Rodríguez-Casavilca et al. (2025) Sistema inteligente de monitoreo ambiental y análisis de datos para la eficiencia del riego en agricultura de precisión

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Anales de la Facultad de Medicina (Facultad de Medicina San Fernando)
• Year: 2025
• Date: 2025-12-05
• Authors: Hipólito Martín Rodríguez-Casavilca, Brandon Mayer Flores Huamanñahui, Alexandra De la Gracia Rodríguez Guim
• DOI: 10.15381/electron.v21i1.31892

Research Groups

Not explicitly provided in the paper text.

Short Summary

This paper designs and implements a low-cost IoT-based smart environmental monitoring system for agriculture, providing real-time data and forecasting capabilities for variables like soil moisture. The system demonstrated its effectiveness in a real agricultural field by optimizing water resource usage through informed irrigation decisions.

Objective

• To optimize water resource usage in agriculture through continuous measurement of key environmental variables such as soil moisture, air temperature, relative humidity, solar radiation, and rainfall, using a low-cost IoT-based monitoring system.

Study Configuration

• Spatial Scale: Field scale (a real agricultural field).
• Temporal Scale: Continuous monitoring over an unspecified period.

Methodology and Data

• Models used: Basic predictive algorithms, including linear forecasting.
• Data sources: Calibrated sensors collecting observational data (soil moisture, air temperature, relative humidity, solar radiation, rainfall) from a real agricultural field.

Main Results

• A functional smart environmental monitoring system was designed and implemented using low-cost IoT technologies and microcontrollers.
• The system provides real-time visualization, automated reporting, and forecasting capabilities for soil moisture.
• Experimental results from a real agricultural field demonstrated time series visualization, linear forecasting, and optimized water consumption compared to traditional methods.
• The platform enables real-time decision-making for irrigation, contributing to water resource optimization.

Contributions

• Design and implementation of an accessible, low-cost IoT-based smart environmental monitoring system for precision agriculture.
• Integration of real-time environmental data visualization, automated reporting, and basic predictive algorithms for irrigation management.
• Demonstrated applicability and effectiveness in a real agricultural field, showing potential for optimizing water usage.
• Highlights accessibility for small producers and scalability potential through advanced machine learning techniques.

Funding

Not explicitly provided in the paper text.

Citation

@article{RodríguezCasavilca2025Sistema,
  author = {Rodríguez-Casavilca, Hipólito Martín and Huamanñahui, Brandon Mayer Flores and Guim, Alexandra De la Gracia Rodríguez and Rodríguez-Casavilca, Hipólito Martín and Huamanñahui, Brandon Mayer Flores and Guim, Alexandra De la Gracia Rodríguez},
  title = {Sistema inteligente de monitoreo ambiental y análisis de datos para la eficiencia del riego en agricultura de precisión},
  journal = {Anales de la Facultad de Medicina (Facultad de Medicina San Fernando)},
  year = {2025},
  doi = {10.15381/electron.v21i1.31892},
  url = {https://doi.org/10.15381/electron.v21i1.31892}
}

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