Visual AI for transport networks monitoring
TraCK, the Transport Camera Kit, is a collection of advanced visual AI analytics to perform road asset inventory while monitoring their quality. Feed your day-by-day operations and predictive maintenance with actual data from the field, captured with a single pass.
Turn connected vehicle cameras into active road sentinels
Add unprecedented capabilities to your cameras in 3 simple steps:
1
INSTALL
TraCK analytics can be installed on vehicle PCs to process images in real time or can run in post processing mode .
2
ANALYSE
TraCK analytics create a database of road assets and defects, assigning to each detected feature its GPS position .
3
REACT
Receive real time notifications directly from vehicles on the road, or browse the most relevant data collected by TraCK when they come back.
How it works?
TraCK analytics work with images captured by vehicle cameras to automatically generate information and reports on the road pavement and road assets conditions. TraCK analytics run both in real-time on a connected vehicle PC equipped with GPS, to perform the most critical analyses, and in post-processing when the vehicle returns to base, to extract information that doesn't need to be transmitted immediately.
Key Benefits
TraCK analytics return geolocated information on many aspects of the road infrastructure, like roadworks compliance, tunnel lights status or vegetation interference. You may equip your own vehicles with cameras and an automotive grade PC for continuous and frequent monitoring, or you may rely on our camera kit to use any vehicle for occasional surveys. No matter what’s your choice, TraCK analytics will always capture images and provide data at cruising speed (yes, up to 100 km/h on highways).
obtain geolocated information
available on kits for occasional surveys
monitor multiple road assets
working at cruising speed
Key Features
Data returned by TraCK analytics are structured in JSON format, containing information on the vehicle position, a timestamp, and descriptions of the identified features. Depending on the analytics, these can be coupled with supporting visuals like graphs, camera snapshots or time lapse videos. TraCK data are immediately ready to be used in control room dashboards, managed with a GIS or exchanged with any third-party decision support system.
Edge native applications
Output ready for GIS tools
Easy configuration
Milestone XProtect integrated
Integrated anonymizer for faces and license plates
Ready for IoT architectures
Analytics
Road signs
Visual AI for road signs inventory and monitoring, on the go
This function analyses images captured at high frame rate from a vehicle camera to identify and geolocate the road signs along the way. The kind and position of each road sign is stored in a database, which is the base for subsequent automated analyses like compliance control of form and position (not only for single signs, but also for sequences like these in roadworks) or check for missing elements.
Tunnels
Visual AI for periodic inspection of tunnel assets status and conditions
Tunnels adapts camera parameters to enhance the visibility of different features, like the sides of a tunnel or its lamps, in environments with extreme contrasts between light and shadow. This way, this advanced visual AI can count and report the number of lights on, or seize the overall quality of tunnel side coating.
Vegetation
Visual AI for inspecting the interference of vegetation on roadsides
Plant growth is among the major concern in road infrastructure maintenance. With Vegetation, images of the roadsides captured by front and side vehicle cameras are processed to identify herbs, shrubs or tree branches that may interfere with the traffic flow. The geolocated data provided by Vegetation can be used to plan cleaning interventions to maintain a proper safety margin.
Road pavement
Visual AI for mapping paving materials on road surface and defects like cracks, potholes and discontinuities
It is full of solutions out there that allow you to measure and monitor every physical parameter of the road surface. But in most cases, identifying potholes, cracks and discontinuities on different types of road pavement is more than enough, and this is where cameras and visual AI come into play. Whether they are processed in real time or not, the generated data can be displayed on maps or used to calculate road pavement quality indices, thus streamlining maintenance planning.
Powered by
TraCK is powered by Arco, the service-oriented software platform developed by WaterView to run visual AI on dedicated servers or edge AI units. Arco works with virtually any camera, and exchanges data with third-party solutions by using standard IoT communication protocols. Arco is a Swiss knife offering several tools like universal grabber for camera interfacing, native image anonymization, advanced load balancing, services for remote maintenance and diagnostics, as well as versatile data exchange via MQTT, Kafka, email, Telegram and more.
Discover Arco