Abstract
This paper presents a novel approach in enhancing Unmanned Aerial Vehicle (UAV) communication systems through the application of reliable Electroencephalogram (EEG)-based Motor Imagery signals. The concept of EEG signals and the active role that Motor Imagery (MI) signals can play in UAV systems is explored, along with the efficiency aspects and algorithmic superiority of the communication system, demonstrating how the EEG information signal is reliable enough to be utilized in a UAV communication system. The results provide a performance evaluation of the CNN model along with a comparison to other learning models, and an analysis of the spatial separation in the brain. The study concludes by suggesting the implications of the findings for UAV communication and AI in future researches.
Original language | English |
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Title of host publication | ICTC 2023 - 14th International Conference on Information and Communication Technology Convergence |
Subtitle of host publication | Exploring the Frontiers of ICT Innovation |
Publisher | IEEE Computer Society |
Pages | 415-418 |
Number of pages | 4 |
ISBN (Electronic) | 9798350313277 |
DOIs | |
Publication status | Published - 2023 |
Event | 14th International Conference on Information and Communication Technology Convergence, ICTC 2023 - Jeju Island, Korea, Republic of Duration: 2023 Oct 11 → 2023 Oct 13 |
Publication series
Name | International Conference on ICT Convergence |
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ISSN (Print) | 2162-1233 |
ISSN (Electronic) | 2162-1241 |
Conference
Conference | 14th International Conference on Information and Communication Technology Convergence, ICTC 2023 |
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Country/Territory | Korea, Republic of |
City | Jeju Island |
Period | 23/10/11 → 23/10/13 |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
ASJC Scopus subject areas
- Information Systems
- Computer Networks and Communications