A network of excellence for distributed, trustworthy, efficient and scalable AI at the Edge

Informations projet

dAIEDGE

N° de convention de subvention: 101120726

DOI

10.3030/101120726

Date de signature de la CE 27 Juin 2023

Date de début 1 Septembre 2023

Date de fin 31 Août 2026

Financé au titre de

• Digital, Industry and Space

Coût total

€ 10 746 872,00

Contribution de l’UE

€ 10 746 872,00

Coordonné par

DEUTSCHES FORSCHUNGSZENTRUM FUR KUNSTLICHE INTELLIGENZ GMBH
Germany

CORDIS fournit des liens vers les livrables publics et les publications des projets HORIZON.

Les liens vers les livrables et les publications des projets du 7e PC, ainsi que les liens vers certains types de résultats spécifiques tels que les jeux de données et les logiciels, sont récupérés dynamiquement sur OpenAIRE .

Livrables

Other (5)

Pan-European Workshop on Edge AI technological trends and developments

Workshop of the NoE on future trends of edge AI

Workshop on industrial and investments priorities for successful AI at the Edge in Europe - Workshop Nr 1

Workshop for collaboration with PPP and industrial stakeholders

Seminars, workshop and events - Event Nr 1

Dissemination events, multiplier events

Roundtable on Edge AI functional and non-functional requirements

Expert workshop for requirements gathering and discussion

Workshops (co-organized with other pillars) - Workshop Nr 1

Two-day workshop for alignment with all pillars of the EU AI Lighthouse

Documents, reports (18)

Algorithms and methods prototype

First version of the edge AI algorithms

Call Announcement and Guide for Applicants - Call Nr 2

Open Call Package documents

Middleware prototype

First version of the middleware

Intermediate report and risk log - Report Nr 1

Updated report and log for risk prevention and mitigation (every 6 months)

Platform prototype

First version of the hardware platform solutions

dAIEDGE Communication, Dissemination and Exploitation plan

Plan of the project communication, dissemination and exploitation

Report on Edge AI functional and non-functional requirements

Comprehensive report on edge AI requirements

Call Announcement and Guide for Applicants - Call Nr 1

Open Call Package documents

Intermediate reports and risk log - Report Nr 3

Updated report and log for risk prevention and mitigation (every 6 months)

Evolutive infrastructure inventory - Report Nr 1

Inventory of existing infrastructure for edge AU

Quality assurance plan

Measures for ensuring quality

Risk management plan

Plan and measures for risk prevention and mitigation

Distributed network design

Design and architecture of the distributed network of frameworks

Intermediate reports and risk log - Report Nr 2

Updated report and log for risk prevention and mitigation (every 6 months)

Reference document on European AI Lighthouse implementation

Plans and recommendations organisation of the EU AI Lighthouse

Evolutive infrastructure inventory - Report Nr 2

Inventory of existing infrastructure for edge AU

dAIEDGE Communication, Dissemination and Exploitation plan - update Nr 1

First update of the dAIEDGE Communication, Dissemination and Exploitation plan

Report on Use Case definition, demonstration setup and validation plan

Complete and refined definition of the three use cases with evaluation plan

Data Management Plan (2)

Final data management plan

Plan for management of data in the NoE and in the consortium - final version

Initial data management plan

Plan for management of data in the NoE and in the consortium - intial version

Publications

Peer reviewed articles (12)

Data in Brief

Auteurs: Jesus Ruiz-Santaquiteria; Juan D. Muñoz; Francisco J. Maigler; Oscar Deniz; Gloria Bueno
Publié dans: Data in Brief, 2023, ISSN 2352-3409
Éditeur: Elsevier BV
DOI: 10.1016/j.dib.2024.110030

WRIT: Web Request Integrity and Attestation Against Malicious Browser Extensions

Auteurs: Giorgos Vasiliadis, Apostolos Karampelas, Alexandros Shevtsov, Panagiotis Papadopoulos, Sotiris Ioannidis, Alexandros Kapravelos
Publié dans: IEEE Transactions on Dependable and Secure Computing, Numéro 21, 2024, ISSN 1545-5971
Éditeur: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/TDSC.2023.3322516

Concealed Weapon Detection Using Thermal Cameras

Auteurs: Juan D. Muñoz, Jesus Ruiz-Santaquiteria, Oscar Deniz, Gloria Bueno
Publié dans: Journal of Imaging, Numéro 11, 2025, ISSN 2313-433X
Éditeur: MDPI AG
DOI: 10.3390/JIMAGING11030072

