Vehicle Detection
Building upon every cities’ mission to provide for the safe, efficient, and convenient movement of people and goods, NoTraffic is leveraging cloud computing, AI, and computer vision to digitize urban intersections, connecting the infrastructure to the grid.
NoTraffic Detection Package empowers cities to digitize their urban intersections in 2 hours, through a plug & play IoT sensor offering superior detection. It also includes our signature AI and machine-learning algorithms for detection & classification, along with a 24/7/365 always manned support center.
AI Sensor
Control Unit
VMC
Product Sheets
COMING SOON:
NoTraffic Nexus Unit
How the Nexus unit works
The Nexus unit is a key component of the NoTraffic platform, which includes several technologies that work together to create an intelligent transportation system.
In-cabinet installation: The unit is installed in the electrical cabinet at an intersection, where it integrates with and directs the existing traffic light controller.
Sensor communication: It receives traffic demand data from AI sensors equipped with radar and video that are mounted on the traffic poles. These sensors provide a constant, human-eye-level view of all road users, including vehicles, pedestrians, and cyclists.
Edge and cloud processing: It uses high-powered AI and edge computing to process sensor data locally, making quick decisions about signal timing and coordination. The unit also connects to the cloud to provide real-time remote management and advanced analytics.
System integration: The Nexus unit can operate either as a standalone connectivity gateway or as part of NoTraffic's full AI platform. This allows cities to upgrade their traffic management capabilities incrementally without replacing all existing hardware.
Vehicle-to-everything (V2X) capability: The platform is equipped to communicate with connected vehicles, preparing road infrastructure for future mobility technology.
If your agency’s goals are to reduce congestion, improve road safety, reducing emissions, or to enable future upgrades, then the future is already here.
Better, more accurate detection
Through a fusion of Video, Radar and Artificial Intelligence using techniques such as Machine Learning and Deep Learning we are able to learn over time edge cases. Those findings get distributed across all of your sensors and help the entire platform get even more accurate over time.