AIEC 2025 - Artificial Intelligence & Edge Computing
In conjunction with
The 12th International Conference on Global Congress on Emerging Technologies


Artificial Intelligence (AI) has evolved from a niche domain into a powerful enabler of next‑generation software futures. Today, generative AI and Large Language Models (LLMs)—such as ChatGPT, Claude, Gemini, and Llama—are spearheading breakthroughs across industries, enabling content creation, code generation, and multimodal services at scale. Over the past year, a lot of organizations have adopted AI in at least one business function, and private investment in GenAI has surged. This wave of innovation opens doors for AI‑powered tools in translation, medical imaging, conversational agents, autonomous systems, and more—making AI not just a research topic but a foundational technology for modern digital transformation.

Complementing these leaps, Edge Computing remains essential for deploying AI where latency, data privacy, and real‑time responsiveness matter most. Edge platforms reduce dependence on distant data centers, enabling real‑time analytics in IoT, smart cities, healthcare, manufacturing, and logistics. The rise of 5G and edge infrastructure further blurs the line between cloud and device, extending AI’s reach into mobile and embedded systems. When combined with lightweight LLMs and on-device AI inference, edge‑based generative models and agentic assistants can deliver sophisticated, secure, and context-aware services without compromising speed or privacy.

The Workshop on AI, Edge and Computing (WAIEC), now in its third edition (2020, 2021, and 2025), organized in conjunction of IOTSMS 2025 Internet of Things: Systems, Management and Security, will bring together academia and industry leaders to explore the synergy between AI, edge/IoT, and agent‑driven architectures. We seek contributions at the intersection of AI/LLMs, generative and multimodal systems, edge‑native deployment, and secure, intelligent IoT frameworks. Emphasis areas include LLM‑powered agent systems, multi‑agent orchestration, AI‑enabled edge platforms, real‑time IoT security, and AI‑driven sensing and automation. Our aim is to foster the exchange of research insights, identify emerging challenges, and chart the path for integrating generative AI and agentic technologies into scalable, secure IoT/edge ecosystems.

Topics

The Workshop on Artificial Intelligence & Edge Computing (AIEC) calls for contributions that address fundamental research and solutions issues in Artificial Intelligence and Edge Computing including but not limited to the following :

Big Data mining at the Edge (e.g., federated analytics, synthetic data generation for training, privacy-preserving data pipelines)

Machine Learning at the Edge (including TinyML, on-device LLM inference, edge-model compression & pruning for resource efficiency

Architectures of Edge AI for IoT (edge–cloud collaboration, 6G-driven metaverse devices, neuromorphic and quantum-assisted edge systems)

Security on the Edge (adversarial robustness, differential privacy, secure multi-party LLMs, zero-trust agentic architectures)

Graph Databases on the Edge (knowledge-graph integration for local reasoning, LLM-aided graph query and inference)

Resource-friendly Edge AI Model Design (federated learning, neural architecture search, energy-efficient generative models)

Resource Management for Edge AI (AI-driven orchestration, dynamic resource allocation, AI optimization for edge deployment)

Applications/services for Edge AI (on-device generative assistants, real-time multimodal IoT systems, smart aquaculture, healthcare & environmental monitoring)

Communication and Networking Protocols for Edge AI (6G-enabled architectures, decentralized networking, real-time streaming for agent systems)

Software Platforms for Edge (autoML toolchains, LLM‑aided design platforms, secure composable agent frameworks)

Generative AI at the Edge (on-device generative models, LLM-aided data augmentation and code generation toolkits)

LLM‑Aided Design & Agentic Systems (co‑design with hardware, software, IoT sensors using LLM agents for EDA, cyber‑physical integration)

Living Intelligence & Bio‑Sensor Fusion (convergence of AI, biotech, advanced sensing into adaptive edge systems)

Sustainability and Green Edge AI (energy-aware model design, renewable-powered edge data centers, lifecycle carbon impact mitigation)