almeyda Vázquez, National Technological Institute of Mexico

Industrial Engineer in the HSE area, as Industrial Safety Supervisor at BME SUBTEC DE BLUE MARINE on platforms and barges in the Campeche Sound. I am currently studying for a Master's Degree in Industrial Engineering, with a research focus on improving SMEs, strengthening management, technological adoption, innovation, and financing to boost their competitiveness, survival, and sustainable growth.

Nicolas Galindo Cruz, National Technological Institute of Mexico

Industrial engineer, administrator at TecNM La Venta campus, with experience in non-destructive testing and industrial safety in onshore and offshore oil facilities. Currently pursuing a master's degree in industrial engineering, with a research focus on SME improvements. His research work focuses on continuous improvement in the production area of the purification plant using the kaizen strategy.

Ana Ruth Ulloa Pimienta, National Technological Institute of Mexico

Doctor in Administration and Education, professor and researcher at TecNM/ITS in Villa la Venta. SNII candidate, member of the State System of Researchers, the Register of Mentors for New Talent, and the RedEvalúa network for CCYTET, she is a lecturer, workshop leader, and speaker at national and international conferences.

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