Singh, Shailendra Kr and Paul, Mukul Chandra and Kumar, Pratik (2026) Emerging Trends in the Integration of AI Technology with FBG and SPR Sensors for Environmental Health Monitoring. Materials Science in Semiconductor Processing, 202 (110127). ISSN 13698001
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In the modern age, optical fiber sensors have emerged as vital tools across various scientific and industrial domains due to their high demand in automation, gas sensing, chemical sensing, drug monitoring, heavy metal detection, safety, and other applications. Consequently, researchers have focused on the development of various types of optical sensors, including grating based sensors, plasmonic sensors, distributed fiber optic sensors, and absorption spectroscopy-based sensors. Fiber optic sensors are increasingly preferred over electronic sensors because of their real time monitoring capabilities, multiplexing, and suitability in hazardous environments. This research article presents a comprehensive review of two types of fiber optic sensors, detailing their applications, advantages, disadvantages, limitations, and future prospects. Our literature survey indicates that grating, absorption spectroscopy, distributed, and plasmonic based sensors have been prioritized owing to their wide demand in sensing applications. Importantly, several research groups have explored the role of plasmonic effects on grating based sensors, reporting significant improvements in performance, including higher sensitivity, better selectivity, reduced hysteresis error, and faster response times. We further critically examine the integration of Surface Plasmon Resonance (SPR) with grating based sensors, which is essential for advancing next generation sensor technologies. This approach provides deeper scientific insights into current trends and future directions in the evolving field. Additionally, incorporating Artificial Intelligence (AI) with FBG and SPR enhances sensor performance in terms of accuracy, adaptability under different conditions, and improved analysis of signal interference. Finally, this review aims to serve as a valuable resource for young researchers, academicians, and industrialists interested in photonic sensor development.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | FBG sensor,SPR sensor, Machine learning, Smart sensing technology, Environmental monitoring |
| Subjects: | Environment and Pollution |
| Divisions: | Fiber Optics and Photonics |
| Depositing User: | Ms Upasana Sahu |
| Date Deposited: | 12 May 2026 17:01 |
| Last Modified: | 12 May 2026 17:01 |
| URI: | https://cgcri.csircentral.net/id/eprint/5802 |
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