Abstract. We present a real-time, fully automatic vehicle traffic mon- itoring system based on phase-sensitive Optical Time Domain Reflec- tometry (Φ-OTDR) using distributed fiber optic sensors. The solution is designed for embedded on-the-edge deployment, leveraging a com- pact system composed of an FPGA with an integrated processor. It enables direct, in-stream processing of Φ-OTDR signals without requir- ing data storage or offline analysis. The system emulates, among oth- ers facilities, the functionality of a simplified Hough Transform (HT) through a lightweight hardware architecture based on an array of binary shift registers, optimized for detecting near-vertical line segments that correspond to the signature of moving vehicles. The proposed solution demonstrates that existing optical fiber networks can be effectively repur- posed for low-power, real-time traffic monitoring using dedicated embed- ded hardware.

Real-Time Vehicle Traffic Detection Using Distributed Fiber Optic Sensors

Marsi, Stefano
;
Carini, Alberto;Buttazzoni, Giulia;Comisso, Massimiliano;
2026-01-01

Abstract

Abstract. We present a real-time, fully automatic vehicle traffic mon- itoring system based on phase-sensitive Optical Time Domain Reflec- tometry (Φ-OTDR) using distributed fiber optic sensors. The solution is designed for embedded on-the-edge deployment, leveraging a com- pact system composed of an FPGA with an integrated processor. It enables direct, in-stream processing of Φ-OTDR signals without requir- ing data storage or offline analysis. The system emulates, among oth- ers facilities, the functionality of a simplified Hough Transform (HT) through a lightweight hardware architecture based on an array of binary shift registers, optimized for detecting near-vertical line segments that correspond to the signature of moving vehicles. The proposed solution demonstrates that existing optical fiber networks can be effectively repur- posed for low-power, real-time traffic monitoring using dedicated embed- ded hardware.
2026
9783032171733
9783032171740
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/3126819
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