To address this problem, the development of an automated biological information control system using fuzzy logic for smart aquaponics is deemed necessary. The biological information present on the nutrient solution system such as pH and electrical conductivity are vital to plant health, thus, necessary to be monitored and controlled. Nutrient imbalance occurs in a recirculating aquaponic system due to Constant absorption of plants set on the growth bed.
The light control will be more accurate if the growth stage is estimated by machine vision with an RGB camera. Finally, light quality was controlled by the FLC based on three light regimes upon days of duration blue light for germination, red light for vegetative growth and green light for flowering stage. Besides, comparison between simulation and actual operation were carried out and it was noticed that heaters’ actual work was done inappropriately breaking the boundary of simulation. Because fan’s correlations with heaters, humidity and mist were lower than expected, it was assumed that the fan made a significant contribution to the problem. To address this problem, the rules and membership functions were analyzed by Pearson’s correlation coefficients. However, the controlled humidity should have been maintained at an approximately lower temperature of the level of 60 – 65 %. Furthermore, the mean value of inner humidity is 75.58 %, the outer humidity was 16.57 %. The results showed that inner temperature of the control uses airflow to maintain the temperature at approximately 21 – 26 ℃ (average of 21.24 ℃) compared to the outer temperature of 19.8 ℃.
Each growth stage required different light quality and density inducing different volatile compounds and flavors of plants.
The FLC ensured that the three lights operate for three different cultivating periods. The input variables were temperature, humidity, and growth stage (duration) and the output variables were fan, mist, two heaters (heater1 and heater2), and three RGB LEDs. For the FLC, three input and seven output variables were used. Fuzzy logic control (FLC) was adopted to resolve ambiguity and improve the environmental control of the inside chamber. This study aimed to design household hydroponic systems automatically controlled by fuzzy logic with Raspberry Pi 4 and using the Python programming language. Small-scale cultivation for households requires equal attention. However, most studies focus on industrial farming or large-scale production. Research on stable indoor cultivation systems that cannot be affected by outdoor climate conditions and efficient systems that can maximize production under space constraints is advancing rapidly. Cropping patterns to make farming more efficient that can be helpful to irrigate crops and more disease resistant varieties.Īs environmental pollution gets more severe demands for indoor farming have been rising with a subsequent increase in studies related to it. Plants grown in in the hydroponic system shows high growth as compared to the conventionally field-grown plants also increase the chances of sustainable agricultural development through green technology where large number of plants can be grown in the nutrient medium. It enables the original crop to strike again after harvesting and to raise another crop. Proper irrigation system also another agricultural approach for enriching the ecosystem. This approach can be helpful for targeting the soil-borne pathogens to maximize soil benefits.
#EBB AND FLOW SERIES#
Crop rotation depends on different factors such as rotating series and applied frequency of certain crops that improved the functional properties of microorganisms growth. Monocropping patterns increase the mass crop production due to higher yields by controlling the attack of different pests and improving the soil microbe diversity.
It also advances the soil agro ecological measurement and climatic conditions. Cropping pattern reflects the growing of genetically modified crops and ordinary crops in the different conditions of temperature and pH also affected the cultivation.
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