Photonics Fiber-Sensing to Monitor Smart Cities

Written by Euclides Chuma

To facilitate the evolution of an ordinary city into a Smart City, sensors that monitor the greatest number of variables are needed in order to ensure that decision-making is performed in the best possible way and benefits the largest number of inhabitants. Monitoring a city requires thousands or even millions of sensors spreading over a Smart City. However, photonics technologies have recently emerged as a mean to enable the continuous monitoring of tens of kilometers of geographical coverage using a single device and a single optical fiber that has already been installed by telecommunications operators. This technology is known as Distributed Acoustic Sensing (DAS) [1][2] and promises to revolutionize many aspects of Smart Cities, including vehicle traffic monitoring [3][4], train monitoring [5], subways, and even electric grid monitoring [6]. DAS technology was initially used for seismic monitoring, until when some enterprises, such as Future Photonics [7], took the opportunity to unlock the full potential in DAS to monitor the integrity of oil and gas pipelines and also to monitor oil wells [8].

DAS systems utilize fiber optic cables to provide distributed strain sensing based on Rayleigh scattering. In DAS, a coherent laser pulse is sent along a fiber optic, and scattering within the fiber causes the fiber to act as a distributed interferometer. The intensity of the reflected light is measured as a function of time after the laser pulse is transmitted. When the pulse has had time to travel the full length of the fiber and back, the next laser pulse is then sent, and the process continues. The changes in the reflected intensity of the successive laser pulses from the same region of the fiber are driven by the changes in the fiber (e.g., strain and temperature). Figure 1 illustrates the DAS applied principle.



 Fig 1. The DAS applied principle


Currently, a DAS interrogator, can monitor continuous distances of 100 km with a single piece of equipment using optical fibers already installed for telecommunications. With all these advantages, DAS technology can be used in Smart Cities for traffic monitoring, railways, accidents, intrusions, etc. Figure 2 illustrates the DAS technology applied in monitoring events within the context of Smart Cities.



Fig 2. DAS applied in Smart Cities


The use of DAS with Artificial Intelligence, harnessing the fiber optic that is already installed along the road, enables the operation centers within a Smart City to access accurate and timely information on the current traffic situation. This information is critical to minimize traffic congestion and reduce travel times. Therefore, the DAS converts existing fiber-optic cables into an array of intelligent sensors, which deliver timely and accurate traffic monitoring and incident detection information across the entire monitored route.

DAS solutions have already been used to improve railway transportation monitoring and safety by facilitating faster and better processes for maintaining and protecting railway systems and trains. Modern infrastructures have been already equipped with these fiber-optic cables that can be further used to monitor and detect railway environments at remote locations, providing surveillance and real-time threat detection for up to 100 km with only one DAS.

Traditional DAS applications in pipeline monitoring can be an important part of Smart Cities monitoring systems since pipelines are susceptible to a wide range of external threats, which can potentially result in significant damage, or worse yet, a rupture. When a rupture occurs in a pipeline, its environmental damages and economic losses affect the entire society inside and outside Smart Cities. However, a majority of these incidents can be prevented using DAS.

Another photonics fiber-sensing solution is the Distributed Temperature Sensing (DTS) [9] that also uses fiber optic sensor cables and functions as linear temperature sensors. The result is a continuous temperature profile along the entire length of the sensor´s cable. Instead of DAS, which utilizes the Rayleigh effect, the DTS utilizes the Raman effect to continuously measure the temperature.

Finally, fiber photonic sensors are promising monitoring technologies that can be quickly adopted in Smart Cities as they use the fiber optic infrastructure already installed by the telecommunications industry. The big question is: when will we start using it for a smarter city of the future?



  1. A. H. Hartog, "An Introduction to Distributed Optical Fibre Sensors (Series in Fiber Optic Sensors)", CRC Press (Taylor and Francis), 2017, ed.1
  2. J. Ajo-Franklin, Y. Li, M. Karrenbach, "Distributed Acoustic Sensing in Geophysics: Methods and Applications", American Geophysical Union, 2021, ed.1
  3. H. Liu, et. al., "Vehicle Detection and Classification Using Distributed Fiber Optic Acoustic Sensing", IEEE Transactions on Vehicular Technology, 2020, v.69, i.2, pp.1363-1374
  4. H. Liu, et. al., "Traffic Flow Detection Using Distributed Fiber Optic Acoustic Sensing", IEEE Access, 2018, v.6, pp.68968-68980
  5. A. Papp, et. al., "A real-time algorithm for train position monitoring using optical time-domain reflectometry", IEEE International Conference on Intelligent Rail Transportation (ICIRT), 2016
  6. S. Cherukupalli, G. J. Anders, "Distributed Fiber Optic Sensing and Dynamic Rating of Power Cables", Wiley-IEEE Press, 2020
  7. Future Photonics, “DAS Technology Solutions”, 15 June 2021,
  8. K. Johannessen, B. Drakeley, M. Farhadiroushan, "Distributed Acoustic Sensing - A New Way of Listening to Your Well/Reservoir", SPE Intelligent Energy International, 2012
  9. A. Ukil, H. Braendle, P. Krippner, "Distributed Temperature Sensing: Review of Technology and Applications", IEEE Sensors Journal, 2012, v.12, i.5, pp.885-892




This article was edited by Payman Dehghanian

For a downloadable copy of the July 2021 eNewsletter which includes this article, please visit the IEEE Smart Cities Resource Center.

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Euclides Chuma earned a degree in mathematics (2003) from University of Campinas (UNICAMP), a graduate degree in network and telecommunications Systems (2015) at INATEL, and MSc in electrical engineering (2017) at UNICAMP, and PhD in electrical engineering (2019) at UNICAMP, SP-Brazil. His research interests are smart cities, artificial intelligence, internet of things, microwave, millimeter wave, photonics, bioengineering, sensors, wireless power transfer, and telecommunications.

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