aspg-3-3918-1791419283 20261008002803 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Fusion: Practice and Applications FPA 2770-0070 2692-4048 2026 21 1 Lina Warlina Faculty of Science and Technology, Universitas Terbuka, Tangerang Selatan 15437, Indonesia Sri Listyarini Faculty of Science and Technology, Universitas Terbuka, Tangerang Selatan 15437, Indonesia Mohamad Afendee Mohamed Faculty of Informatics and Computing, Universiti Sultan Zainal Abidin, Campus Besut, 22200 Terengganu, Malaysia Wan Suryani Wan Awang Faculty of Informatics and Computing, Universiti Sultan Zainal Abidin, Campus Besut, 22200 Terengganu, Malaysia Roslan Umar East Coast Environmental Research Institute (ESERI), Universiti Sultan Zainal Abidin, Gong Badak 21300, Malaysia Aceng Sambas Faculty of Informatics and Computing, Universiti Sultan Zainal Abidin, Campus Besut, 22200 Terengganu, Malaysia; Department of Mechanical Engineering, Universitas Muhammadiyah 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mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:Arial; mso-bidi-theme-font:minor-bidi; mso-ansi-language:TR;} Particulate Matter (PM) concentration significantly affects public health, exacerbating respiratory conditions and contributing to environmental challenges. This study presents a real-time Internet of Things (IoT)-based portable particulate matter monitoring device utilizing the PMS5003 sensor. The device measures PM1.0, PM2.5, and PM10 concentrations and uploads the data to the cloud at 15-second intervals for real-time visualization. A two-week observational study in South Tangerang, Indonesia, revealed peak PM2.5 and PM10 levels of 218 µg/m³ and 232 µg/m³, respectively, on weekdays, compared to a weekend low of 19.76 µg/m³ for PM2.5. Variations were influenced by anthropogenic factors, including vehicular and industrial activity. Data analysis showed a 78% reduction in PM2.5 levels during weekends, highlighting the impact of human activity on air quality. These findings underscore the impact of anthropogenic activities on air quality and demonstrate the effectiveness of IoT-based systems in environmental monitoring. The study highlights the potential for such technology to support data-driven strategies for pollution management and public health improvement. 2026 13 26 3918 https://creativecommons.org/licenses/by/4.0/ 10.54216/FPA.210102 https://www.americaspg.com/journal/3/article/3918 https://www.americaspg.com/storage/71752856000.pdf