Cloud-based Speech Recognition for UAV Control Architecture in Industry 4.0

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.