Neural Computing and Applications

Auteurs: Anibal Pedraza; Oscar Deniz; Harbinder Singh; Gloria Bueno
Publié dans: Neural Computing and Applications, Numéro Springer, 2024, ISSN 0941-0643
Éditeur: Springer Verlag
DOI: 10.1007/s00521-024-10141-1

A Cautionary Tale: On the Role of Reference Data in Empirical Privacy Defenses

Auteurs: Caelin Kaplan, Chuan Xu, Othmane Marfoq, Giovanni Neglia, Anderson Santana de Oliveira
Publié dans: Proceedings on Privacy Enhancing Technologies, Numéro 2024, 2023, ISSN 2299-0984
Éditeur: Privacy Enhancing Technologies Symposium Advisory Board
DOI: 10.56553/popets-2024-0031

Real-Time Edge Computing vs. GPU-Accelerated Pipelines for Low-Cost Microscopy Applications

Auteurs: Gloria Bueno, Lucia Sanchez-Vargas, Alberto Diaz-Maroto, Jesus Ruiz-Santaquiteria, Maria Blanco, Jesus Salido, Gabriel Cristobal
Publié dans: Electronics, Numéro 14, 2025, ISSN 2079-9292
Éditeur: MDPI AG
DOI: 10.3390/ELECTRONICS14050930

DLAS: A Conceptual Model for Across-Stack Deep Learning Acceleration

Auteurs: Perry Gibson, Jose Cano, Elliot Crowley, Amos Storkey, Michael O'Boyle
Publié dans: ACM Transactions on Architecture and Code Optimization, 2024, ISSN 1544-3566
Éditeur: Association for Computing Machinery (ACM)
DOI: 10.1145/3688609

Leveraging AutoEncoders and chaos theory to improve adversarial example detection

Auteurs: Anibal Pedraza, Oscar Deniz, Harbinder Singh, Gloria Bueno
Publié dans: Neural Computing and Applications, Numéro 36, 2024, ISSN 0941-0643
Éditeur: Springer Science and Business Media LLC
DOI: 10.1007/S00521-024-10141-1

Leveraging AutoEncoders and chaos theory to improve adversarial example detection

Auteurs: Anibal Pedraza, Oscar Deniz, Harbinder Singh, Gloria Bueno
Publié dans: Neural Computing and Applications, Numéro 36, 2024, ISSN 0941-0643
Éditeur: Springer Science and Business Media LLC
DOI: 10.1007/S00521-024-10141-1

Data in Brief

Auteurs: Jesus Ruiz-Santaquiteria; Juan D. Muñoz; Francisco J. Maigler; Oscar Deniz; Gloria Bueno
Publié dans: Data in Brief, 2023, ISSN 2352-3409
Éditeur: Elsevier BV
DOI: 10.1016/J.DIB.2024.110030

Fast Transciphering Via Batched And Reconfigurable LUT Evaluation

Auteurs: Leonard Schild, Aysajan Abidin, Bart Preneel
Publié dans: IACR Transactions on Cryptographic Hardware and Embedded Systems, Numéro 2024, 2024, ISSN 2569-2925
Éditeur: Universitatsbibliothek der Ruhr-Universitat Bochum
DOI: 10.46586/tches.v2024.i4.205-230

ShareBERT: Embeddings Are Capable of Learning Hidden Layers

Auteurs: Jia Cheng Hu, Roberto Cavicchioli, Giulia Berardinelli, Alessandro Capotondi
Publié dans: Proceedings of the AAAI Conference on Artificial Intelligence, Numéro 38, 2024, ISSN 2374-3468
Éditeur: Association for the Advancement of Artificial Intelligence (AAAI)
DOI: 10.1609/aaai.v38i16.29781

Other (2)

Kraken: An Open-Source RISC-V SoC for Ultra-Low Power Multi-Modal Perception

Auteurs: Viviane Potocnik; Alfio Di Mauro; Christoph Leitner; Moritz Scherer; Georg Rutishauser; Lorenzo Lamberti; Luca Benini
Publié dans: 2024
Éditeur: www.researchsquare.com
DOI: 10.21203/rs.3.rs-4023416/v1

Leveraging AutoEncoders and chaos theory to improve adversarial example detection

Auteurs: Anibal Pedraza; Oscar Deniz; Harbinder Singh; Gloria Bueno
Publié dans: Neural Computing and Applications, 2024, ISBN 1826518275
Éditeur: Neural Computing and Applications (2024)
DOI: 10.1007/s00521-024-10141-1

Conference proceedings (13)

Efficient Tiny Machine Learning for Human Activity Recognition on Low-Power Edge Devices

