Identification of Toxic Gases using Electronic Nose

Ravindra, VelankarAshwini; Rajbhoj, S. M.

doi:10.1109/iccubea.2017.8463908

Cited by 7 publications

(3 citation statements)

References 3 publications

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“…In the study [11], the outdoor air quality performance of three Electronic Nose systems utilizing only semiconducting gas sensors, only amperometric gas sensors, or both types of sensors are examined. Three semiconducting gas sensors and three amperometric gas sensors were ultimately employed to detect nitrogen dioxide, Sulphur dioxide, Ozone, and carbon monoxide.…”

Section: Related Workmentioning

confidence: 99%

A Smart-home Electronic-Nose for Detecting Hazardous Gases

Moustafa

Metawie

Hany

et al. 2023

Journal of Computing and Communication

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The idea of networking household appliances and technologies has been promoted for over a decade using smart home technology. The Smart Homes Association defines "the combination of technology and services" for a higher living level as "smart home technology" through home networking. Computer tools come in a variety. Systems can also be included in smart home systems. In this essay, we present. Systems for Smart Homes that can use or include several technologies. Automatic detection of dangerous substances, early fires, smoke, and gas leaks is provided by this ground-breaking device. E-nose can recognize seven different odors with the help of various gas sensors and several machine learning techniques. Finally, if a hazardous gas spread occurs, the system sends out an alarm message that is particular to the gas or occurrence. Support Vector Machine (SVM), Logistic Regression, and Decision Tree all received an F1score of 98% from us. Random Forest and K-Nearest Neighbors both received perfect scores.

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Section: Related Workmentioning

confidence: 99%

A Smart-home Electronic-Nose for Detecting Hazardous Gases

Moustafa

Metawie

Hany

et al. 2023

Journal of Computing and Communication

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“…Sensor dengan seri MQ ini digunakan karena sensor jenis ini hemat biaya dan mudah tersedia di pasaran. Sensor MQ-135 membutuhkan waktu pemanasan lebih sedikit, memberikan respon cepat dan sensitivitasnya baik [7].Prinsip kerja dari sensor ini adalah ketika timah dioksida (partikel semikonduktor) dipanaskan di udara pada suhu tinggi, oksigen diserap di permukaan. Di udara bersih, elektron donor dalam timah dioksida tertarik ke arah oksigen yang diserap pada permukaan bahan sensor.…”

Section: Sensor Gas Mq-135unclassified

Sistem Pemantauan Kadar Gas pada Tambang Batubara Berbasis IoT Menggunakan Teknologi Komunikasi LoRa

Ikhsan¹,

Rivai²

2020

JTITS

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Sistem pemantauan kadar gas pada tambang batu bara berbasis IoT menggunakan teknologi komunikasi LoRa adalah sebuah sistem portabel yang berfungsi untuk memantau kadar gas yang berbahaya di tambang menggunakan dua sensor dan modul GPS untuk mengetahui posisi dari alat ini, serta menggunakan LoRa sebagai modul komunikasi. Pembuatan alat ini didasarkan oleh adanya gas yang berbahaya untuk manusia di daerah pertambangan, dari segi kecelakaan kerja seperti kebakaran atau ledakan yang dikarenakan gas CH4 dan juga sistem pernapasan yang akan terganggu jika terlalu banyak terpapar gas CO2. Sistem ini dapat memantau perubahan konsentrasi gas. Sensor yang digunakan adalah sensor gas jenis MQ-02 dan MQ-135. Dalam penelitian ini mengimplementasikan sistem IoT untuk pemantauan kadar gas di tambang batu bara. Alat ini nantinya dapat dibawa oleh pengguna asalkan masih dalam jarak yang stabil untuk komunikasi antar LoRa. Ketika LoRa di transmitter mengirimkan data, maka LoRa di receiver akan menerima data tersebut dan mengolahnya. Data kemudian dikirim melalui komunikasi serial ke NodeMCU, dan diteruskan ke aplikasi yang ada di smart phone. Pengujian sensor gas dilakukan dengan beberapa bahan seperti asap dari kertas dan asap rokok. Hasil yang didapatkan di pengujian tersebut berbeda. Jarak komunikasi maksimal yang bisa dilakukan di daerah perkotaan kurang lebih 600 meter. Konsentrasi gas yang terukur saat pengujian relatif naik turun dikarenakan faktor alam seperti adanya angin.

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“…ANN, BP, PCA, SVM, LDA, and other sorts of algorithms can be utilised for classification. [6] Using Visual Basic 6.0, the backpropagation algorithm is produced. The outcomes are presented as percentages.…”

mentioning

confidence: 99%

Toxic Gases Detection and Tolerance Level Classification Using Machine Learning Algorithms

Deepan,

Saravanan

2023

International Journal of Electronics and Telecommunications

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with rapid population increases, people are facing the challenge to maintain healthy conditions. One of the challenges is air pollution. Due to industrial development and vehicle usage air pollution is becoming a high threat to human life. This air pollution forms through various toxic contaminants. This toxic contamination levels increase and cause severe damage to the living things in the environment. To identify the toxic level present in the polluted air various methods were proposed by the authors, But failed to detect the tolerance level of toxic gases. This article discusses the methods to detect toxic gasses and classify the tolerance level of gasses present in polluted air. Various sensors and different algorithms are used for classifying the tolerance level. For this purpose "Artificial Sensing Methodology" (ASM), commonly known as e-nose, is a technique for detecting harmful gases. SO2-D4, NO2-D4, MQ-135, MQ136, MQ-7, and other sensors are used in artificial sensing methods (e-nose). "Carbon monoxide, Sulfur dioxide, nitrogen dioxide, and carbon dioxide" are all detected by these sensors. The data collected by sensors is sent to the data register from there it is sent to the Machine learning Training module (ML) and the comparison is done with real-time data and trained data. If the values increase beyond the tolerance level the system will give the alarm and release the oxygen.

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Identification of Toxic Gases using Electronic Nose

Cited by 7 publications

References 3 publications

A Smart-home Electronic-Nose for Detecting Hazardous Gases

A Smart-home Electronic-Nose for Detecting Hazardous Gases

Sistem Pemantauan Kadar Gas pada Tambang Batubara Berbasis IoT Menggunakan Teknologi Komunikasi LoRa

Toxic Gases Detection and Tolerance Level Classification Using Machine Learning Algorithms

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