Integrating AI with optical fiber sensors allows a hybrid system that enhances strength for detecting various physical parameters such as intensity, data transmission, wavelength, and phase. These hybrid systems have been widely used in environmental sensing, telecommunication, and health monitoring. By analyzing the previous and current data trends, AI models enable predictive future maintenance, which reduces interruption and maintenance costs. These systems are better known for their high sensitivity, improved work efficiency in harsh environments, wide dynamic range, and are immune to electromagnetic (EM) interference and electrical noise. This integration minimizes environmental impact, reduces downtime, increases lifetime benefits, improves resource management, and optimizes production. This chapter elucidates the hybrid optical fiber sensors, hybrid system strengths, limitations, applications, and future trends.

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Hybrid Systems Combining Traditional and AI-Enhanced Optical Fiber Sensors

  • Arvind Sharma,
  • Sugandha Gupta,
  • Kavita Rani Segwal

摘要

Integrating AI with optical fiber sensors allows a hybrid system that enhances strength for detecting various physical parameters such as intensity, data transmission, wavelength, and phase. These hybrid systems have been widely used in environmental sensing, telecommunication, and health monitoring. By analyzing the previous and current data trends, AI models enable predictive future maintenance, which reduces interruption and maintenance costs. These systems are better known for their high sensitivity, improved work efficiency in harsh environments, wide dynamic range, and are immune to electromagnetic (EM) interference and electrical noise. This integration minimizes environmental impact, reduces downtime, increases lifetime benefits, improves resource management, and optimizes production. This chapter elucidates the hybrid optical fiber sensors, hybrid system strengths, limitations, applications, and future trends.