About this Computer Science article
Smart and Selective Gas Sensor System Empowered With Machine Learning Over IoT Platform by Snehanjan Acharyya; Abhishek Ghosh; Sudip Nag; Subhasish Basu Majumder; Prasanta Kumar Guha is a Computer Science article available to read on EtoBox.
Simple, accurate, portable, and selective gas sensors with autonomous, remote, and real-time access have become a requisite in various fields of applications. In this paper, we report the development of a stand-alone and selective gas sensor system incorporating a single resistive sensor with wireless monitoring and internet connectivity. The sensor is fabricated in-house with platinum decorated tin-oxide hollow-spheres as the sensing material, which exhibits a prominent response towards the tested volatile organic compounds (VOCs) at different concentrations. The intelligence in terms of accurate identification of VOCs and their concentration is attained by employing a machine learning tool based on deep neural network. The applied model displays an average accuracy of 96.43% with a fast prediction speed of 310μs, allowing a real-time recognition capability. The wireless connectivity is established utilizing a low-power microcontroller board and a Bluetooth module. The real-time data is made available for the users over an Android-based mobile application and a webpage while utilizing cloud services through the internet. The implemented system is successfully experimented with and
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- Author
- Snehanjan Acharyya; Abhishek Ghosh; Sudip Nag; Subhasish Basu Majumder; Prasanta Kumar Guha
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Published
- 2024
- Language
- EN
- Field
- Computer Science (Physical Sciences)