<![CDATA[Drosera sessilifolia is a carnivorous plant that requires optimal environmental conditions, par-ticularly in terms of light intensity, temperature, and water level. This study aims to utilize the In-ternet of Things (IoT) to implement an environmental control system using Type-2 Fuzzy Logic for monitoring and controlling the environmental parameters of Drosera sessilifolia. The system uses an ESP32 microcontroller supported by several sensors, including a DS18B20 temperature sensor, an LDR light intensity sensor, and a water level sensor, to monitor environmental parameters ac-curately. The acquired data are processed using the Type-2 Fuzzy method to generate control deci-sions for actuators such as a heater, peltier, lamp, peristaltic pump, and fan. The Blynk platform is used to display environmental conditions, including temperature, light intensity, water level, and actuator decision status in real time. Based on the results of a 7-day indoor test conducted in the morning and at night, the average morning temperature was 30.04°C and the average nighttime temperature was 27.91°C, while the average light intensity was 1278 ADC in the morning and 2525.43 ADC at night, and the average water level was 1.16 cm in the morning and 0.99 cm at night. Based on 14 observations over 7 days, the system showed appropriate control responses in all observed scenarios, resulting in a 100% response success rate for the detected conditions. The novelty of this study lies in the implementation of an IoT-based Type-2 Fuzzy system specifically designed for the indoor cultivation of Drosera sessilifolia by simultaneously controlling temper-ature, light intensity, and water level. In addition, this study highlights the novelty of integrating Type-2 Fuzzy Logic and IoT for carnivorous plants, which remains very limited, especially for the cultivation of Drosera sessilifolia in a controlled indoor environment. The test results show that the system is capable of controlling temperature, light intensity, and water level effectively and responsively to environmental changes. The Type-2 Fuzzy method also produces stable and adap-tive control decisions. This system offers a solution for real-time indoor monitoring and environ-mental control of Drosera sessilifolia.]]>
