[Apologies if you got multiple copies of this invitation] *The International workshop on Artificial Neural Networks for Edge Intelligence (ANNEI 2024)* Co-located with The 9th International Conference on Fog and Mobile Edge Computing (FMEC 2024) https://emergingtechnet.org/FMEC2024/Workshops/ANNEI2024/index.html Malmö, Sweden. September 2-5, 2024 Technically Co-Sponsored by IEEE Sweden Section *ANNEI 2024 CFP:* 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 reduce 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. *Submissions Guidelines and Proceedings* Manuscripts should be prepared in 10-point font using the IEEE 8.5" x 11" two-column format. All papers should be in PDF format, and submitted electronically at Paper Submission Link. A full paper can be up to 8 pages (including all figures, tables and references). Submitted papers must present original unpublished research that is not currently under review for any other conference or journal. Papers not following these guidelines may be rejected without review. Also submissions received after the due date, exceeding length limit, or not appropriately structured may also not be considered. Authors may contact the Program Chair for further information or clarification. All submissions are peer-reviewed by at least three reviewers. Accepted papers will appear in the FMEC Proceeding, and be published by the IEEE Computer Society Conference Publishing Services and be submitted to IEEE Xplore for inclusion. Submitted papers must include original work, and must not be under consideration for another conference or journal. Submission of regular papers up to 8 pages and must follow the IEEE paper format. Please include up to 7 keywords, complete postal and email address, and fax and phone numbers of the corresponding author. Authors of accepted papers are expected to present their work at the conference. Submitted papers that are deemed of good quality but that could not be accepted as regular papers will be accepted as short papers. Length of short papers can be between 4 to 6 pages. *Important Dates:* Submission Due: June 30th, 2024 Notification: July 30th, 2024 Camera-ready submission: August 10th, 2024 *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 *Contact:* Please send any inquiry to : Lucia Cavallaro <lucia.cavallaro@ru.nl> Liotta Antonio <Antonio.Liotta@unibz.it> Yaqub Muhammad Azfar <MuhammadAzfar.Yaqub@unibz.it>