Review on Discrimination of Hazardous Gases by Smart Sensing Technology

Authors

  • Gangadhar Bandewad Deen Dayal Upadhyay KAUSHAL Kendra, Dr. Babasaheb Ambedkar Marathwada University, India https://orcid.org/0000-0003-2832-3955
  • Kunal P. Datta Deen Dayal Upadhyay KAUSHAL Kendra, Dr. Babasaheb Ambedkar Marathwada University, India
  • Bharti W. Gawali Department of Computer Science and IT, Dr. Babasaheb Ambedkar Marathwada University Aurangabad, India
  • Sunil N. Pawar Department of Electronics and Communication Engineering, Jawaharlal Nehru Engineering College MGM University, India

DOI:

https://doi.org/10.47852/bonviewAIA3202434

Keywords:

smart gas sensor, algorithm, hazardous gases

Abstract

Real-time detection of hazardous gases in the ambient and indoors has become the prime motive for curbing the problem of air pollution. Keeping the concentration of hazardous gases in control is the main task before human society so as to keep environmental balance. Researchers are concentrating on smart sensors because they can detect and forecast the presence of gas in real-time, provide correct information about gas concentration, and detect a target gas from a mixture of gases. This smart gas sensor system can have applications in the field of military, space, underwater, indoor, outdoors, factories, vehicles, and wearable smart devices. This study reviews recent advances in smart sensor technology with respect to the material structure, sensing technique, and discrimination algorithm. Focus is given on reducing the power consumption and area of a sensor circuitry with the help of different techniques.

 

Received: 29 September 2022 | Revised: 10 February 2023 | Accepted: 27 February 2023

 

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

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Published

2023-02-27

How to Cite

Bandewad, G., Datta, K. P. ., Gawali, B. W. ., & Pawar, S. N. . (2023). Review on Discrimination of Hazardous Gases by Smart Sensing Technology. Artificial Intelligence and Applications, 1(2), 86–97. https://doi.org/10.47852/bonviewAIA3202434

Issue

Section

Review