Descripción del proyecto
Inteligencia artificial para monitorizar el tráfico en tiempo real
La rápida urbanización y el incremento continuo de las cifras de vehículos ha aumentado la preocupación por la seguridad de las carreteras. Como resultado, se han instalado sistemas de monitorización del tráfico en tiempo real para ayudar a los operadores para el control del tráfico y para situaciones de emergencia. El proyecto VISIONS, financiado con fondos europeos, desarrollará un sistema de monitorización del tráfico mediante transmisión de vídeo de alta calidad en ciudades inteligentes basado en métodos de inteligencia artificial (IA) aplicados al procesamiento y la transmisión de vídeo. Se tendrán en cuenta las características de los sistemas visuales de los humanos a la hora de determinar la asignación de la calidad del vídeo con el fin de limitar la capacidad necesaria para la transmisión de vídeo. Se implementará un método avanzado basado en redes neuronales profundas para permitir la reproducción y la transferencia de vídeo a resoluciones menores y se planeará un nuevo sistema de adaptación de la tasa de bits basado en el aprendizaje de refuerzo para garantizar la calidad de la experiencia.
Objetivo
With the rapid development of urbanization and continuous increase of vehicles on roadways, Intelligent Transportation Systems (ITS) play a key role in revolutionizing the way people commute. To make our cities safer and smarter, real-time traffic monitoring systems are deployed to help operators with observing traffic flows and identifying emergency situations.
This project aims to achieve real-time traffic monitoring with high-quality video transmission in smart cities, leveraging the emerging Artificial Intelligence methods in video processing and video streaming. Firstly, the features of human visual systems will be referred on video quality allocation to reduce the required bandwidth for video transmission. Next, an innovative method for end-to-end video processing based on Deep Neural Networks will be developed to allow the video rendering and streaming at a lower resolution and also restore/improve the quality at the user ends. Finally, a new bitrate adaption scheme based on Reinforcement Learning will be designed to accommodate the unexpected network dynamics, guaranteeing the Quality-of-Experience to be perceived by users. The expected outcome can promote safer and more efficient travel for millions of users in Europe and billions of users all over the world. Moreover, the results of this project can be used in other multimedia applications, such as cloud virtual reality, distance education, smart transportation, and healthcare where video processing and video streaming are needed.
To broaden the fellow’s knowledge horizon, a series of research, training, and knowledge transfer activities are planned. The new knowledge and skills imparted in these activities will further promote his academic portfolio and significantly enhance his career prosperity. The project will also play a solid foundation for the long-term and wide-range collaborations and eventually lead to more extensive impact of project results, from which both EU and China will benefit.
Ámbito científico
- engineering and technologycivil engineeringurban engineeringsmart cities
- natural sciencescomputer and information sciencesartificial intelligencemachine learningreinforcement learning
- natural sciencescomputer and information sciencessoftwaresoftware applicationsvirtual reality
- natural sciencescomputer and information sciencesartificial intelligencecomputational intelligence
Palabras clave
Programa(s)
Régimen de financiación
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinador
EX4 4QJ Exeter
Reino Unido