Artificial Intelligence in Gas Sensing: A Review
Rensselaer Polytechnic Institute
Indexed incrossrefpubmed
Abstract
The role of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in enhancing and automating gas sensing methods and the implications of these technologies for emergent gas sensor systems is reviewed. Applications of AI-based intelligent gas sensors include environmental monitoring, industrial safety, remote sensing, and medical diagnostics. AI, ML, and DL methods can process and interpret complex sensor data, allowing for improved accuracy, sensitivity, and selectivity, enabling rapid gas detection and quantitative concentration measurements based on sophisticated multiband, multispecies sensor systems. These methods can discern subtle patterns in sensor signals, allowing sensors to…
Citation impact
80
total citations
- FWCI
- 41.84
- Percentile
- 100%
- References
- 203
Citations per year
Authors
2Topics & keywords
Topics
Keywords
- Environmental science
- Computer science
- Biochemical engineering
- Nanotechnology
- Data science
- Materials science
- Engineering
No related works found for this paper.