W15 – Intelligent Synergy of Sensing and Communications for Green IoT

Co-organizer: Chen Dai, Nanjing University of Posts and Telecommunications, China
Co-organizer: Miao Liu, Nanjing University of Posts and Telecommunications, China
Co-organizer: Kun Zhu, Nanjing University of Aeronautics and Astronautics, China
Co-organizer: Bintao Hu, Xi’an Jiaotong-Liverpool University, China
Co-organizer: Yiping Zuo, , Nanjing University of Posts and Telecommunications, China

Abstract: In the era of large-scale IoT deployment and growing environmental awareness, Green IoT has become a cornerstone for sustainable digital transformation. Intelligent synergy between sensing and communications is essential to achieving low-carbon, energy-efficient, and adaptive IoT systems. As IoT expands into smart cities, precision agriculture, and industrial automation, harmonizing data perception (sensing) and transmission (communications) is increasingly critical. Key challenges include balancing sensing accuracy with ultra-low-power connectivity (e.g., Wi-Fi HaLow, NB-IoT, 6G NTN), ensuring interoperability across heterogeneous devices, optimizing data–energy trade-offs, and reducing lifecycle waste through modular and reconfigurable designs. Advances in semantic communications, edge intelligence, and AI-native integrated sensing and communication (ISAC) architectures are reshaping the landscape of sustainable IoT.

This workshop aims to explore next-generation frameworks that integrate sensing and communications for Green IoT. It emphasizes emerging technologies such as federated learning, reconfigurable intelligent surfaces (RIS), and energy-harvesting-enabled zero-energy IoT devices to enhance efficiency and sustainability.

Co-organizer’s Bios:

Chen Dai:

Chen Dai received the Ph.D. degree in 2022 from the College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, China. From March 2021 to March 2022, he was a Visiting Scholar with the University of Manitoba, Canada. He is currently an Assistant Professor with the School of Computer Science, Nanjing University of Posts and Telecommunications, China. He was the recipient of the 2024 Jiangsu Excellent Doctoral Dissertation Award. He has served as the TPC member of multiple IEEE conferences. His research interests include resource management, integrated sensing and communication, and applied game theory and machine learning for wireless networks.

Miao Liu:

Miao Liu, (Senior member, IEEE) received the Ph.D. degree in communication engineering from Southeast University, Nanjing, China in 2019. He is an assistant professor with Nanjing University of Posts and Telecommunications, Nanjing, China. He served as track chairs for multiple IEEE conferences like VTC and ICCC. His research interests include deep learning, cognitive radio networks, heterogeneous IoT, and resource allocation in B5G/6G communications.

Kun Zhu:

Kun Zhu (Member, IEEE) is currently a Professor in the College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, and the Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing, China. He is also a Jiangsu specially appointed professor. He received his Ph.D. degree in 2012 from School of Computer Engineering, Nanyang Technological University, Singapore. His research interests include resource allocation in 5G, wireless virtualization, and self-organizing networks. He has published more than fifty technical papers and has served as TPC for several conferences. He won several research awards including the IEEE WCNC 2019 Best Paper Award, ACM China rising star chapter award.

Bintao Hu:

Bintao Hu (Member, IEEE) is an Assistant Professor at the School of Internet of Things, Xi’an Jiaotong-Liverpool University, Suzhou, China. He received his B.Eng. degree in Telecommunications engineering from Xiangtan University, Xiangtan, China, in 2015, M.Sc. degree in Data Communications in 2017 and Ph.D. degree in Electronic and Electrical Engineering in 2022, both from the University of Sheffield, UK. He attended the European Commission Decade project with Ranplan, Barcelona, Spain, in 2018. He received the best paper award in EAI 2025, ECNCT 2025, IEEE CIoTSC 2025, the best oral presentation award in IEEE/ACIS ICIS 2023, the Outstanding Young Investigator Award in IEEE CCAI 2025, and the best workshop organisation award in SMC-IoT 2023. He served as a Chair/Co-Chair of many international workshops such as IEEE WCNC 2026, IEEE VTC 2024-2025, IEEE ICCCN 2024-2025, IEEE RFIT 2024, etc. He served as a TPC for many conferences such as IEEE VTC 2023-2025, IEEE WCNC 2023-2026, IEEE PIMRC 2024-2026, etc. He also served as a reviewer for many journals, such as IEEE TMC, IEEE TNSM, IEEE TCC, IEEE TNSE, IEEE IoTJ, etc. His current research interests include UAV communications, MEC, ISAC, digital twins, AI for wireless, etc.

Yiping Zuo:

Yiping Zuo (Member, IEEE) received the B.S. degree in electronic information science and technology from Huaiyin Normal University, Huaian, China, in 2015, the M.S. degree in communication and information systems from the Nanjing University of Posts and Telecommunications, Nanjing, China, in 2018, and the Ph.D. degree in information and communications engineering from Southeast University, Nanjing, China, in 2022. She is currently with the faculty of the School of Computer Science, Nanjing University of Posts and Telecommunications. Her current research interests include blockchain, wireless sensing, and integrated sensing and communication.

Workshop Call For Papers: CPF-VTC2026-Spring-WS-ISACIOT-1

 

Paper submission deadline Extended: 8 February 2026
Acceptance notification: 18 March 2026
Final paper submission deadline Extended: 7 April 2026

Submission requirements: 5-page paper (without overlength charge) and up to 2 additional pages are allowed with the purchase of additional page charges in the amount of $100 USD per additional page at the time of registration and final paper submission.

Paper submission can be located here: https://vtc2026s-rr-wks.trackchair.com/