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International Journal of Research and Innovation in Applied Science (IJRIAS)

Sensor Fingerprinting–Based Gas Identification Using Artificial Intelligence

byMrs. K. Jayanthi; Naren Ariya S.; Devasridharan K.M.; Deva Suriya S.; Hari S.

Published May 9, 2026  •  Vol. 11, Issue 4, pp. 1306–1309Open Access
DOI: 10.51584/IJRIAS.2026.110400093

Abstract

Accurate identification of hazardous gases remains a critical challenge in environmental monitoring due to the limitations of single-sensor and threshold-based systems. This work presents an intelligent gas identification approach based on sensor fingerprinting and embedded artificial intelligence. A multi-sensor array comprising MQ-series sensors is used to capture distinct response patterns generated by different gases. These patterns are preprocessed and analyzed using a lightweight TinyML model deployed on an ESP32 microcontroller for on-device classification. The system enables real-time detection, local visualization, and wireless transmission of gas data for remote monitoring. An integrated alert mechanism enhances safety by providing immediate warnings when abnormal conditions are detected. The proposed solution offers a compact, low-cost, and scalable framework suitable for smart environments, industrial safety, and IoT-based monitoring applications.

Keywords: Gas Identification, Sensor Fingerprinting

JournalInternational Journal of Research and Innovation in Applied Science (IJRIAS)
ISSN2454-6194
Volume / IssueVolume 11, Issue 4
Pages1306–1309
Publication dateMay 9, 2026
DOI10.51584/IJRIAS.2026.110400093
PublisherRSIS International
LicenseOpen Access

How to cite this article

Mrs. K. Jayanthi, Naren Ariya S., Devasridharan K.M., Deva Suriya S., & Hari S. (2026). Sensor Fingerprinting–Based Gas Identification Using Artificial Intelligence. International Journal of Research and Innovation in Applied Science (IJRIAS), 11(4), 1306-1309. https://doi.org/10.51584/IJRIAS.2026.110400093

BibTeX

@article{Mrs2026,
  title   = {Sensor Fingerprinting–Based Gas Identification Using Artificial Intelligence},
  author  = {Mrs. K. Jayanthi and Naren Ariya S. and Devasridharan K.M. and Deva Suriya S. and Hari S.},
  journal = {International Journal of Research and Innovation in Applied Science (IJRIAS)},
  volume  = {11},
  number  = {4},
  pages   = {1306--1309},
  year    = {2026},
  doi     = {10.51584/IJRIAS.2026.110400093},
  publisher = {RSIS International}
}