For several years, alongside the traditional and professional interfaces dedicated to digital audio (such as AES/EBU, ADAT, MADI), numerous remote control solutions have been developed based on shared or dedicated use of network infrastructures.

These solutions,  mainly based on proprietary technologies, are remains “islands” that tend to limit the interoperability between equipments and systems, leaving the role of “bridge” to the single devices or to the tradtional interfaces.

In this context, the standardization efforts occurred in AES (with AES67 and AES70 standards) and the job that is addressing normative entity the solutions for the Video Over IP transport are the  Networked Audio world changing elements.

MULTIDRONE is an EC funded project of the H2020 research programme.

The recent technological advancement of computing systems allows today to find computers with extremely advanced numerical processing capabilities. In particular, the use of Graphics Processing Units (GPUs) for image and multimedia content processing and classification is experiencing a phase of intense development thanks to the deep-seated scientific research conducted in recent years (Deep Learning). Deep Learning is a branch of Machine Learning that uses complex neural networks for a variety of applications. Among these, the application area of  automatic classification of audiovisual content is certainly one of the most interesting from the strategic point of view for RAI.

Visual search technology allows users to search and match image and video contents depicting the same objects, such as buildings, paintings and logos, based on visual similarities and without the need of querying for manually generated metadata.

RAI CRIT is supporting research to extend cloud object store technologies to address emerging media industry requirements, such as scalability, efficiency and adaptability of production and archiving workflows.