TY - GEN
T1 - Cloud-based Speech Recognition for UAV Control Architecture in Industry 4.0
AU - Eruero, Oghenegueke P.
AU - Okwu, Modestus O.
AU - Eric, Favour O.
AU - Tartibu, Lagouge K.
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Unmanned Aerial Vehicles (UA Vs) have emerged as indispensable assets globally. The classical control mechanisms rely heavily on tactile inputs and semi-Autonomous navigation. However, the advent of Industry 4.0 and the impending Industry 5.0 has necessitated the growing demand for intuitive and effective control mechanisms to enable efficient operations and foster human-machine collaboration. This study is focused on the exposition of a novel approach to UA V control architecture by integrating a cloud-based speech recognition algorithm into UA V technology within the CoppeliaSim platform. The system demonstrates proficient English language comprehension, mapping spoken English commands to predefined sets of commands corresponding to specific UA V operations, and executing the corresponding operations seamlessly. This study underscores the potential of cloud-based speech recognition as an intuitive UA V control mechanism, paving the way for further research and development in this domain.
AB - Unmanned Aerial Vehicles (UA Vs) have emerged as indispensable assets globally. The classical control mechanisms rely heavily on tactile inputs and semi-Autonomous navigation. However, the advent of Industry 4.0 and the impending Industry 5.0 has necessitated the growing demand for intuitive and effective control mechanisms to enable efficient operations and foster human-machine collaboration. This study is focused on the exposition of a novel approach to UA V control architecture by integrating a cloud-based speech recognition algorithm into UA V technology within the CoppeliaSim platform. The system demonstrates proficient English language comprehension, mapping spoken English commands to predefined sets of commands corresponding to specific UA V operations, and executing the corresponding operations seamlessly. This study underscores the potential of cloud-based speech recognition as an intuitive UA V control mechanism, paving the way for further research and development in this domain.
KW - Automatic speech recognition
KW - Cloud-based voice control
KW - CoppeliaSim
KW - UA V control architecture
UR - http://www.scopus.com/inward/record.url?scp=85203791374&partnerID=8YFLogxK
U2 - 10.1109/icABCD62167.2024.10645268
DO - 10.1109/icABCD62167.2024.10645268
M3 - Conference contribution
AN - SCOPUS:85203791374
T3 - 7th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2024 - Proceedings
BT - 7th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2024 - Proceedings
A2 - Pudaruth, Sameerchand
A2 - Singh, Upasana
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2024
Y2 - 1 August 2024 through 2 August 2024
ER -