Prof. Lu Bai
Institute Shandong University Date & Time Date: 5 Nov. 2024 Time: 13:30-14:20 Zoom ID: 987 5125 6055 Passcode: 123456
With the wide popularization of low-altitude economy, low-altitude intelligent transportation has received extensive attention. In low-altitude intelligent transportation, multiple intelligent networked unmanned aerial vehicles (UAVs) and autonomous vehicles are simultaneously deployed with communication devices and multi-modal sensors. In this case, the communication capability and sensing capability coexist symbiotically, which brings more opportunities for the development of intelligent networked low-altitude transportation.
In this talk, inspired by human synesthesia, we proposes a novel concept, named Synesthesia of Machines (SoM). SoM refers to intelligent multi-modal sensing-communication integration. As the key cornerstone of modeling the SoM mechanism, i.e., mapping relationship between sensing and communications, a new mixed multi-modal (MMM) sensing-communication dataset, named M3SC, is constructed. Based on the constructed dataset, we give the recent advance in the multi-modal sensing-communication integrated channel modeling for intelligent networked low-altitude transportation and further presents the contributions and innovations therein. Finally, conclusions and future work related to the multi-modal sensing aided 6G wireless communication intelligent channel modeling are given.
Dr. Lu Bai is currently a professor at the Joint SDU-NTU Centre for Artificial Intelligence Research (C-FAIR), Shandong University. Her general research interests are in areas of wireless communications and artificial intelligence, subject on which she has published more than 40 journal and conference papers, 2 books, and holds 5 patents. She has received IEEE VR Best Paper Award and TaiShan Scholar Award. She has served as the member of the Technical Program Committee and session chair for several international conferences. She is currently an Associate Editor of IET Communications and a member of IEEE P1944 Standard Group.
来源：智能交通学域
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