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All Journal Internet of Things and Artificial Intelligence Journal
Tiga, Marianus
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Automatic Wastewater Control System for Soil Fertility use Fuzzy Logic and IoT-Based Tiga, Marianus
Internet of Things and Artificial Intelligence Journal Vol. 1 No. 3 (2021): Volume 1 Issue 3, 2021 [August]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1374.264 KB) | DOI: 10.31763/iota.v1i3.500

Abstract

The process of controlling the flow of waste in irrigation canals is one form of effort to support the sustainability of plant growth on garden beds. Farmers use many strategies or efforts to maintain fertility and plant growth to obtain more increased and productive yields. Based on research, clean water from rivers in irrigation canals that pass through residential areas to produce wastewater before it reaches plants. Moreover, a process, less healthy for plant growth than clean water irrigation channels with normal pH (Potential Hydrogen) required by plants. Setting pH and soil moisture according to plant needs, i.e., 6.5-7 for water pH and 50%-70% for soil moisture. This value is the best step in plant growth care; an irrigation canal is made that can measure water pH using sensor pH and soil moisture by using a soil moisture sensor and can normalize water pH and soil moisture according to plant needs. The pH down pump automatically pours acidic pH when the pH reading is alkaline and vice versa; the up pump automatically pours acid when the pH reading is acidic. To measure the water level in the reservoir, use an ultrasonic sensor to not seep out of the reservoir because it is full. This tool is equipped with a pump to channel water from the wastewater reservoir to the water pH measurement reservoir and proceed to the plants, where fuzzy logic works to regulate the speed of the plant watering pump with input obtained from soil moisture sensor readings and temperature sensors. Finally, control using the Esp32 MCU Node by being monitored using the Blynk application displayed on the android.
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