Sistem Monitoring dan Pengaturan Kualitas Udara Dalam Ruangan Berbasis Internet of Things

Humans spend almost 90% of their time indoors, making indoor air quality very important for health. According to the Regulation of the Minister of Health of the Republic of Indonesia, the ideal indoor humidity is 40-60%, while experts recommend 45-65%. The maximum allowable level of carbon monoxide (CO) is 9 PPM and carbon dioxide (CO2) is 1000 PPM. Non-ideal air quality parameters can have a negative impact on health, so the use of tools such as air filters and humidifiers is highly recommended to maintain air quality. This research aims to develop an indoor air quality monitoring system with control in the form of an ESP32 module. The system is equipped with an MQ135 sensor to detect CO2 levels, an MQ7 sensor to detect CO levels, and a DHT22 sensor to measure temperature and humidity. Data from the sensor is displayed directly on the LCD and the smartphone app whose value comes from ThingSpeak. The system also has LEDs as indicators, an Exhaust Fan that activates when CO2 and CO levels exceed safe limits, and an automatic humidifier if the humidity is below the recommended value range. In addition, this device is equipped with an ultrasonic sensor to measure the water level in the humidifier and buzzer as an indicator when the water is low. The tool can also be controlled manually which can provide flexibility for users to adjust the air conditions as needed

Authors

Institutions

Publication Details

Journal
Jurnal Ampere
Published
2025-06-30
DOI
https://doi.org/10.31851/ampere.v10i1.18193
Primary Topic
IoT-based Control Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Sistem Monitoring dan Pengaturan Kualitas Udara Dalam Ruangan Berbasis Internet of Things

Yeni Irdayanti, Ahlika Azzahra, Johansyah Alrasyid
1 links
Jurnal Ampere
IoT-based Control Systems
article

Sistem Monitoring dan Pengaturan Kualitas Udara Dalam Ruangan Berbasis Internet of Things

Yeni Irdayanti, Ahlika Azzahra, Johansyah Alrasyid
article en

Abstract

Humans spend almost 90% of their time indoors, making indoor air quality very important for health. According to the Regulation of the Minister of Health of the Republic of Indonesia, the ideal indoor humidity is 40-60%, while experts recommend 45-65%. The maximum allowable level of carbon monoxide (CO) is 9 PPM and carbon dioxide (CO2) is 1000 PPM. Non-ideal air quality parameters can have a negative impact on health, so the use of tools such as air filters and humidifiers is highly recommended to maintain air quality. This research aims to develop an indoor air quality monitoring system with control in the form of an ESP32 module. The system is equipped with an MQ135 sensor to detect CO2 levels, an MQ7 sensor to detect CO levels, and a DHT22 sensor to measure temperature and humidity. Data from the sensor is displayed directly on the LCD and the smartphone app whose value comes from ThingSpeak. The system also has LEDs as indicators, an Exhaust Fan that activates when CO2 and CO levels exceed safe limits, and an automatic humidifier if the humidity is below the recommended value range. In addition, this device is equipped with an ultrasonic sensor to measure the water level in the humidifier and buzzer as an indicator when the water is low. The tool can also be controlled manually which can provide flexibility for users to adjust the air conditions as needed

Jurnal AmpereVol. 10(1)
Sriwijaya University (ID), Politeknik Negeri Sriwijaya (ID)
Openalex Percentile: Top 79%
IoT-based Control Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.