FIBRATRAFIC

Artículos científicos

• Corera, I.; Piñeiro, E.; Navallas, J.; Sagues, M.; Loayssa, A. Long-Range Traffic Monitoring Based on Pulse-Compression Distributed Acoustic Sensing and Advanced Vehicle Tracking and Classification Algorithm. Sensors 2023, 23, 3127. (https://doi.org/10.3390/s23063127)
• Enrique Piñeiro, Mikel Sagues, Alayn Loayssa (2023): “Compensation of Phase Noise Impairments in Distributed Acoustic Sensors Based on Optical Pulse Compression Time-Domain Reflectometry”, JOURNAL OF LIGHTWAVE TECHNOLOGY, VOL. 41, NO. 10, MAY 15, 2023

Conferencias

• Optical Fiber Sensors 2022 (29 August–2 September 2022) – Alexandria, Virginia United States
• Iñigo Corera, Enrique Piñeiro, Javier Navallas, Mikel Sagues, and Alayn Loayssa: “Long-range and high-resolution traffic monitoring based on pulse-compression DAS and advanced vehicle tracking algorithm” (ISBN: 978-1-957171-14-2)

The FIBRATRAFIC project made it possible to develop a traffic monitoring system based on using the fibre optic networks that have already been installed on the roadways using a novel sensor technology called DAS, Distributed Acoustic Sensing.

In contrast to conventional traffic monitoring solutions that are limited to providing information at a specific point on a road, the technology developed in this project makes it possible to obtain a distributed measurement where every point on a road along tens of kilometres can be monitored simultaneously without having to make any modifications to the fibre telecommunications network used. Additionally, using signal processing techniques and machine learning on the signals gathered by the DAS sensors, it was possible to detect the position of vehicles along the road, determine their speed, the distance between vehicles and even classify the vehicles by characteristics (heavy vehicles, touring cars).

In short, at a technological level, the project was fuelled by three different technologies (photonic sensing, signal processing and machine learning), which are linked to the fields of specialisation of the three research groups involved in the project, being made public.
The goals were easily met by the project, and all the specific goals specified as challenged at the beginning were achieved.

• A photonic sensing scheme was developed using DAS technology, which improves the performance of previously existing systems and makes it possible to use them for advanced traffic monitoring in a distributed way over tens of kilometres. Specifically, for the first time in the field of traffic monitoring, the sensor developed uses a photonic sensing scheme based on detecting the optical phase, and also uses optical pulse compression techniques, which makes it possible to increase the sensitivity, resolution and measurement range. It was thus possible to detect a richer signal (with more information), which made it possible to use new signal processing and machine learning techniques that had not been explored previously in this field.
• Processing and machine learning techniques were developed that were applied to DAS signals for detecting, tracking and classifying vehicles. The development of a processing scheme, based on a novel transformed domain that makes it possible to optimise vehicle detection that, in turn, simplifies the vehicle tracking process, should be highlighted. Furthermore, machine learning techniques were used for classifying vehicles using DAS signals, which made it possible to distinguish between light and heavy vehicles automatically and with great precision. In order to prepare the information needed to train the machine learning algorithms, an automatic labelling system was developed based on neural networks using optical cameras. in addition, a detected vehicle tracking algorithm was used to be able to track the paths of vehicles on the video and thus do a precise vehicle count.
• A pre-commercial field prototype of a high-performance DAS interrogator device was built.
• Lastly, the operation of the technology developed on a road network using fibre optic links owned by public institutions of the Chartered Community of Navarre was shown, and excellent results were obtained in field measurements done in a long range (35 km) real open traffic environment. Thanks is given to the collaboration of the government of Navarre and the city of Pamplona through the NASERTIC and ANIMSA public companies.
  The technology developed in the project made it possible to publish an article in a scientific journal, so the novelty of the system developed could be quantified.

Corera, I.; Piñeiro, E.; Navallas, J.; Sagues, M.; Loayssa, A. Long-Range Traffic Monitoring Based on Pulse-Compression Distributed Acoustic Sensing and Advanced Vehicle Tracking and Classification Algorithm. Sensors 2023, 23, 3127. https://doi.org/10.3390/s23063127

On the other hand, it is important to underline that the experience created from this project, with the joint work of three research groups and the use of three different but complementary technologies, will simplify the application of similar developments in other fields aside from traffic management. In that way, and even though it is outside the scope of the project, the technology developed in the project could be applicable in other fields, which could include intrusion detection, which will make it possible to protect fibre optics that belong to (public or private) telecommunications operators from external threats, monitoring the integrity of road infrastructures, distributed sensing of structure in different industrial areas, or monitoring seismic phenomena.

As a final assessment of the project, the benefits of being able to work with different SINAI agents, which made it possible to find synergies that would not have been created otherwise, should be highlighted. In particular, in this project the relationship was fluid and constructive and was valued very highly by both parties, UPNA-NAITEC.