Fingerprinting New York City's Scaffolding Problem with Longitudinal
  Dashcam Data
Dorin Shapira Matt Franchi Wendy Ju
Scaffolds, also called sidewalk sheds, are intended to be temporary
structures to protect pedestrians from construction and repair hazards.
However, some sidewalk sheds are left up for years. Long-term scaffolding
becomes eyesores, creates accessibility issues on sidewalks, and gives cover to
illicit activity. Today, there are over 8,000 active permits for scaffolds in
NYC; the more problematic scaffolds are likely expired or unpermitted. This
research uses computer vision on street-level imagery to develop a longitudinal
map of scaffolding throughout the city. Using a dataset of 29,156,833 dashcam
images taken between August 2023 and January 2024, we develop an algorithm to
track the presence of scaffolding over time. We also design and implement
methods to match detected scaffolds to reported locations of active scaffolding
permits, enabling the identification of sidewalk sheds without corresponding
permits. We identify 850,766 images of scaffolding, tagging 5,156 active
sidewalk sheds and estimating 529 unpermitted sheds. We discuss the
implications of an in-the-wild scaffolding classifier for urban tech,
innovations to governmental inspection processes, and out-of-distribution
evaluations outside of New York City.