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Project name and Acronym

EMERALD – AI and Process Automation for Sustainable Entertainment and Media

Project Code




Financing Program

Horizon Europe

Promotor/ Coordinator

Universidad Pompeu Fabra

Consortia Partners

Universidad Pompeu Fabra | Brainstorm Multimedia SL | British Broadcasting Corporation | Disguise Systems Limited | Filmlight GMBH | The Provost, Fellows, Foundation Scholars & other members of Board, of the College of the Holy & Undivided Trinity Of Queen Elizabeth Near Dublin | MOG Technologies SA


30 months

Total Eligible Costs (€)

317.200 €

EU Grant Amount (€)


Main objective

To develop and demonstrate exemplary tools for the digital entertainment and media industries using AI Machine Learning and Big Data technologies, to automate and speed processing, increase production efficiency, use less energy and increase the quality of content. There is a massive increase in the volume of video-based and extended reality content, with an unsustainable demand for skilled human resources, data processing and energy. EMERALD aims to meet the challenge by developing process automation for sustainable media creation; creating a testbed for measuring the energy used in media computation; developing more efficient data use for AI/ML in entertainment and media applications; reducing the power demands for large-scale media data processing; and creating acceptance and demand for AI and sustainable production technologies in the entertainment and media industries.


Objective 1: Develop tools for sustainable digital content creation using ML and process automation.
Objective 2: Develop open-source tools for quantifying granular energy consumption in video pipelines.
Objective 3: Develop more efficient data use in entertainment and media applications.
Objective 4: Reduce the power demands for large-scale digital content processing.
Objective 5: Create acceptance and demand for AI and sustainable entertainment and media.

Work Packages

Work Package 1: Project Management.
Work Package 2: AI-supported automation of tools and methods for sustainable digital content creation.
Work Package 3: Energy measurement framework for content processing.
Work Package 4: Efficient data use in entertainment and media applications.
Work Package 5: Reduced power demands for large-scale digital content processing.
Work Package 6: Acceptance and demand for sustainable entertainment and media.


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