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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) · pp. 7–12

DOI
10.68129/jcsns.v1i1.51
ISSN
3163-5539
Published
2026-07-20
Publisher
Politeknik Elektronika Negeri Surabaya
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

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

Keywords

Collaboration network of the authors

20 authors · 56 co-authorship links

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Muhammadiyah Semarang
  • Politeknik Negeri Malang
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
mohammad ridwanUniversitas Muhammadiyah Semarang3
Afina Nabila DirganingsihAffiliation unknown3
Yoedy MoegihartoAffiliation unknown3
Nihayatus Sa'adahAffiliation unknown2
Renel Cikita RobbynAffiliation unknown1
Muchammad Yahya Ma’rufAffiliation unknown1
Paramitha Eka Wahyu LestariAffiliation unknown1
Nailul MunaPoliteknik Negeri Malang1
Muhammad Edo ListiawanAffiliation unknown1
Karimatun Nisa'Affiliation unknown1
Rahardhita Widyatra SudibyoAffiliation unknown1
Haniah MahmudahAffiliation unknown1
Fitri FitriahAffiliation unknown1
Hari Wahjuningrat SuparnoAffiliation unknown1
Muhammad Hendra SyahputraAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journals.pens.ac.id/index.php/jcsns/oai, first harvested 6 Nov 2026, last seen 8 Nov 2026.
Original metadata (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>