Consumer Personalized Gesture Recognition in UAV-Based Industry 5.0 Applications

In the era of Industry 5.0, technology promises the rapid and smart growth of industries to improve the system performance substantially and be sustainable and more secure. Industry 5.0 enabled the conventional unmanned aerial vehicle (UAV) industries to represent a dynamic result that can offer various services irrespective of time, place, and in broader physical range. Hence, satellite systems of high performance having advanced pre-processing transmission capabilities are gaining considerable attention to increase overall system throughput. In enhancing the efficiency of interaction between humans and machines, gesture recognition in UAV-based industry 5.0 can perform a vital role as the transmission medium in end-user based applications with low latency periods. However, few smart consumer personalized gesture recognition (CPGR) systems are insufficient in the privacy preservation in UAV-based industry 5.0 applications. Also, privacy-preserving is time-consuming, especially for model training and real-time CPGR. Although wireless technologies with big-data schemes provide such applications but lack emotional attachments. This article proposes a gesture-aware system with pre-processing connected systems using a powerful emotion detection system by incorporating a conventional analysis-modification-synthesis framework used for industry 5.0 applications. This study demonstrates the effectiveness of different noise estimation techniques on the proposed Modulation domain Recognition (MDSR) approach for UAV-based Industry 5.0.