INTERNET OF THINGS-BASED AIR QUALITY MONITORING SYSTEM USING ESP32 AND PPD42 SENSOR TO SUPPORT OCCUPATIONAL SAFETY IN THE CRUSHER ROOM AREA

Air quality monitoring is an important aspect of supporting occupational safety and health (OSH), particularly in industrial areas with potential exposure to particulate matter, such as Crusher Rooms. This study implemented an Internet of Things (IoT)-based air quality monitoring system using a PPD42/PPD42NS sensor and an ESP32 microcontroller. The system measures PM1.0 and PM2.5 concentrations, transmits data via a Wi-Fi network to a server, stores historical measurement data, and displays information through a web-based dashboard. System testing covered sensor functionality, IoT communication, database operations, dashboard performance, and field monitoring. The results demonstrated that the system successfully recorded 774 historical monitoring data entries, with an average PM2.5 concentration of 22.70 µg/m³ and a maximum concentration of 150.89 µg/m³. The developed system can serve as a prototype for real-time airborne particulate matter monitoring to support the evaluation of workplace environmental conditions.

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Publication Details

Journal
Simtek jurnal sistem informasi dan teknik komputer
Published
2026-11-02
DOI
https://doi.org/10.51876/simtek.v11i2.1890
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
Field-Weighted Citation Impact
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article

INTERNET OF THINGS-BASED AIR QUALITY MONITORING SYSTEM USING ESP32 AND PPD42 SENSOR TO SUPPORT OCCUPATIONAL SAFETY IN THE CRUSHER ROOM AREA

Ilin Sukma, Henny Henny, Muhammad Habibi
3 links
Simtek jurnal sistem informasi dan teknik komputer
Air Quality Monitoring and Forecasting
article

INTERNET OF THINGS-BASED AIR QUALITY MONITORING SYSTEM USING ESP32 AND PPD42 SENSOR TO SUPPORT OCCUPATIONAL SAFETY IN THE CRUSHER ROOM AREA

Ilin Sukma, Henny Henny, Muhammad Habibi
article en

Abstract

Air quality monitoring is an important aspect of supporting occupational safety and health (OSH), particularly in industrial areas with potential exposure to particulate matter, such as Crusher Rooms. This study implemented an Internet of Things (IoT)-based air quality monitoring system using a PPD42/PPD42NS sensor and an ESP32 microcontroller. The system measures PM1.0 and PM2.5 concentrations, transmits data via a Wi-Fi network to a server, stores historical measurement data, and displays information through a web-based dashboard. System testing covered sensor functionality, IoT communication, database operations, dashboard performance, and field monitoring. The results demonstrated that the system successfully recorded 774 historical monitoring data entries, with an average PM2.5 concentration of 22.70 µg/m³ and a maximum concentration of 150.89 µg/m³. The developed system can serve as a prototype for real-time airborne particulate matter monitoring to support the evaluation of workplace environmental conditions.

Simtek jurnal sistem informasi dan teknik komputerVol. 11(2)
STMIK Catur Sakti Kendari (ID)
Industry, innovation and infrastructure, Good health and well-being
Openalex Percentile: Top 24%
Air Quality Monitoring and Forecasting
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