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Anindya Tara Danendra Alamsyah
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Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Engineering Library & Information Science Other

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IoT-Based Air Pollution Trend Analysis: A Case Study in Residential Areas of Karawang Industrial Estate Anindya Tara Danendra Alamsyah; Andi Susilo
Journal TIFDA (Technology Information and Data Analytic) Vol 3 No 1 (2026): Journal Technology Information and Data Analytic
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v3i1.140

Abstract

Air quality degradation in industrial zones poses a significant health risk to surrounding residential communities. Karawang, as a major manufacturing hub in West Java, faces challenges in monitoring particulate matter and gas emissions due to the high cost and limited coverage of standard monitoring stations. This study aims to design a low-cost Internet of Things (IoT) system to monitor and analyze air pollution trends in the residential buffer zones of the Karawang Industrial Estate. The proposed system integrates an ESP32 microcontroller with multispectral sensors, including MQ-135 for hazardous gases, PMS5003T for particulate matter (PM2.5/PM10), and DHT22 for meteorological variables. Data is transmitted in real-time to a web-based server using a non-blocking transmission algorithm to ensure data integrity. The results demonstrate that the system reliably captures diurnal fluctuations in air quality. Trend analysis reveals a consistent pattern of increased pollutant concentration during morning (06:00–09:00) and late-night (19:00–22:00) periods, correlated with anthropogenic activities and meteorological phenomena such as temperature inversion. While the daily average Air Quality Index (AQI) predominantly falls within the "Moderate" category, episodic spikes reaching "Unhealthy for Sensitive Groups" were observed, highlighting the necessity for granular, real-time monitoring for public health mitigation.
Co-Authors andi susilo