Fuzzy based Irrigation and Lighting Systems for Indoor Farming

Jayalakshmi, B.; H, Haritha; Maniyeri, Abijith; Arjun, N

doi:10.1109/icirca48905.2020.9183154

Cited by 4 publications

(1 citation statement)

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“…The relationship between input and output is in the form of “If-Then” rules that are based on the dynamic performance of processes ( Potdar et al., 2017 ). Fuzzy logic has been used to manage environmental conditions in a range of agricultural circumstances, such as general crop- ( Singhala et al., 2014 ; Robles Algarín et al., 2017 ; Xu et al., 2017 ; Lakhiar et al., 2018 ), pest- ( Roussel et al., 2000 ; Shi et al., 2007 ; Jesus et al., 2008 ), and irrigation management ( Dengel, 2013 ; Bannerjee et al., 2018 ; Daud et al., 2018 ; Jayalakshmi et al., 2020 ). However, no studies have reported applying fuzzy logic to manage light quality according to different plant growth stages.…”

Section: Introductionmentioning

confidence: 99%

Development of a fuzzy logic-controlled system for home cultivation of sweet basil

Kim

Jeong²,

Park³

et al. 2022

Front. Plant Sci.

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As environmental pollution and the global population increase, and the COVID-19 pandemic becomes more severe, demands for indoor farming, especially home food gardening, have also increased. However, most research thus far has focused on large-scale food production, with very few studies having been conducted at the household scale. Also, the devices cultivating household crops with control systems in a continuous way, which minimize fluctuations of environmental conditions, have been rarely developed. Therefore, this study aimed to design a household cultivation system for sweet basil that is automatically and continuously controlled by fuzzy logic with a Raspberry Pi4. Three inputs (temperature, humidity, and growth stage) and seven outputs (fan, humidifier, heater 1, heater 2, LED red, green, and blue) were used with six rules, ensuring that three lights operated independently upon three growth stages. Simulation and actual operation were carried out, resulting in an appropriately controlled system that operated with few defects. In the case of an operation of the input variable, temperature and humidity were maintained at an average of 21.24 °C and 75.58%, respectively, and the LED operation for the growth stage was confirmed to be flawless. For verification of the designed fuzzy system, a comparison between the simulation and actual operation was performed to examine differences and identify problems. To this end, Pearson’s correlation coefficients were used, and the direction of correction of the fuzzy logic system was proposed. Through these results, the feasibility of a home cultivation system using fuzzy logic was demonstrated, and it is expected that further studies applying it will be conducted in the future.

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