  We introduce the TelecomTM system that uses pre-existing telecommunication
fiber-optic cables as virtual strain sensors to sense vehicle-induced ground
vibrations for fine-grained and ubiquitous traffic monitoring and
characterization. Here we call it a virtual sensor because it is a
software-based representation of a physical sensor. Due to the extensively
installed telecommunication fiber-optic cables at the roadside, our system
using redundant dark fibers enables to monitor traffic at low cost with low
maintenance. Many existing traffic monitoring approaches use cameras,
piezoelectric sensors, and smartphones, but they are limited due to privacy
concerns and/or deployment requirements. Previous studies attempted to use
telecommunication cables for traffic monitoring, but they were only exploratory
and limited to simple tasks at a coarse granularity, e.g., vehicle detection,
due to their hardware constraints and real-world challenges. In particular,
those challenges are 1) unknown and heterogeneous properties of virtual sensors
and 2) large and complex noise conditions. To this end, our TelecomTM system
first characterizes the geographic location and analyzes the signal pattern of
each virtual sensor through driving tests. We then develop a spatial-domain
Bayesian filtering and smoothing algorithm to detect, track, and characterize
each vehicle. Our approach uses the spatial dependency of multiple virtual
sensors and Newton's laws of motion to combine the distributed sensor data to
reduce uncertainties in vehicle detection and tracking. In our real-world
evaluation on a two-way traffic road with 1120 virtual sensors, TelecomTM
achieved 90.18% vehicle detection accuracy, 27$\times$ and 5$\times$ error
reduction for vehicle position and speed tracking compared to a baseline
method, and $\pm$3.92% and $\pm$11.98% percent error for vehicle wheelbase and
weight estimation, respectively.
