Abstrak Artikel
This study was conducted to develop and test an Internet of Things (IoT)-based automated irrigation and lighting system for tomato plants using the Tsukamoto Fuzzy Logic method. The system utilizes an ESP32 microcontroller; data is collected from a CJMCU-TEMT6000 light sensor and a soil moisture sensor, and then used to control a water pump and UV LED lights via PWM. Monitoring and control can be performed directly via the Firebase platform and an Android app. Test results show that the soil moisture sensor has an average error rate of 2.15% with an accuracy of 97.85%, and the overall sensor accuracy is approximately 94.66%. The IoT system responds stably with a latency ranging from 3.32 to 5.03 seconds. Experiments on three plants: Plant A, which used the system, grew stably with an average height of 20.5 cm and bore fruit; Plant B only grew leaves without bearing fruit; Plant C failed to bear fruit due to weather conditions such as heavy rain, strong winds, and excessive heat. These results demonstrate that the system operates automatically and flexibly, maintaining better conditions for tomato plants compared to manual methods or natural conditions.
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