Software apps and online services
The maintenance of city streets is a most visible indicator of a city government's performance.
Every year, US cities spend $ Billions to maintain their local roads, that account for 77% of the nation's infrastructure.
New York City's Ten-Year Capital Strategy allocates $5.4 Billion for the rehabilitation of approximately 8,238 lane miles of its streets. This includes
- $1.6 Billion for resurfacing (patching potholes)
- $2.4 Billion for reconstruction.
Current methods used to survey streets range from:
- Citizens calling in potholes on an ad-hoc basis, or reporting via smartphone apps.
- “Windshield surveying” where a trained inspector assigns a score to the quality of a street based on his/her judgement along with a scoring methodology that dates back to the '70s. (Pavement Condition Index)
- Bulky, expensive, military grade laser equipment that provide high precision data only for a small sample of streets. Even if a city commits to surveying all their streets, which can cost in the millions, this data is only a snapshot in time and significantly loses its value over time.
What's missing is a low-cost method to collect continuous street quality data for ALL city streets in a consistent and methodical manner.
Our goal is to help cities and public works managers answer a simple question:How quickly are each of my city's streets deteriorating?
As cities witness the rise of mobility options in the form of scooters, e-bikes and autonomous vehicles, they need digital tools to ensure that streets, bike lanes and assets are accounted for and maintained at cost.
To this end, we develop SQUID, a low cost data platform that integrates open source technologies to combine street imagery and ride quality data to provide a visual ground truth for all the city's streets.
SQUID was a recipient of the 2016 Prototyping fund from the Knight Foundation.
SQUID started out as a hardware device, a $30 Raspberry Pi micro-computer fitted with accelerometer and GPS sensors, naive optimism and a persistence to prove the initial hypothesis. After collecting our first dataset on the streets of New York, we set out to polish our "lump of clay".
We currently use OpenStreetCam as the primary method to collect street imagery and ride quality data. This approach allows cities and municipalities simply download an app and start collecting data.
We worked with City of New York's Office of Operations and their SCOUT Team to collect 400+ miles of data from a single vehicle in just over 1 week!
Imagine, if just 15 vehicles vehicles were used to collect street imagery and ride quality data, we could achieve a complete and up-to-date street condition surveys across the entire city in mere weeks!
The City of Syracuse, NY invites us to prototype with their Public Works Department.
Between April 14 - 28, 2016, we collected an estimated 500 miles of street imagery (over 110,000 images) in just 10 days using a single vehicle with little manual intervention, demonstrating the scalability of this approach to inspect an entire city's street infrastructure.
We worked with students from NYU's Center for Urban Science and Progress and used OpenStreetCam, an open-source mobile application purposefully designed to collect street imagery and repurpose SQUID for bike lane inspections giving birth to SQUID BIKE!
We are currently building towards a Computer Vision approach to partially automate the detection of street defects such as cracks and large potholes and street assets.
We welcome feedback, ideas and support on how SQUID can be used to empower cities be proactive, open, and transparent around their public works.
- Route Fifty, A City Data Collaborative for the Age of Autonomous Vehicles
- New York Times, Why are the streets always under construction?
- Fast Company, A new cheap way to quickly map your city's potholes.
- FOX news(video), Smart Cities: The pothole problem.
- Staten Island Live, A 21st century proposal for Street maintenance.
- WRVO, SQUID to give Syracuse better feel for needed road repairs.
- Syracuse.com, Syracuse to map every pothole with truck-mounted camera, $35 computer.
- Forbes Tech Blog, The Knight Foundation Funds 20 Media Tech Projects.
- Metro New York, Filling potholes faster.