IoT-Based Monitoring and Control of Smoke Concentration in Fish Smoking Warehouses Using Fuzzy Logic and ESP32

Urifah Nur Rohmah; Faridatun Nadziroh; Budi Aswoyo; Anang Budikarso; Ida Anisah

doi:10.68129/jcsns.v1i1.51

Akses terbuka Jurnal

IoT-Based Monitoring and Control of Smoke Concentration in Fish Smoking Warehouses Using Fuzzy Logic and ESP32

Journal of Communication Systems, Networks, and Security · Vol. 1 No. 1 (2026) · hlm. 7–12

DOI: 10.68129/jcsns.v1i1.51
ISSN: 3163-5539
Terbit: 2026-07-20
Penerbit: Politeknik Elektronika Negeri Surabaya
Bahasa: eng
Lisensi: creativecommons.org/licenses/by-sa/4.0

Abstrak

Fish smoking is a common practice for preserving and flavoring fish; unfortunately, traditional methods of smoking can produce dangerous air pollutants, including carbon monoxide (CO) and nitrogen oxides (NO₂), which have severe implications for workers' health and environmental performance. In this context, we propose an Internet of Things (IoT)- based intelligent system for real-time monitoring and control of smoke levels in fish smoking warehouses. The MICS-6814 gas sensor, combined with the ESP32 microcontroller, measures CO and NO₂ levels, while a fuzzy-logic algorithm classifies air quality using the CO₂-N₂ Air Pollution Standard Index (ISPU) from the reference. The proposed approach automatically controls ventilation via a fan actuator, which is triggered when pollutant levels exceed specific thresholds. The results of the experiment show that at a distance of 40 cm, as soon as it falls, this system is determined to be an unhealthy air condition if it starts automatic ventilation. Still, at a distance of 1 m, air quality remains moderate and therefore requires no action. The system enabled real-time monitoring, classification, and control, while data visualization was handled via a web-based interface and an LCD. Power, investigations repeatedly reported that indoor air quality management in fish smoking places demonstrated its practicality in reducing health risks from smoke exposure

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Politeknik Negeri Malang
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Rekan penulis	Organisasi	Artikel bersama
Afina Nabila Dirganingsih	Afiliasi tidak diketahui	3
Yoedy Moegiharto	Afiliasi tidak diketahui	3
Mohammad Ridwan	Afiliasi tidak diketahui	3
Renel Cikita Robbyn	Afiliasi tidak diketahui	1
Muchammad Yahya Ma’ruf	Afiliasi tidak diketahui	1
Paramitha Eka Wahyu Lestari	Afiliasi tidak diketahui	1
Nailul Muna	Politeknik Negeri Malang	1
Muhammad Edo Listiawan	Afiliasi tidak diketahui	1
Nihayatus Sa'adah	Afiliasi tidak diketahui	1
Karimatun Nisa'	Afiliasi tidak diketahui	1

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) https://journals.pens.ac.id/index.php/jcsns/oai, pertama di-harvest 6 Nov 2026, terakhir terlihat 8 Nov 2026.

Metadata asli (oai_dc)

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	<dc:title xml:lang="en">IoT-Based Monitoring and Control of Smoke Concentration in Fish Smoking Warehouses Using Fuzzy Logic and ESP32</dc:title>
	<dc:creator xml:lang="en">Urifah Nur Rohmah</dc:creator>
	<dc:creator xml:lang="en">Faridatun Nadziroh</dc:creator>
	<dc:creator xml:lang="en">Budi Aswoyo</dc:creator>
	<dc:creator xml:lang="en">Anang Budikarso</dc:creator>
	<dc:creator xml:lang="en">Ida Anisah</dc:creator>
	<dc:subject xml:lang="en">smoke</dc:subject>
	<dc:subject xml:lang="en">MICS-6814</dc:subject>
	<dc:subject xml:lang="en">NodeMCU ESP32</dc:subject>
	<dc:subject xml:lang="en">fuzzy logic</dc:subject>
	<dc:description xml:lang="en">Fish smoking is a common practice for preserving and flavoring fish; unfortunately, traditional methods of smoking can produce dangerous air pollutants, including carbon monoxide (CO) and nitrogen oxides (NO₂), which have severe implications for workers' health and environmental performance. In this context, we propose an Internet of Things (IoT)- based intelligent system for real-time monitoring and control of smoke levels in fish smoking warehouses. The MICS-6814 gas sensor, combined with the ESP32 microcontroller, measures CO and NO₂ levels, while a fuzzy-logic algorithm classifies air quality using the CO₂-N₂ Air Pollution Standard Index (ISPU) from the reference. The proposed approach automatically controls ventilation via a fan actuator, which is triggered when pollutant levels exceed specific thresholds. The results of the experiment show that at a distance of 40 cm, as soon as it falls, this system is determined to be an unhealthy air condition if it starts automatic ventilation. Still, at a distance of 1 m, air quality remains moderate and therefore requires no action. The system enabled real-time monitoring, classification, and control, while data visualization was handled via a web-based interface and an LCD. Power, investigations repeatedly reported that indoor air quality management in fish smoking places demonstrated its practicality in reducing health risks from smoke exposure</dc:description>
	<dc:publisher xml:lang="en">Politeknik Elektronika Negeri Surabaya</dc:publisher>
	<dc:date>2026-07-20</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journals.pens.ac.id/jcsns/article/view/51</dc:identifier>
	<dc:identifier>10.68129/jcsns.v1i1.51</dc:identifier>
	<dc:source xml:lang="en">Journal of Communication Systems, Networks, and Security; Vol. 1 No. 1 (2026): April; 7-12</dc:source>
	<dc:source>3163-5539</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journals.pens.ac.id/jcsns/article/view/51/47</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2026 Urifah Nur Rohmah, Faridatun Nadziroh, Budi Aswoyo, Anang Budikarso, Ida Anisah</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>