To help decision-making in the management of road assets, we offer an innovative offer for digitizing road equipment.
Our tools, based on artificial intelligence, make it possible to inventory and automatically analyze road infrastructure.
Our solution, based on data provided by VIAPIX Acquisition, detects, identifies and geolocates road objects:
- Vertical signage (vertical police signage, directional signage, traffic lights, etc) ;
- Horizontal signage (pedestrian crossings, arrows, bike icons, etc) ;
- Urban furniture (streetlamps, bollards, etc).
Thanks to AI, automatic object recognition allows efficient and reliable restitution of results in a short time.
In addition, with our degradation detection algorithms, our solution automatically analyses the condition of the roads. Signs of fatigue and anomalies visible on the surface are referenced and qualified. We classify these degradations into longitudinal, transverse cracks, crazing, potholes, etc.
High-performance automatic auscultation allows optimized, precise and eco-responsible management of road assets.
VIAPIX systems offers a new tool for automatically conducting an inventory of road signs.
The automatic recognition of objects is done using methods and techniques based on artificial intelligence allowing efficient and reliable rendering of results.
Based on the images from the three cameras of the VIAPIX Acquisition module, we deploy a powerful tool to detect, classify and geolocate all the elements of the infrastructure located in the field of view of our acquisition system.
Our tool automatically extracts two signalling categories:
- Spot markings: arrows icons, pedestrian crossing, bike icons
- Continuous markings: solid lines, broken lines, dissuasion lines
- Police signs
- Directional signage
Our automatic inventory solution saves productivity time, and also checks compliance with standards in terms of installation and positioning.
This analysis provides managers with information on the surface condition of the pavement to facilitate decision-making on the prioritization of maintenance interventions.
WE PROPOSE A TOOL FOR THE EXTRACTION AND CLASSIFICATION OF ROAD DISORDERS.
Based on Deep Learning and thanks to a pixel-by-pixel analysis of images from VIAPIX Acquisition, our solution makes it possible to extract:
- Longitudinal cracks,
- Transversal cracks,
Nous proposons un outil d’extraction et de classification des désordres de la chaussée.
Basée sur le Deep Learning et grâce à une analyse pixel par pixel des images issues de VIAPIX Acquisition, notre solution permet d’extraire :
- Fissures longitudinales,
- Fissures transversales,
Cette analyse fournit aux gestionnaires les informations sur l’état superficiel de la chaussée pour faciliter la prise de décision de priorisation des interventions d’entretien.