The convergence of Access Networks and Artificial Intelligence (AI) is redefining the intelligence boundary of the Internet. As data generation increasingly shifts to edge environments—homes, enterprises, factories, and cities—the access layer has emerged as a critical arena for deploying intelligent services that demand ultra-low latency, high contextual awareness, and privacy-preserving computation. Recent advances in Fiber-to-the-Room (FTTR), Wi-Fi 7, and multi-modal edge sensing have transformed access networks from passive conduits into active participants in AI-driven systems. At the same time, emerging AI technologies such as edge-optimized deep learning and LLM-based network agents are enabling new capabilities for real-time sensing, adaptive network control.
ANAI 2025 invites original research that explores these questions, aiming to bridge researchers and practitioners working at the intersection of AI, edge computing, wireless networking, and intelligent infrastructure. We seek high-quality submissions describing novel ideas, system designs, experimental studies, and real-world deployments in topics including, but not limited to:
1. Access Networks Enabling Intelligent Applications
- FTTR-based smart home, smart healthcare, and AIoT applications
- Wi-Fi sensing for activity recognition, presence detection, and human-computer interaction
- Low-latency access for AR/VR, cloud gaming, and real-time robotics
- On-device learning and inference in edge access environments
2. AI for Access Network Optimization
- Machine learning for network performance monitoring and adaptive configuration
- LLM-based agents for automated network control and self-healing
- AI-driven QoS management in multi-user, multi-service access environments
- Predictive maintenance for fiber and Wi-Fi hardware components
3. Joint Communication and Sensing
- Access networks as ambient sensors: gesture, vital signs, posture estimation
- Multi-modal fusion using Wi-Fi, LiDAR, mmWave, and camera signals
- AI techniques for distributed sensing and environment modeling
4. Deployment Experiences and Case Studies
- Large-scale deployments of FTTR, Wi-Fi 7, or multi-ONT systems with embedded AI
- Prototype systems demonstrating access-network-based inference
- Lessons learned from commercial or public deployments
Submission Requirements
Please submit via the submission website (https://anai2025.hotcrp.com/). The submission should be in the ACM conference proceedings format (https://www.acm.org/publications/proceedings-template).