Microcontroller Based Sensor-Array Data Acquisition System for Electronic Nose

Debabhuti, Nilava; Sen, Rishav; Sengupta, Anik; Sengupta, Sahil; Sharma, Prolay; Tudu, Bipan; Bandyopadhyay, Rajib; Bhattacharyya, Nabarun

doi:10.1109/icce50343.2020.9290704

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2022

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“…40,41,48,118,121 In many real-time applications, E-noses are used with proper visualization tools. [153][154][155] Debabhuti et al 156 developed a graphical user interface (GUI) for Quartz crystal Microbalance sensors and implemented in a Raspberry Pi module. A GUI with interactive control and visualization system was developed by Djelouat et al 30 which can also analyze the responses and display the extracted features of the gas sensor system real time.…”

Section: Evolution Of Managerial Toolsmentioning

confidence: 99%

Review–Modern Data Analysis in Gas Sensors

Sagar

Allison

Jalajamony

et al. 2022

J. Electrochem. Soc.

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Development in the field of gas sensors has witnessed exponential growth with a multitude of applications. The diversity of the applications has led to unexpected challenges. Recent advances in data science have addressed the challenges such as selectivity, drift, aging, limit of detection, and response time. The incorporation of modern data analysis including machine learning techniques have enabled a self-sustaining gas-sensing infrastructure without human intervention. This article provides a birds-eye view on data enabled technologies in the realm of gas sensors. While elaborating the prior developments in gas-sensing related data analysis, this article is intended as an entrant for enthusiasts in the domain of data science and gas sensors.

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