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19 September 2018

 

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Parifex targets growth with Nano-cam

First publishedin ITS World Congress
2018
Daily News
Day 2
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Nathalie Deguen of Parifex

French engineering firm Parifex has unveiled the Nano-Cam, its new sensor combined with intelligent software that analyses automatically, and in real time, all moving targets in its field of view.

Parifex says the new ultra-light and compact Nano-Cam lidar-based equipment technology can provide, in a single sensor, the same functionalities that would normally require several different pieces of equipment, including cameras, induction loops, and radar units.

Additionally, the company says accuracy is much better with the Nano-Cam; it provides 3D shapes and precise dimensions; has a larger field of view (360°) and a longer range and allows object recognition. Importantly, Nano-Cam works in extreme weather conditions, including rain, snow, and dust and is immune to lighting variations between day and night.

The Nano-Cam comes with software which provides a user-friendly application programming interface for Windows.  This sensor can be easily integrated into many applications, including smart parking, smart city, autonomous vehicles projects, and security and surveillance, enabling integrators to make the most of this cutting-edge technology while providing high flexibility. Parifex has already provided the Nano-Cam for an important autonomous vehicle research project in France. In this case, the device is installed on roundabouts and acts as additional eyes for the vehicle by covering all blind spots and communicating in advance any danger involving pedestrians crossing, cyclists or other vehicles. On receiving the information, the autonomous vehicle can react to the danger.

Another project that Parifex is involved with is a speed control system where the Nano-Cam performs multi offence detection: red light and railroad crossing; speed, lane-related (reserved lanes for taxis or buses) and tailgating violations; obstacle detection; and vehicles driving against the flow of traffic (wrong-way drivers).

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