Rancang bangun sistem kontrol konsentrasi karbondioksida dan monitoring laju pernapasan dalam smart mask berbasis internet of things

Cahyani, Yeni Dwi (2022) Rancang bangun sistem kontrol konsentrasi karbondioksida dan monitoring laju pernapasan dalam smart mask berbasis internet of things. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Masker merupakan kebutuhan masyarakat saat ini. Semenjak pandemi, masker diwajibkan oleh semua pihak. Namun, penggunaan masker memiliki dampak negatif seperti sesak napas (dyspnea), pusing, dan mual. Oleh karena itu, dirancanglah smart mask yang dapat melakukan sistem kontrol konsentrasi karbon dioksida dan monitoring laju pernapasan berbasis Internet of Things. Smart mask dirancang menggunakan sensor MQ-135 untuk mendeteksi konsentrasi karbon dioksida dalam masker, sensor LM35 untuk mendeteksi laju pernapasan dan kondisi pernapasan manusia, fan sebagai kontrol saat konsentrasi karbon dioksida lebih dari set point, dan aplikasi Blynk sebagai monitor serta alarm atau notifikasi konsentrasi karbon dioksida, laju dan kondisi pernapasan, serta suhu pernapasan secara real-time. Dalam membangun smart mask, sensor MQ-135 memiliki akurasi pembacaan dalam mendeteksi konsentrasi karbon dioksida sebesar 99,22% dengan error sebesar 0,78%, sedangkan sensor LM35 memiliki akurasi pembacaan dalam mendeteksi laju pernapasan sebesar 98,22% dengan error sebesar 1,78%, sehingga kedua sensor layak digunakan dalam smart mask. Dengan menggunakan sistem kontrol on-off, smart mask memiliki performansi maksimum persentase overshoot (MP) sebesar 5,78% dan error steady-state sebesar 5%. Error steady-state masih dalam batas allowable tolerance, walaupun untuk mencapai keadaan steady membutuhkan waktu yang lama dan menghasilkan osilasi yang tinggi. Kondisi konsentrasi karbon dioksida dalam smart mask terakumulasi dari awal hingga akhir pemakaian, sehingga terjadi osilasi naik turun yang tinggi pada grafik. Sistem monitoring pada smart mask sudah berjalan dengan baik, yaitu dapat melakukan pengiriman data konsentrasi karbon dioksida, laju pernapasan, kondisi pernapasan, dan suhu pernapasan secara real-time, serta notifikasi dapat muncul pada ponsel dengan selang waktu setiap 2 detik.
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Masks are a necessity in today's society. Since the pandemic, masks have been mandatory for everyone. However, wearing masks can have negative effects such as shortness of breath (dyspnea), dizziness, and nausea. Therefore, a smart mask was designed to control carbon dioxide concentration and monitor respiratory rate based on the Internet of Things. The smart mask is designed using an MQ-135 sensor to detect the concentration of carbon dioxide inside the mask, an LM35 sensor to detect respiratory rate and human respiratory conditions, a fan to control the carbon dioxide concentration when it exceeds the set point, and the Blynk application as a monitor and alarm or notification system for carbon dioxide concentration, respiratory rate and conditions, as well as respiratory temperature in real time. In developing the smart mask, the MQ-135 sensor achieved a reading accuracy of 99.22% in detecting carbon dioxide concentration, with an error of 0.78%, while the LM35 sensor achieved a reading accuracy of 98.22% in detecting respiratory rate, with an error of 1.78%. Therefore, both sensors are suitable for use in the smart mask. By using an on-off control system, the smart mask achieved a maximum percent overshoot (MP) of 5.78% and a steady-state error of 5%. The steady-state error is still within the allowable tolerance limit, although it takes a long time to reach steady-state conditions and produces high oscillations. The carbon dioxide concentration inside the smart mask accumulates from the beginning to the end of use, resulting in high fluctuations in the graph. The monitoring system of the smart mask has functioned well, as it can transmit data on carbon dioxide concentration, respiratory rate, respiratory conditions, and respiratory temperature in real time, while notifications can be displayed on a mobile phone at intervals of every 2 seconds.

Item Type:	Thesis (Other)
Additional Information:	621.391 6 Cah r-1
Uncontrolled Keywords:	Dyspnea, Smart mask, Internet of Things (IoT), Dyspnea, Smart mask, Internet of Things (IoT)
Subjects:	T Technology > TJ Mechanical engineering and machinery > TJ213 Automatic control.
Divisions:	Faculty of Vocational > Instrumentation Engineering
Depositing User:	magang .
Date Deposited:	05 Oct 2026 03:05
Last Modified:	05 Oct 2026 03:05
URI:	http://repository.its.ac.id/id/eprint/145236

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