Implementation of Fuzzy Logic for Chili Irrigation Integrated with Internet of Things

DOI:

https://doi.org/10.47709/cnahpc.v5i2.2518

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Keywords:

Fuzzy, internet of things, irrigation, agriculture, humidity

Abstract

Chili, mustard greens, and tomatoes have always been farmers' favored crops, despite their high water and labor demands. Adapt to these conditions by utilizing smart agriculture systems (SAS) agricultural techniques that involve technology such as automatic irrigation that regulates watering based solely on routine, regardless of land conditions. This type of control during the transitional season can lead to root rot and fungisarium disease on chile plants. In the form of an embedded system with internet of things (IoT) monitoring, a system incorporating artificial intelligence such as fuzzy logic is proposed as a solution. Fuzzy logic will regulate irrigation based on the land's humidity and temperature using computational mathematics. Beginning with the fuzzyification stage to map the sensor's temperature and humidity input values, fuzzy logic is applied. The creation of an inference engine in the NodeMcu 8266 microcontroller to interpret fuzzy rule statements in the form of aggregation of minimum conditions with the AND operator, followed by the combination of a single set value of 0 and 1 in the fuzzy system to produce an appropriate actuator response After the entire system has been prototyped, testing is conducted to determine the responsiveness of the fuzzy program code to changes in the simulated agricultural cultivation land ecosystem. This study found that the fuzzy logic program code embedded in the nodeMCU8266 microcontroller effectively controls the spraying duration of the pump in response to various simulated environmental conditions within 3.6 seconds.

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Published

2023-07-14

How to Cite

Prasetyo, A. ., Yusuf, A. R., Litanianda, Y. ., Sugianti, & Masykur, F. . (2023). Implementation of Fuzzy Logic for Chili Irrigation Integrated with Internet of Things. Journal of Computer Networks, Architecture and High Performance Computing, 5(2), 494–502. https://doi.org/10.47709/cnahpc.v5i2.2518

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Source: OpenAlex  · Updated 2026-11-08 03:58 UTC