Impact of Fuzzy Tsukamoto in Controlling Room Temperature and Humidity

Abstract

Dry season is a season where the room temperature exceeds the needs of the body so that it is unpleasant, unhealthy and can interfere with human productivity. In addition, the efficiency of use and resource requirements are also a concern for some people. To overcome this problem, an automatic room temperature control device was created using the ESP32 microcontroller with Tsukamoto's fuzzy algorithm optimization as a data processing technique to produce optimal fan speeds in duty cycle units based on temperature and humidity conditions in realtime. Four tests by running a fan for 30 minutes on each showed that the average difference between the maximum and minimum temperatures in the room was 0.95°C, while the average difference between maximum and minimum humidity was 2.0%. In addition, the test graph shows that when the fan is rotated in a closed room without air circulation, the relative temperature change increases from the initial minute to the last minute of the test. Meanwhile, changes in relative humidity decrease, although fluctuations increase within 1-4 minutes. This study found that fans are not effective in lowering room temperature optimally. Therefore, it is recommended to replace with an exhaust fan in future research.