Teaching irrigation automation in small gardens using wireless sensor networks

Authors

DOI:

https://doi.org/10.62305/alcon.v5i5.894

Keywords:

irrigation; teaching; automation; sensors

Abstract

The teaching of irrigation automation in small gardens using wireless sensor networks focused on showing students how smart technologies applied to the care of green areas worked. The classes explained the basic principles of humidity, temperature, and light sensors, which recorded data from the environment and sent it to a central system. Students understood how these values made it possible to determine the right time to activate irrigation, avoiding waste and improving responsible water use. During the educational process, the concept of wireless sensor networks was presented, highlighting their ability to communicate without cables and cover different points in the garden. Actuators, such as electronically controlled valves, which were automatically activated according to the conditions detected, were also analyzed. Participants learned how to program operating rules, configure communication modules, and review the information generated by the system. They worked on the practical interpretation of data, which helped them relate theory to real decision-making in irrigation management. The experience allowed students to understand how automation contributed to the efficient maintenance of small spaces and how the integration of wireless sensors facilitated the creation of sustainable and technological solutions within the environmental field. This training strengthened their skills in basic electronics, programming, and information analysis applied to automation projects. The results showed that predictive maintenance with Artificial Intelligence reduced critical failures by 35%, improved energy efficiency, and significantly decreased incidents with potential environmental impact. An optimization in maintenance planning and a reduction in operating costs were observed. It was determined that the integration of LSTM and MLP neural networks, together with smart sensors and continuous monitoring systems, represented an effective and sustainable strategy to strengthen operational safety, increase equipment life, and contribute to environmental protection in industrial settings.

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References

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Published

2025-12-31

How to Cite

Paredes Regalado, A. I. ., Cadena Astudillo , M. I., Jácome Torres , M. A., & Obregón Gutiérrez , J. O. (2025). Teaching irrigation automation in small gardens using wireless sensor networks . Scientific Journal of Educational Innovation and Current Society "ALCON". ISSN 2960-8473, 5(5), 468–478. https://doi.org/10.62305/alcon.v5i5.894

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Original articles