IMPLEMENTASI SISTEM SMART VENTILATION BERBASIS IOT MENGGUNAKAN THRESHOLD KUALITAS UDARA

Muhammad Almas Albirra  Hamid; Dicky Aldian Pratama; Gian  Alghifari; Ravi Rabbani Aprialna; Anan Satria  Perkasa; Rahmad  Firdaus; Febby Apri Wenando

doi:10.37859/seis.v6i2.11039

Authors

Muhammad Almas Albirra Hamid Ilmu Komputer, Universitas Muhammadiyah Riau
Dicky Aldian Pratama Ilmu Komputer, Universitas Muhammadiyah Riau
Gian Alghifari Ilmu Komputer, Universitas Muhammadiyah Riau
Ravi Rabbani Aprialna Ilmu Komputer, Universitas Muhammadiyah Riau
Anan Satria Perkasa Ilmu Komputer, Universitas Muhammadiyah Riau
Rahmad Firdaus Ilmu Komputer, Universitas Muhammadiyah Riau
Febby Apri Wenando Sistem Informasi, Fakultas Teknologi Informasi Universitas Andalas

DOI:

https://doi.org/10.37859/seis.v6i2.11039

Keywords: Smart Ventilation, Internet of Things, Indoor Air Quality, Threshold-Based Control, ESP32

Abstract

Poor air quality in enclosed workspaces, particularly in Micro, Small, and Medium Enterprises (MSMEs) that operate CNC laser cutting machines for acrylic processing, poses potential health risks and reduces worker comfort. This study aims to design and implement an Internet of Things (IoT)–based Smart Ventilation system capable of automatically monitoring and controlling indoor air quality based on predefined threshold values. The system integrates air quality sensors to detect smoke or hazardous gases, an ESP32 microcontroller as the central processing unit, and an exhaust fan as the actuator. Sensor data are processed in real time and used as the basis for activating or deactivating the ventilation system, while monitoring information is displayed through an IoT platform for remote supervision. Experimental results indicate that the proposed system can accurately identify changes in air quality and respond automatically to hazardous conditions in accordance with the defined thresholds. The implementation of this system is expected to improve indoor air quality, support occupational health and safety, and enhance energy efficiency through condition-based ventilation control.

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