technology
Digital Twin Maps
Smart intersections - smart crosswalk
Smart intersections - smart crosswalk
A digital twin map of a traffic intersection or a road section is a virtual representation of the physical intersection that includes real-time data from sensors and other sources such as cameras, lidars, and GPS systems. The digital twin map can be used to visualize and analyze the traffic environment in real-time allowing traffic control to improve public safety by sending instant alerts to vehicles and road users to avoid collisions, optimize traffic flow, and reduce congestion
Smart intersections - smart crosswalk
Smart intersections - smart crosswalk
Smart intersections - smart crosswalk
Real time high precision localization using any combination of cameras and lidars enables a rapid transformation of city intersections to smart intersections. A single camera can make the roads safer. Connectivity can scale sensor systems to cover wider areas and overcome occlusion, weather, and sensor resolution and sensitivity issues
AI Powered Sensors
Advanced perception for autonomous driving and ADAS
Advanced perception for autonomous driving and ADAS
AI-powered traffic sensors include cameras and lidars equipped with artificial intelligence (AI) capabilities and capable of processing and analyzing visual data in real time to localize and track vehicles, pedestrians, and other objects in the surrounding area. Smart traffic sensors can be used to provide real-time traffic alerts to drivers, help reduce congestion, and automate transportation safety
Advanced perception for autonomous driving and ADAS
Advanced perception for autonomous driving and ADAS
Advanced perception for autonomous driving and ADAS
Our Technology achieves the highest level of full perception and precision localization for vehicles using any combination of built-in vehicle sensors provided by ADAS vendors, Current vehicles can be empowered with smart perception using our cooperative-AI methods with infrastructure sensors
Precise localization and detection
CAPLOC
Precise localization using connected traffic cameras and lidars involves using a network of AI-powered cameras, lidars, and other sensors that are connected to computer vision system and are able to communicate with one another. Collectively, these sensors can be used to identify the precise location of a vehicle or pedestrian within a certain area, by triangulating their position based on the images captured by the different cameras. This can be done in real-time, allowing for real-time tracking and monitoring of the movement of people or vehicles within the area covered by the camera network. Precise localization using connected traffic cameras can be used for a variety of purposes, including traffic management, public safety, and transportation planning.
Precision localization using connected AI-powered sensors provides a range of benefits for automated traffic safety, including:
- Improved visibility: Sensors can detect and track vehicles, pedestrians, and other objects in real-time, providing a comprehensive view of the traffic environment.
- Enhanced situational awareness: Sensors can be used to identify and alert drivers to potential hazards, such as pedestrians crossing the road or other vehicles in blind spots.
- Predictive analytics: AI-powered sensors can analyze data from the traffic environment to predict where and when accidents are likely to occur, allowing authorities to take preventative measures.
- Increased efficiency: Connected sensors can help optimize traffic flow, reducing congestion and improving the efficiency of the transportation network.
- Automated safety: By providing drivers with real-time information about their surroundings and alerting them to potential hazards, sensors can help reduce the likelihood of accidents and improve overall traffic safety.
Overall, the use of connected AI-powered sensors can help to make roads and highways safer for all users, and can contribute to the reduction of accidents and fatalities
