Machine Vision on Roadways
The New Age of Maintenance
Utilizing dash cam footage from inside thousands of cars already on roadways and machine learning, Payver can automatically detect anything the eye can see.
From pot holes to traffic light outages, Payver provides real time insights into the quality of your roadways. Departments from across the country are piloting Payver to increase safety, sustainability, and efficiency on their roadways.
If you can see it, so can Payver.
Safety is a Priority
Smart Work Zones
With Payver, you can gain automatic insights into the condition of your work zones.
Monitor the Condition of Bus Stops
Using our network of dashcam imagery and machine vision, we can automatically detect bus stops and bus shelters and provide insights on
Road way view into the condition of bus shelters from the comfort of your desk
Detect Safety Critical Assets
Automatically get notified if a roadside asset needs maintenance
Preserve the Life of Pavement
Using machine vision, Payver can automatically detect cracking, striping conditions, and score pavement according to the PASER scale and HD PCI- all within 1% accuracy of LiDar.
Get insights on cracking, PASER analysis, and striping conditions
Save money and resources
- Payver can detect if street lights are not on at night or on during the day
- Detect power lines: line sagging, vegetation encroachment, and leaning poles
- Save energy and increase safety
Real-Time Images Whenever and Wherever you Want
Light up your maps with roadway images from dashcams already in over 400,000 cars. We can deliver images in as little as 60 seconds of a car passing by. Simply click on a point and Payver will gather images until you tell it to stop.
We have over 50 detection models
Payver can currently detect over 50 different assets and we are currently building more models.
Departments Using Payver
Blyncsy's Collaboration with The University of Utah's Deep Learning Certificate Program
The University of Utah's Deep Learning Certificate Program is collaborating with Blyncsy to help students develop deep technology talent. Part of the R430, Deep Technology Initiative, students are utilizing Blyncsy Cloud to apply artificial intelligence and new techniques to push the boundaries of transportation system management.