Auteurs: Vinamra Sharma, Danilo Pau, José Cano
Publié dans: 2024 IEEE 8th Forum on Research and Technologies for Society and Industry Innovation (RTSI), 2024
Éditeur: IEEE
DOI: 10.1109/RTSI61910.2024.10761203

PELS: A Lightweight and Flexible Peripheral Event Linking System for Ultra-Low Power IoT Processors

Auteurs: Alessandro Ottaviano, Robert Balas, Philippe Sauter, Manuel Eggimann, Luca Benini
Publié dans: 2024 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2024
Éditeur: IEEE
DOI: 10.23919/DATE58400.2024.10546868

FedStale: leveraging Stale Updates in Federated Learning

Auteurs: Angelo Rodio, Giovanni Neglia
Publié dans: Frontiers in Artificial Intelligence and Applications, ECAI 2024, 2024
Éditeur: IOS Press
DOI: 10.3233/FAIA240849

Scheduling with Fully Compressible Tasks: Application to Deep Learning Inference with Neural Network Compression

Auteurs: Tiago Da Silva Barros, Frédéric Giroire, Ramon Aparicio-Pardo, Stéphane Pérennes, Emanuele Natale
Publié dans: 2024 IEEE 24th International Symposium on Cluster, Cloud and Internet Computing (CCGrid), 2024
Éditeur: IEEE
DOI: 10.1109/CCGrid59990.2024.00045

Weapon Detection Using PTZ Cameras

Auteurs: Juan Daniel Muñoz, Jesus Ruiz-Santaquiteria, Oscar Deniz, Gloria Bueno
Publié dans: Communications in Computer and Information Science, Robotics, Computer Vision and Intelligent Systems, 2024
Éditeur: Springer Nature Switzerland
DOI: 10.1007/978-3-031-59057-3_7

Exploiting Multiple Sequence Lengths in Fast End to End Training for Image Captioning

Auteurs: Jia Cheng Hu, Roberto Cavicchioli, Alessandro Capotondi
Publié dans: 2023 IEEE International Conference on Big Data (BigData), 2024
Éditeur: IEEE
DOI: 10.1109/BIGDATA59044.2023.10386812

The Bidirectional Awareness Induction in Autoregressive Sequence-To-Sequence Models

Auteurs: Jia Cheng Hu
Publié dans: 31th International Conference on Neural Information Processing (ICONIP) abstracts, 2025
Éditeur: Tuwhera
DOI: 10.24135/ICONIP25

BatDeck: Advancing Nano-Drone Navigation with Low-Power Ultrasound-Based Obstacle Avoidance

Auteurs: Hanna Müller, Victor Kartsch, Michele Magno, Luca Benini
Publié dans: 2024 IEEE Sensors Applications Symposium (SAS), 2024
Éditeur: IEEE
DOI: 10.1109/SAS60918.2024.10636518

Minimum Time Maximum Fault Coverage Testing of Spiking Neural Networks

Auteurs: Spyridon Raptis, Haralampos-G. Stratigopoulos
Publié dans: 2025 Design, Automation & Test in Europe Conference (DATE), 2025
Éditeur: IEEE
DOI: 10.23919/DATE64628.2025.10993048

Work in Progress: Linear Transformers for TinyML

Auteurs: Moritz Scherer, Cristian Cioflan, Michele Magno, Luca Benini
Publié dans: 2024 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2024
Éditeur: IEEE
DOI: 10.23919/DATE58400.2024.10546828

Scheduling Machine Learning Compressible Inference Tasks with Limited Energy Budget

Auteurs: Tiago Da Silva Barros, Davide Ferre, Frederic Giroire, Ramon Aparicio-Pardo, Stephane Perennes
Publié dans: Proceedings of the 53rd International Conference on Parallel Processing, 2024
Éditeur: ACM
DOI: 10.1145/3673038.3673106

Satellite on-board processing of synthetic aperture radar data for rapid delivery of latency sensitive maritime information products

Auteurs: Dominik Günzel, Srikanth Mandapati
Publié dans: Active and Passive Remote Sensing of Oceans, Seas, and Lakes, 2025
Éditeur: SPIE
DOI: 10.1117/12.3040646

FedLoRa: IoT Spectrum Sensing Through Fast and Energy-Efficient Federated Learning in LoRa Networks

Auteurs: Fabio Busacca, Stefano Mangione, Giovanni Neglia, Ilenia Tinnirello, Sergio Palazzo, Francesco Restuccia
Publié dans: 2024 IEEE 21st International Conference on Mobile Ad-Hoc and Smart Systems (MASS), 2024
Éditeur: IEEE
DOI: 10.1109/MASS62177.2024.00047