Welcome to the International workshop on Artificial Neural Networks for Edge Intelligence (ANNEI 2024)! The workshop will discuss artificial intelligence (AI) optimization and its implementation in edge computing and Internet of Things (IoT) environments, with a focus on federated learning, artificial neural networks, and sparse neural networks. Federated Learning investigates a cooperative method that protects data privacy while allowing AI models to be trained over dispersed edge devices. Sparse ANNs are a viable option that can be deployed in edge computing/IoT scenarios since they address scalability issues and reduces energy usage. Sparsity approaches also allow the topology of ANNs to be smaller and more scalable, which makes them appropriate for deployment in resource-constrained situations like edge computing and IoT devices. Multidisciplinary research that combines edge computing with other emerging technologies, such as blockchain, artificial intelligence, cybersecurity technologies, etc., is highly welcomed. The potential topics include, but are not limited to:

Federated Learning: Privacy-Preserving Collaborative AI Training on Edge Devices.
Sparse Neural Networks: Principles, Advantages, and Applications in Edge Computing and IoT.
Optimization Techniques for AI Models in Resource-Constrained Environments.
Scalability Challenges and Solutions in Edge Computing and IoT Deployments.
Energy-Efficient Computing Strategies for Edge Devices and IoT Systems.
Exploring the Interplay between Federated Learning and Edge Computing Technologies.
Security and Privacy Considerations in Federated Learning and Edge AI Systems.
Real-world Case Studies of Federated Learning and Sparse Neural Networks in Edge Computing.
Integration of Edge Computing with Blockchain Technology for Secure and De-centralized AI Applications.
Advances in Cyber-security Technologies for Securing Edge Computing/IoT Environments.
Hardware Acceleration and Edge Computing Architectures for Efficient AI Inference.
Federated Learning for Healthcare Applications: Challenges and Opportunities.
Exploring Edge Computing and AI Integration in Smart Cities and Urban Infrastructure.
Future Directions and Emerging Trends in Edge Computing and IoT Integration with AI Technologies.

Organization Committee

Dr. Lucia Cavallaro, Radboud University, The Netherlands
Dr. Muhammad Azfar Yaqub, Free University of Bozen-Bolzano, Italy
Dr. Antonio Liotta, Free University of Bozen-Bolzano, Italy

KEYNOTE SPEAKERS

For Keynote Speakers information, please visit https://emergingtechnet.org/FMEC2024/keynote-speakers.php

Authors Submission Guidelines:

Submission Site:

https://easychair.org/conferences/?conf=fmec2024

Paper format

Submitted papers (.pdf format) must use the A4 IEEE Manuscript Templates for Conference Proceedings. Please remember to add Keywords to your submission.

Length

Submitted papers may be 6 to 8 pages. Up to two additional pages may be added for references. The reference pages must only contain references. Overlength papers will be rejected without review.

Originality

Papers submitted to DTL must be the original work of the authors. The may not be simultaneously under review elsewhere. Publications that have been peer-reviewed and have appeared at other conferences or workshops may not be submitted to DTL. Authors should be aware that IEEE has a strict policy with regard to plagiarism https://www.ieee.org/publications/rights/plagiarism/plagiarism-faq.html The authors' prior work must be cited appropriately.

Author list

Please ensure that you submit your papers with the full and final list of authors in the correct order. The author list registered for each submission is not allowed to be changed in any way after the paper submission deadline.

Proofreading:

Please proofread your submission carefully. It is essential that the language use in the paper is clear and correct so that it is easily understandable. (Either US English or UK English spelling conventions are acceptable.)

Publication:

All accepted papers in FMEC2024 and the workshops colocated with it will be submitted to IEEEXplore for possible publication.

Program

The program will be announced with the FMEC2024 program at https://emergingtechnet.org/FMEC2024/final-program.php

Venue

For venue and acomodoation information, please visit https://emergingtechnet.org/FMEC2024/accommodation.php

Registration

For registration information, please visit https://emergingtechnet.org/FMEC2024/CameraReady.php

Camera Ready

For registration information, please visit https://emergingtechnet.org/FMEC2024/CameraReady.php