Distributed Fiber Optic Sensor Technology for the Real-Time Monitoring and Preservation of Ancient Sites and Artifacts
محورهای موضوعی : Archaeometry
Mahyar Radak
1
,
Anita Akhgar
2
1 - Department of Atomic and Molecular Physics, Mazandaran University, Babolsar, Iran
2 - Department of Archaeology, Mazandaran University, Babolsar, Iran
کلید واژه: Fiber Optic Sensors, Cultural Heritage Preservation, Distributed Acoustic Sensing, Michelson Interferometer, Mach-Zehnder Interferometer, Archaeological Site Security,
چکیده مقاله :
The preservation of invaluable cultural heritage assets, including ancient artifacts and historical sites, remains a critical global concern. Existing perimeter protection methods, such as CCTV systems, infrared sensors, and conventional surveillance technologies, often exhibit significant limitations in terms of spatial coverage, sensitivity to subtle intrusions, and adaptability to varying environmental conditions. This paper presents an innovative and highly effective solution utilizing fiber optic sensor (FOS) technology, which offers numerous advantages, including lightweight construction, immunity to electromagnetic interference, ease of installation, high sensitivity, and reliable performance across a broad range of applications. Specifically, the study introduces novel designs for distributed acoustic FOS systems based on Michelson, Mach-Zehnder, and Sagnac interferometric configurations. Through comprehensive theoretical analysis, simulation modeling, and experimental validation, the research explores their practical utility in protecting cultural heritage. Two detailed case studies—focused on the Louvre Museum in France and the ancient archaeological site of Persepolis in Iran—demonstrate the implementation, functionality, and real-world efficacy of the proposed systems. The findings highlight how these FOS networks, particularly when combined with advanced artificial intelligence and machine learning algorithms, can effectively detect, classify, and localize human-induced acoustic disturbances such as walking or digging, while minimizing false alarms caused by environmental noise. This enhanced discrimination capability not only improves overall security but also significantly reduces the need for extensive human surveillance. Moreover, these systems enable precise, continuous, and real-time 24-hour monitoring over vast indoor and outdoor areas. In conclusion, the integration of FOS technology offers a scalable, intelligent, and transformative approach to addressing the complex and evolving challenges associated with the long-term preservation and protection of cultural heritage sites around the world.
The preservation of invaluable cultural heritage assets, including ancient artifacts and historical sites, remains a critical global concern. Existing perimeter protection methods, such as CCTV systems, infrared sensors, and conventional surveillance technologies, often exhibit significant limitations in terms of spatial coverage, sensitivity to subtle intrusions, and adaptability to varying environmental conditions. This paper presents an innovative and highly effective solution utilizing fiber optic sensor (FOS) technology, which offers numerous advantages, including lightweight construction, immunity to electromagnetic interference, ease of installation, high sensitivity, and reliable performance across a broad range of applications. Specifically, the study introduces novel designs for distributed acoustic FOS systems based on Michelson, Mach-Zehnder, and Sagnac interferometric configurations. Through comprehensive theoretical analysis, simulation modeling, and experimental validation, the research explores their practical utility in protecting cultural heritage. Two detailed case studies—focused on the Louvre Museum in France and the ancient archaeological site of Persepolis in Iran—demonstrate the implementation, functionality, and real-world efficacy of the proposed systems. The findings highlight how these FOS networks, particularly when combined with advanced artificial intelligence and machine learning algorithms, can effectively detect, classify, and localize human-induced acoustic disturbances such as walking or digging, while minimizing false alarms caused by environmental noise. This enhanced discrimination capability not only improves overall security but also significantly reduces the need for extensive human surveillance. Moreover, these systems enable precise, continuous, and real-time 24-hour monitoring over vast indoor and outdoor areas. In conclusion, the integration of FOS technology offers a scalable, intelligent, and transformative approach to addressing the complex and evolving challenges associated with the long-term preservation and protection of cultural heritage sites around the world.
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