Implementation of Fuzzy Tsukamoto in the Design of Nutrient Control and Monitoring System for Aquaponics Based on the Internet of Things
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Abstract
Aquaponic is an important aquaculture technique because it is easy to apply, saves water, and allows the integration of plant roots to absorb waste nitrogen from fish waste as nutrients. However, temperature, pH, Total Dissolved Solids (TDS), and water level greatly affect plant growth. This research aims to design a control system to monitor plant nutrition and development in real-time using temperature, pH, TDS, and ultrasonic sensors and apply Tsukamoto Fuzzy model to overcome uncertainty in decision making based on sensor data. This research uses a quantitative approach with a design and development method. Data were collected through direct observation, interviews with aquaponic farmers, and related literature studies. The designed system successfully fulfills the need to control and monitor nutrients in aquaponic systems effectively. The system utilizes an ESP8266 module and various sensors (pH, TDS/PPM, temperature, and water level) to monitor water conditions in real-time and send the data to Firebase, which is then displayed on the application interface. Automatic control allows for quick adjustments to changing environmental conditions, ensuring an optimal environment for plant growth.
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