ANT
Financiado
Embedded AI Systems and Applications
Embedded Artificial Intelligence (AI) has emerged as a transformative technology with immense potential to revolutionise various domains, spanning from robotics and healthcare to environmental monitoring and the Internet of Things...
Embedded Artificial Intelligence (AI) has emerged as a transformative technology with immense potential to revolutionise various domains, spanning from robotics and healthcare to environmental monitoring and the Internet of Things. This Doctoral Network (DN) project ANT aims to train a network of 15 excellent Doctoral Candidates (DCs) by addressing the fundamental challenges of Embedded AI and accelerating the development of Embedded AI systems and applications through an innovative and interdisciplinary research and training program. ANT consists of four interconnected Work Packages (WPs) that encompass different aspects of Embedded AI. WP1 tackles the challenges in designing low-footprint standalone Embedded AI models under resource constraints and with diverse contexts and evolving environments. WP2 goes beyond standalone Embedded AI and designs innovative distributed and scalable learning solutions for heterogeneous Embedded AI networks under energy and bandwidth constraints. WP3 enhances the trustworthiness of Embedded AI with explainability, robustness, security, and privacy. ANT concludes in WP4 with a concerted effort to transfer fundamental research contributions to industry-relevant applications in autonomous robotics, underwater IoT, mobile healthcare, and smart farming, boosting Europe’s position in the global AI market both from a talent and a technological perspective. These interdisciplinary and inter-domain research training, along with the comprehensive soft-skills training (spanning from presentation skills to intellectual property, marketing, and economics, etc.) will make ANT’s 15 DCs highly employable in various industries, academia, or public government bodies, and will position the EU at the forefront of the emerging revolution of Embedded AI on Things.
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Duración del proyecto: 47 meses
Fecha Inicio: 2025-02-01
Fecha Fin: 2029-01-31
Fecha Fin: 2029-01-31
Línea de financiación: concedida
El organismo HORIZON EUROPE notifico la concesión del proyecto
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
HORIZON-MSCA-2023-DN-01-01:
MSCA Doctoral Networks 2023
Cerrada
hace 11 meses
Líder del proyecto
TECHNISCHE UNIVERSITEIT DELFT
No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico
TRL
4-5
Perfil tecnológico
TRL
4-5