In a field trial, existing cables acted as ‘smart city’ sensors, collecting info about traffic patterns, road conditions and capacity, and vehicle classification.
This is potentially of huge interest to European operators at a time when they are looking to extend their services beyond connectivity and see smart cities as a very attractive market, and many are racing to build out fibre infrastructure.
The proof-of-concept project relied on new optical sensor technology developed from NEC with software underpinned by artificial intelligence (AI) for intelligent traffic monitoring – to measure vehicle density, direction, speed, acceleration, deceleration and more.
Previously, companies had to lay purpose-built fibre very shallow in the ground with fibre grating at intervals to gather and synthesise such information.
Public functions and services
The hope is the new tech could lead to or improve other solutions to support public services, such as helping first responders detect and respond to gun shots.
Other potential uses could be helping municipal authorities identify the deterioration of bridges, tunnels and other critical infrastructure more quickly and easily. “This test marks an important milestone for technology that could provide a huge leap forward for those building smart cities and those tasked to manage them,” said Adam Koeppe, SVP of Technology Planning and Development with Verizon.
He added, “Instead of ripping up tarmac to place road and traffic-sensing technology, cities will be able to simply piggyback Verizon’s existing fibre optic network.”
Technical details about the trial
The Verizon trial used a fibre sensing system alongside existing Wavelength Division Multiplexing (WDM) communication channels on the same fibre with minimal impact on the fibre’s data transmission capacity.
NEC said in a statement that this makes it suitable even on congested networks, and marks the first time that a 36.8Tbps data transmission system and distributed optical fibre sensing have been successfully demonstrated together through an operational telecom network.
Results from this trial can be found here.
The trial used AI tools such as convolutional neural networks and software vector machines to leverage distributed intelligent traffic informatics, through a single, integrated interrogator.
The distributed, multi-parameter sensor system evaluated various properties of back-scattering light, to derive data about the static strain, dynamic strain, acoustics, vibrations and temperatures for each fibre segment.
From them, users could identify detected signatures and translate the back-scattering signals into actionable information over a wide area, which was not possible using conventional sensors.