Bridging Integrated Sensing, Edge Intelligence, and Sustainable Communication for Intelligent Ecosystems.

• Special Session Organizers

+ Assoc. Prof. Kien Nguyen, Chiba University, Japan

+ Assoc. Prof. Minh Thuy Le, Hanoi University of Science and Technology, Vietnam

+ Dr. Hanh Nguyen Thi, Phenikaa University, Vietnam

• Objectives and topics

The evolution toward AI-native and future wireless systems is rapidly expanding beyond high-throughput data communication to include high-precision, real-time environmental and visual perception. Integrated Sensing and Communication (ISAC) and Networked Computer Vision have emerged as cornerstone technologies to achieve this vision.

However, a critical research gap persists: most current work treats sensing (RF or Visual), communication, and AI-driven computation as separate, sequential tasks. This creates a fundamental bottleneck, preventing the network from achieving true real-time, perception-aware behavior.

This Special Session, SPACS, aims to bridge this gap. We solicit novel, high-impact research on the fundamental fusion of ISAC, Computer Vision, Edge-AI, and Sustainable Communication. We seek contributions that explore how the network itself can not only transmit data but simultaneously perceive, reason, and act upon its physical environment to create truly Intelligent Ecosystems.

The session focuses on hardware-algorithm co-design, AI-native architectures, and advanced optimization protocols. It aims to pave the way for next-generation applications, ranging from cooperative autonomous systems and immersive digital twins to resilient, self-healing sensor networks.

• Scope and Topics

The scope of this special session covers, but is not limited to, the following topics:

1. Integrated Sensing, Communication, and Computation (ISAC)

• ISAC-based architectures for simultaneous information transmission and environment sensing.
• Multi-Modal Sensor Fusion: Integrating RF sensing (Radar/Wi-Fi) with Computer Vision (RGB/Depth/LiDAR) for robust environment mapping.
• Joint waveform design and resource optimization for sensing-communication fusion.
• Radar–communication coexistence and cooperative perception for autonomous systems.

2. AI, Computer Vision, and Edge Intelligence

• Networked Computer Vision: Distributed inference, split-computing, and collaborative video analytics over wireless edges.
• Semantic Communication: AI-driven image/video compression and semantic-aware transmission for bandwidth-constrained networks.
• TinyML for on-device intelligence, ultra-low-power AI processing, and vision-on-chip solutions.
• Federated and edge learning for distributed and privacy-preserving visual perception.

3. Sustainable and Green Communication Technologies

• Green ICT and eco-efficient network design: renewable-powered base stations, energy harvesting, and backscatter communications.
• AI-aided resource allocation and deep reinforcement learning for dynamic spectrum management.
• Energy-aware protocols for massive IoT and industrial automation.
• Green optimization for sustainable Wireless Sensor Networks (WSNs).

4. Resilient Network Management and Fault Optimization

• Advanced Fault Detection: AI-native optimization frameworks to improve fault detection and monitoring in WSNs and IoT.
• Dynamic Monitoring: Monitoring performance for dynamic objects under complex and changing environments.
• Predictive Maintenance: AI-driven self-optimization and reliability enhancement for ICT infrastructures.
• Security and Trust: Blockchain and decentralized approaches for secure network management.

5. Smart Applications for Intelligent Ecosystems

• Robotics and Autonomy: Vision-based navigation, SLAM (Simultaneous Localization and Mapping), and human–robot collaboration.
• Smart Cities & Surveillance: Intelligent video surveillance, anomaly detection, and adaptive traffic management using visual sensors.
• Beyond 5G Applications: Immersive XR/VR, holography, and digital twins supported by perception-aware networks.
• Smart Healthcare: Systems leveraging AI-assisted monitoring and non-contact visual sensing for patient care.

• Session Program Committee

Prof. Tuan Anh Le, Middlesex University, UK

Assoc. Prof. Zhi Liu, The University of Electro-Communications (UEC), Japan

Assoc. Prof. Quoc Cuong Nguyen, Hanoi University of Science and Technology, Vietnam

Assoc. Prof. Thanh Long Cung, Hanoi University of Science and Technology, Vietnam

Prof. Tuan Phung-Duc, Institute of Systems and Information Engineering, University of Tsukuba, Japan;

Assoc. Prof. Hoang Le, The University of Aizu, Japan

Dr. Hai-Trieu Phan, Research Director, Senior Expert, Alternative Energies and Atomic Energy Commission (CEA), France

Dr. Quang Trung Luu, CentraleSupélec, Université Paris-Saclay, France

Prof. Tan-Phu Vuong, Grenoble INP, France

Dr. Nam Khanh Nguyen, National Institute of Information and Communications Technology, Japan

Dr. Xuan Tung Nguyen, Phenikaa University, Vietnam

Dr. Thanh Duc Ngo, University of Information Technology, Vietnam National University Ho Chi Minh City, Vietnam

Dr. Dai Duong Nguyen, Hanoi University of Science and Technology, Vietnam 

Dr. Thi Anh Xuan Tran, Hanoi University of Science and Technology, Vietnam

Dr. Hoang Hiep Ly, Hanoi University of Science and Technology, Vietnam

Dr. Thanh Huy Nguyen, Van Lang University, Vietnam

Assist. Prof. Van-Linh Nguyen,  National Chung Cheng University, Taiwan

• Contact:

+ Assoc. Prof. Kien Nguyen, Chiba University, Japan, nguyen@chiba-u.jp

+ Assoc. Prof. Minh Thuy Le, Hanoi University of Science and Technology, Vietnam, thuy.leminh@hust.edu.vn

+ Dr. Hanh Nguyen Thi, Phenikaa University, Vietnam, hanh.nguyenthi@phenikaa-uni.edu.vn