Intelligent and Sustainable Aerial-Terrestrial IoT Networks

Información del proyecto

INITIATE

Identificador del acuerdo de subvención: 101008297

DOI

10.3030/101008297

Fecha de la firma de la CE 1 Diciembre 2020

Fecha de inicio 1 Enero 2022

Fecha de finalización 31 Diciembre 2025

Financiado con arreglo a

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Coste total

€ 952 200,00

Aportación de la UE

€ 703 800,00

Coordinado por

THE UNIVERSITY OF EXETER
United Kingdom

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Resultado final

Open Research Data Pilot (1)

Data Management Plan (DMP)

This deliverable will define what data will be open for verification and reuse and how it will be curated and preserved and specify which datasets remain closed in order to take part in the Pilot on Open Research Data RRDP

Publicaciones

Peer reviewed articles (12)

Ubiquitous and Robust UxV Networks: Overviews, Solutions, Challenges, and Opportunities

Autores: Z. Li, G. Min, R. Peng, C. Luo, L. Zhang, C. Luo
Publicado en: IEEE Network, Edición 38(2), 2024, Página(s) 26-34, ISSN 0890-8044
Editor: Institute of Electrical and Electronics Engineers
DOI: 10.1109/mnet.2024.3352691

A Self-Adaptive Automatic Incident Detection System for Road Surveillance Based on Deep Learning

Autores: César Bartolomé-Hornillos, Luis M. San-José-Revuelta, Javier M. Aguiar-Pérez, Carlos García-Serrada, Eduardo Vara-Pazos, Pablo Casaseca-de-la-Higuera
Publicado en: Sensors, Edición 24, 2025, Página(s) 1822, ISSN 1424-8220
Editor: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/s24061822

Online Service Migration in Mobile Edge with Incomplete System Information: A Deep Recurrent Actor-Critic Learning Approach

Autores: J. Wang, J. Hu, G. Min, Q. Ni, T. El-Ghazawi
Publicado en: IEEE Transactions on Mobile Computing, Edición 22(11), 2023, Página(s) 6663-6675, ISSN 1536-1233
Editor: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tmc.2022.3197706

Multi-Task Federated Learning for Personalised Deep Neural Networks in Edge Computing

Autores: J. Mills, J. Hu, G. Min
Publicado en: IEEE Transactions on Parallel and Distributed Systems, Edición 33(3), 2022, Página(s) 630-641, ISSN 1045-9219
Editor: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tpds.2021.3098467

Federated Ensemble Model-based Reinforcement Learning in Edge Computing

Autores: J. Wang, J. Hu, J. Mills, G. Min, M. Xia, N. Georgalas
Publicado en: IEEE Transactions on Parallel and Distributed Systems, Edición 34(6), 2023, Página(s) 1848-1859, ISSN 1045-9219
Editor: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tpds.2023.3264480

Federated Learning for Distributed IIoT Intrusion Detection using Transfer Approaches

Autores: J. Zhang, C. Luo, M. Carpenter, G. Min
Publicado en: IEEE Transactions on Industrial Informatics, Edición 19(7), 2023, Página(s) 8159-8169, ISSN 1551-3203
Editor: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tii.2022.3216575

Simplifying YOLOv5 for deployment in a real crop monitoring setting

Autores: Emmanuel C. Nnadozie, Pablo Casaseca‑de‑la‑Higuera, Ogechukwu Iloanusi, Ozoemena Ani, Carlos Alberola‑López
Publicado en: Multimedia Tools and Applications, 2023, ISSN 1380-7501
Editor: Kluwer Academic Publishers
DOI: 10.1007/s11042-023-17435-x

Accelerating Federated Learning with a Global Biased Optimiser

Autores: J. Mills, J. Hu, G. Min, R. Jin, S. Zheng, J. Wang
Publicado en: IEEE Transactions on Computers, Edición 72(6), 2023, Página(s) 1804-1814, ISSN 0018-9340
Editor: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tc.2022.3212631

Client-Side Optimization Strategies for Communication-Efficient Federated Learning

Autores: J. Mills, J. Hu, G. Min
Publicado en: IEEE Communications Magazine, Edición 60(7), 2022, Página(s) 60-66, ISSN 0163-6804
Editor: Institute of Electrical and Electronics Engineers
DOI: 10.1109/mcom.005.210108

Insight into ADHD diagnosis with deep learning on Actimetry: Quantitative interpretation of occlusion maps in age and gender subgroups

Autores: Patricia Amado-Caballero, Pablo Casaseca-de-la-Higuera, Susana Alberola-López, Jesús María Andrés-de-Llano, José Antonio López-Villalobos, Carlos Alberola-López
Publicado en: Artificial Intelligence in Medicine, Edición 143, 2023, Página(s) 102630, ISSN 0933-3657
Editor: Elsevier BV
DOI: 10.1016/j.artmed.2023.102630

Deep Reinforcement Learning-Based Task Scheduling and Resource Allocation for Vehicular Edge Computing: A Survey

Autores: Peisong Li, Xinheng Wang, Changle Li, Muddesar Iqbal, Anwer Al-Dulaimi, Chih-Lin I, Pablo Casaseca-de-la-Higuera
Publicado en: IEEE Transactions on Intelligent Transportation Systems, 2025, Página(s) 1-30, ISSN 1524-9050
Editor: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tits.2025.3607910

Multiagent Reinforcement Learning-Based Multimodel Running Latency Optimization in Vehicular Edge Computing Paradigm

Autores: Peisong Li, Ziren Xiao, Xinheng Wang, Muddesar Iqbal, Pablo Casaseca-de-la-Higuera
Publicado en: IEEE Systems Journal, Edición 18, 2024, Página(s) 1860-1870, ISSN 1932-8184
Editor: Institute of Electrical and Electronics Engineers
DOI: 10.1109/jsyst.2024.3407213

Conference proceedings (2)

Optimization of a Deep-Learning-Based Cough Detector Using eXplainable Artificial Intelligence for Implementation on Mobile Devices

Autores: P. Amado-Caballero, I Varona-Peña, B. Gutiérrez-García, J. Aguiar-Pérez, M. Rodriguez-Cayetano, J. Gomez-Gil, J. Garmendia-Leiza, P. Casaseca-De-la-higuera
Publicado en: Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies, 2025, Página(s) 491-498
Editor: SCITEPRESS - Science and Technology Publications
DOI: 10.5220/0013141500003911

Online Active Learning For LSTM-Based Network Traffic Prediction

Autores: Pablo Casaseca-de-la-Higuera, Javier M. Aguiar, Patricia Amado-Caballero, Antonio J. Morgado, Joana da Silva Moreira, Chunbo Luo, Xinheng Wang
Publicado en: 2025 International Conference on Software, Knowledge, Information Management & Applications (SKIMA), 2025, Página(s) 1-5
Editor: IEEE
DOI: 10.1109/skima66621.2025.11155629