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Development of a fuzzy logic-based greenhouse system for optimizing bio-fertigation.

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Title: Development of a fuzzy logic-based greenhouse system for optimizing bio-fertigation.
Authors: Touhami, Achouak1,2,3 achouak.touhami@cuniv-tindouf.dz, Bourouis, Amina3,4 bourouis@univ-bechar.dz, Mahammedi, Amel4 mehammdiamel@gmail.com, Mechraoui, Sana4 sanamechraoui49@gmail.com, Touhami, Sana3,4 touhami.sana@univbechar.dz
Source: International Journal of Electrical & Computer Engineering (2088-8708). Oct2025, Vol. 15 Issue 5, p4555-4568. 14p.
Subjects: Fuzzy logic, Fertigation, Environmental databases, Agriculture, Water conservation, Greenhouses, Sustainability, Fertilizers
Abstract: Modern agriculture faces growing challenges in meeting food and resource demands, particularly with increasing pressure on water and fertilizer usage. This study proposes a fuzzy logic-based algorithm to optimize bio-fertigation by managing key greenhouse parameters: temperature, humidity, soil pH, and soil moisture. Implemented in MATLAB, the system automates the control of actuators (fan, heater, irrigation, fertilization and fertigation pumps) based on sensor data and fuzzy rules. Results show a 27.58% reduction in water use, 58.82% decrease in fertilizer consumption, and a 47.5% increase in tomato yield. Additionally, statistical error metrics mean absolute error (MAE), mean squared error (MSE), root mean squared error (RMSE), and mean absolute percentage error (MAPE) were reduced to zero, confirming the system's high precision and effectiveness in promoting sustainable agricultural practices. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
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Abstract:Modern agriculture faces growing challenges in meeting food and resource demands, particularly with increasing pressure on water and fertilizer usage. This study proposes a fuzzy logic-based algorithm to optimize bio-fertigation by managing key greenhouse parameters: temperature, humidity, soil pH, and soil moisture. Implemented in MATLAB, the system automates the control of actuators (fan, heater, irrigation, fertilization and fertigation pumps) based on sensor data and fuzzy rules. Results show a 27.58% reduction in water use, 58.82% decrease in fertilizer consumption, and a 47.5% increase in tomato yield. Additionally, statistical error metrics mean absolute error (MAE), mean squared error (MSE), root mean squared error (RMSE), and mean absolute percentage error (MAPE) were reduced to zero, confirming the system's high precision and effectiveness in promoting sustainable agricultural practices. [ABSTRACT FROM AUTHOR]
ISSN:20888708
DOI:10.11591/ijece.v15i5.pp4555-4568