Descripción del proyecto
Unas tecnologías de cabina más inteligentes alzan el vuelo
El sector de la aviación requiere nuevas tecnologías rentables y fiables a fin de aumentar la seguridad y la competitividad. Este sector está sujeto a nuevas normativas, como el requisito TTL (hora límite de emisión del billete) para el equipaje de mano. El proyecto SmaCS, financiado con fondos europeos y dirigido por dos agentes clave en el desarrollo de sistemas de cámaras para aeronaves y tecnologías de aprendizaje automático (OTOMY Aviation y VICOMTECH), propone una tecnología avanzada para el control digitalizado del equipaje de cabina. El proyecto desarrollará un algoritmo de aprendizaje automático para el control del equipaje de cabina en condiciones de poca luz y contraste. También creará un método avanzado para realizar predicciones basadas en datos. Sus responsables trabajan asimismo en el diseño de un hardware de procesamiento imágenes que puede instalarse en aviones. En conjunto, esta tecnología innovadora promoverá opciones de seguridad para los sectores de la aviación y el transporte.
Objetivo
The SMACS project, led by OTONOMY Aviation and VICOMTECH, aspires to conceive a camera-based prototype solution for digitalized on-demand verification of TTL requirements for cabin luggage. It will be designed to be highly reliable, cost effective and easy to upgrade, with potential additional camera-based verification services.
To fulfil this ambition, the consortium will capitalise on 3 main pillars:
- A robust Machine Learning algorithm for cabin luggage recognition in low light and low contrast environment that will be built from VICOMTECH’s AI libraries and specific developments
- A highly innovative way to produce learning dataset based on videos coupled with synthetic 3D models
- An aircraft compliant, ultra-light, ultra-compact Image data processing hardware based on COTS, with highly adaptable CVMS interface connection capabilities.
VICOMTECH brings to the consortium its large experience and proven competencies in developing machine-learning based algorithms, notably for object recognition, and its rare and precious capacity to train algorithms from synthetic 3D models to reach higher performances at unmatchable costs.
OTONOMY Aviation brings to the consortium its deep knowledge of aeronautic compliant camera systems and camera implementation in aircraft cabins. Moreover, OTONOMY’s strong relationship with major actors of the ecosystem such as Airbus Interiors Services permitted to get a highly realistic synthetic model of an A320 aircraft that will be used for the algorithm training.
The SMACS project will generate new technology breakthrough for the use of IA in aeronautic and will bring new safety-related solutions to other sectors such as public transportations (trains, buses etc.).
It will also enable OTONOMY to introduce smart IA-empowered cameras in the aeronautic ecosystem, opening new and various opportunities for aeronautic competitiveness, safety and ecology. The derived products will generate an additional turnover of 10M$/year.
Ámbito científico
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensorsoptical sensors
- engineering and technologymechanical engineeringvehicle engineeringaerospace engineeringaircraft
- social sciencessocial geographytransportpublic transport
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
- natural sciencescomputer and information sciencesdata sciencedata processing
Palabras clave
Programa(s)
Régimen de financiación
IA - Innovation actionCoordinador
33700 Merignac
Francia