With the rapid development and cross-integration of the Internet of Things (IoT) and  artificial intelligence (AI) technologies, IoT can integrate monitored entities, wireless communication,  AI, signal processing, intelligent power and intelligent operation and maintenance (O&M)，and health status assessment into an intelligent network system.  Therefore, advanced IoT, MIMO and AI technologies are widely used in the fields of unmanned platform, structure, power  system,  and  intelligent  medical,  such  as  IoT  network  protocols,  MIMO based wireless communication  security,  intelligent  signal processing  of terminal-cloud-edge  collaboration,  unknown   class  recognition  in  small  sample  scenarios,  AI  image  processing and intelligent medical system, and other applications.  This special session focuses on the methods and applications of IoT, MIMO and AI in semantic communication, signal processing of Image recognition, Health Diagnosis, etc,  shares  new  ideas  and  achievements,  and  discusses  the  current challenges and possible solutions in these fields with relevant experts, scholars, and engineers around the world.

This topic focuses on various wireless communication technologies and signal processing technologies related to IoT and artificial intelligence for industrial applications such as unmanned platforms, intelligent power, intelligent medical, intelligent fault diagnosis, etc. This topic not only focuses on the novelty of the relevant technical methods in these application areas, but also focuses on the practicability and value of the application of the relevant methods in the industrial field. Therefore, it is necessary to construct a special topic to provide a platform for scholars and engineers to explore theoretical methods and engineering applications in these specialized fields, and to promote the industrial application of advanced theoretical methods.

Related Topics for this Session:    

1. MIMO and AI Methods in Semantic Communication
2. Intelligent networking methods such as distributed resource allocation and routing
3. Intelligent anti-interference method based on deep learning for Adhoc network
4. Advanced Edge Computing Approaches for IoT
5. AI-based recognition method for unknown classes in small-sample scenes
6. Intelligent patrol of terminal-cloud-edge collaboration for UAV in the power system
7. Application of large models and AI agents in intelligent power grid 
8. Computer vision and 3D vision algorithms for UAVs and robotics in power system inspection
9. Application of advanced IoT and AI technology in smart power grid
10. Application of AI model in intelligent medical
11. Application of intelligent image recognition in power system, structural diagnosis, automatic driving, and intelligent medical

Important Dates:
Submission Deadline: June 25, 2026
Notification: July 15, 2026
Registration: July 30, 2026

Submit Method:
1, submit it via the link: http://www.easychair.org/conferences/?conf=icicsp2026 (after entering the link, click on the corresponding topic)
2, send your manuscript to icicsp@vip.163.com with subject "Submit+Special Session-6+Paper Title". (请通过邮件发送稿件，邮件题目：Submit+Special Session-6+Paper Title)

CHAIRMANS:

Haitao Xiao is an associate professor and doctoral supervisor at the School of Information and Communication Engineering, Xi 'an Jiaotong University, and a visiting researcher at Waseda University. He received the Ph.D. degree from Waseda University, Japan. He was selected into the "Overseas Talent Introduction Project of the International Exchange Program" of the Ministry of Social Security of China in 2018, and won the winning award of the "Source Creation Cup" Innovation and Creativity Competition of JKW in 2022. He is committed to the research of intelligent wireless communication and data computing fields such as smart antennas, intelligent mobile Ad hoc networks, intelligent reliable communications, satellite signal processing and positioning, intelligent fault diagnosis and damage diagnosis.

Yutian Wu received the B.E. degree in computer science and software engineering from Southeast University, China, in 2017, the M.E. and Ph.D. degree from Waseda University, Japan, in 2018 and 2022. She has published more than tens of academic papers in important academic journals and conference. Since 2023, she has been a lecturer at School of Automation and Electrical Engineering, University of Science and Technology Beijing, China. She has presided over the scientific research program supported by Youth Program of National Natural Science Foundation of China, and is mainly engaged in theory of deep learning, computer vision and application of 3D scene understanding in autonomous driving system.

Yingyi Yang is a senior engineer at China Southern Power Grid Technology Co., Ltd., where he is engaged in the research and development of intelligent systems and AI algorithms for robotics and UAVs. Received Ph.D. degrees in Computer Application Technology from South China University of Technology (SCUT), China. He is a member of the Institute of Electrical and Electronics Engineers (IEEE), and an executive committee member of the Technical Committee on 3D Vision (TC3DV) of the China Society of Image and Graphics (CSIG). His current research interests include computer vision, large models, AI agents and their applications in intelligent power grid inspection and operation.

Zhuyun Li is a senior engineer at China Southern Power Grid Technology Co., Ltd., where she is currently engaged in the research and development of visual and multimodal algorithms for UAV, robotics, and monitoring devices. Received the B.E. degree from Beijing Institute of Technology, China, and the M.E. and Ph.D. degrees from Waseda University, Japan.  She has published several papers in SCI and EI indexed journals and conferences, and holds more than ten patents in related fields. Her research interests include computer vision, multimodal large models, and their applications in intelligent power grid inspection and operation.

Harutoshi Ogai is a Professor of Information, Production, and Systems with Waseda University. He was born in Kitakyushu, Japan, and acquired the Ph.D. degree from Tokyo Institute of Technology. He was the director of the Automated Driving Joint Research Center of the Kitakyushu Industry-university-research Cooperation Association and Waseda University. His research interests include Process Control, Process Modeling and Simulation, Process Analysis and Data Mining, signal process, Automatic Control, and Bridge Diagnosis.

Qieshi Zhang is a Project Research Professor, Professor-level Senior Engineer, and Ph.D. Supervisor at the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences. His research focuses on embodied intelligent robots, brain-inspired intelligence, and human–robot interaction and collaboration. He has led or participated in more than 30 research projects, including National Key R&D Programs of China, National Natural Science Foundation of China, and international collaborative research projects etc. He has published over 160 papers, including more than 90 as first or corresponding author, and filed over 90 patents. His work has received several awards, including the Wu Wenjun Artificial Intelligence Science and Technology Award and the Shenzhen Science and Technology Award.

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