Our counting algorithm detects all vehicles on the road, with a high reliability.
As a replacement for counting loops, intrusive and difficult to maintain.
Our solution automatically classifies the traffic flow according to the main typologies: light vehicles, trucks, motorcycles, buses, etc.
The classification can be defined according to specific customer needs.
The solution enables the establishement of masking zones for each camera, providing a specific count per zone.
This functionality is particularly adapted to the processing of dedicated lanes.
Data collection only by camera sensors on roadside. Therefore, no intervention on the roadway is required, neither for installation nor for maintenance.
Compatible with most cameras - few specific constraints on the equipment used, facilitating system maintainability and scalability.
Possibility to progressively integrate additional video detection functionalities, for example: detection of certain types of incidents like congestion, stopped vehicles, etc.
Data confidentiality and respect of road users privacy are at the heart of all our developments. Our Counting solution is therefore, as all Cyclope.ai products, fully compliant with the GPDR.
For analysing traffic travelling on major road axis, with vehicle speeds between 90 km/h and 130 km/h.
To understand the uses on axes with a dense and varied traffic, in particular for metropolitan ring-roads or beltways.
To prioritize soft mobilities and fluidify congestion zones, through better management of the traffic light cycle.
This solution is based on advanced proprietary technologies in Deep Learning and Computer Vision, developed by our Data Science expert team.
LIMA EXPRESA is in charge of operating the Linéa Amarilla, a network of 25km expressways around the city of Lima, capital of Peru.
For maintenance reasons (planning and prioritization) and a better understanding of uses which will then enable them to re-adapt their offers, LIMA EXPRESA called on Cyclope.ai to deploy a video-based only traffic analysis solution.
of processed videos per week
Classes to identify:
light vehicle, truck, motocycle, bus
precision rate by class
camera streams treated
The Aix-Marseille-Provence metropolitan area and its partners have drawn up a mobility plan, which one of the major measure is the implementation of several public transport dedicated lanes on expressways. By 2023, it is already planned to set up 100 kilometers of reserved lanes between Aix-en-Provence and Marseille. At the end of a public Call for Tenders procedure, Cyclope.ai was selected by the DIR Méditerranée in July 2019, to participate in outsourcing to Ingerop in the evaluation of the impact of these reserved lanes.
Of traffic analysis
for each assessment mission
Since 2014, the PCE Lutèce (traffic monitoring center of Paris City) has launched several experiments that promoted the “active” and clean modes of travel - pedestrians, bikes, scooters - used more and more by Parisians. Indeed, in the actual traffic lights management rules, sensors are mainly taking into account the motorized vehicles flow. This very often leads to dangerous situations for the new road users, particularly vulnerable. Thus, within the framework of Datacity (a data innovation program dedicated to Smart City), the Paris City Hall launched a challenge on "How to integrate soft mobilities into traffic light intersections management ?", in which Cyclope.ai participated as the main technology supplier.
equipped with a
system in the 13th arrondissement
for more than 6 months
of treatment time