Perancangan Sistem Kendali Dehumidifikasi Ruangan Berbasis ESP32 dan IoT (Design of a Room Dehumidification Control System Based on ESP32 and IoT)
DOI:
https://doi.org/10.68437/jejpte.v6i2.23Keywords:
ESP32, Internet of Things, humidity control, dehumidification, indoor environmentAbstract
High indoor air humidity can reduce thermal comfort and potentially affect occupants, equipment, and materials. This study aimed to develop and initially evaluate an Internet of Things (IoT)-based room air-drying system using a SoC ESP32 for automatic humidity monitoring and control. A prototype engineering approach was employed through system requirements analysis, hardware and software design, prototype development, IoT integration, and testing in a small-scale test room. The system integrates a DHT22 temperature-humidity sensor, ESP32, relay, air-drying actuator, and IoT dashboard for real-time monitoring. Initial testing showed that the system reduced relative humidity from 78.6% RH to 61.2% RH, corresponding to a reduction of 17.4 percentage points. The temperature decreased from 29.4°C to 28.8°C during the drying process. The measured sensor accuracy was 97.8% for temperature and 96.4% for relative humidity when compared with a reference measuring instrument, while the average actuator response time was 4.7 s from threshold detection to activation. The system successfully displayed temperature, humidity, and actuator status on the dashboard in real time and operated without significant disturbances during the test. However, the evaluation was limited to a small-scale test room and did not include settling time, overshoot, or long-term humidity fluctuation analysis. Therefore, the prototype demonstrates initial feasibility as a low-cost approach to automatic indoor humidity control and has potential for further development and testing under more diverse room conditions.Downloads
References
Cabezas, M. P., Carvajal, J. D., Vivas, F. Y., & Lopez, D. M. (2025). Smart monitoring system for temperature and relative humidity adapted to the specific needs of pharmaceutical services. IoT, 6(1), 15. https://doi.org/10.3390/iot6010015
Daniel, W., Pramono, A., Wijaya, J. F., & Wijaya, N. P. (2023). Integrating IoT-based devices for monitoring the humidity and temperature in the boarding house space. Procedia Computer Science, 227, 204–213. https://doi.org/10.1016/j.procs.2023.10.518
Daulay, M. S. H., Handasah, U., Manik, C. T. S., Sitopu, M. W., Sinurat, & Afdila, R. (2026). Sistem Pemantauan dan Kontrol Kualitas Air Akuarium Berbasis IoT Menggunakan Sensor Turbidity. (2026). JURNAL EDUNITRO Jurnal Pendidikan Teknik Elektro, 6(1), 57-64. https://ejurnal.unima.ac.id/index.php/edunitro/article/view/13520
Demanega, I., Mujan, I., Singer, B. C., Anđelković, A. S., Babich, F., & Licina, D. (2021). Performance assessment of low-cost environmental monitors and single sensors under variable indoor air quality and thermal conditions. Building and Environment, 187, 107415. https://doi.org/10.1016/j.buildenv.2020.107415
Di Leo, V., Speroni, A., Ferla, G., & Blanco Cadena, J. D. (2025). Design and validation of a compact, low-cost sensor system for real-time indoor environmental monitoring. Buildings, 15(19), 3440. https://doi.org/10.3390/buildings15193440
Figueiredo, R. E., Alves, A. A., Monteiro, V., Pinto, J. G., Afonso, J. L., & Afonso, J. A. (2021). Development and evaluation of smart home IoT systems applied to HVAC monitoring and control. EAI Endorsed Transactions on Energy Web, 8(34), 167205. https://doi.org/10.4108/eai.19-11-2020.167205
Furizal, F., Yudhana, A., dkk. (2023). Temperature and humidity control system with air conditioner based on fuzzy logic and Internet of Things. Journal of Robotics and Control, 4(3), 18327. https://doi.org/10.18196/jrc.v4i3.18327
Gabriel, M. F., Marques, G., Filipe, D., Felgueiras, F., Cardoso, J. P., Azeredo, J., dkk. (2024). Implementation of an IoT architecture for promoting healthy air quality in homes. Building and Environment, 266, 112040. https://doi.org/10.1016/j.buildenv.2024.112040
Grassi, B., Piana, E. A., Lezzi, A. M., & Pilotelli, M. (2022). A review of recent literature on systems and methods for the control of thermal comfort in buildings. Applied Sciences, 12(11), 5473. https://doi.org/10.3390/app12115473
Harianto, D., Bintang, H. S., Ardiyanto, A., & Widyawan, V. L. D. (2024). Development and evaluation of an ESP32-based temperature and humidity control unit for textile storage. International Journal of Engineering Continuity, 4(1), 1–19. https://doi.org/10.58291/ijec.v4i1.309
Hidayah, R. R., Nurcahyo, S., & Dewatama, D. (2024). Implementasi pengaturan suhu menggunakan mikrokontroler ESP32. Metrotech (Journal of Mechanical and Electrical Technology), 3(3), 106–115. https://doi.org/10.70609/metrotech.v3i3.5017
Lekamge, S. A., & Oswin, H. P. (2025). Exploration of a practical approach to providing RH corrections to low cost sensor networks. npj Climate and Atmospheric Science, 8, 227. https://doi.org/10.1038/s41612-025-01115-8
Nan, F., Shen, H., & Zeng, C. (2026). An integrated low-cost air quality sensor and a multi-task calibration framework for particulate matter. Environment International, 207, 109981. https://doi.org/10.1016/j.envint.2025.109981
Patel, M. Y., Vannucci, P. F., Kim, J., Berelson, W., dkk. (2024). Towards a hygroscopic growth calibration for low-cost PM2.5 sensors. Atmospheric Measurement Techniques, 17(3), 1051–1060. https://doi.org/10.5194/amt-17-1051-2024
Sulzer, M., Christen, A., & Matzarakis, A. (2022). A low-cost sensor network for real-time thermal stress monitoring and communication in occupational contexts. Sensors, 22(5), 1828. https://doi.org/10.3390/s22051828
Taştan, M. (2025). Machine Learning–Based Calibration and Performance Evaluation of Low-Cost Internet of Things Air Quality Sensors. Sensors, 25(10), 3183. https://doi.org/10.3390/s25103183
Tsang, T. W., Mui, K. W., Wong, L. T., Chan, A. C. Y., & Chan, R. C. W. (2024). Real-time indoor environmental quality monitoring using an IoT-based wireless sensing network. Sensors, 24(21), 6850. https://doi.org/10.3390/s24216850
Zaharieva, S., Georgiev, I., Georgiev, S., Borodzhieva, A., & Todorov, V. (2025). A method for forecasting indoor relative humidity for improving comfort conditions and quality of life. Atmosphere, 16(3), 315. https://doi.org/10.3390/atmos16030315
Zhang, J., Kwok, H. H. L., Luo, H., Tong, J. C. K., & Cheng, J. C. P. (2022). Automatic relative humidity optimization in underground heritage sites through ventilation system based on digital twins. Building and Environment, 216, 108999. https://doi.org/10.1016/j.buildenv.2022.108999
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