KEYWORDS: Analytical research, Statistical analysis, Visualization, Reflection, Visible light communication, Databases, Signal processing, Internet of things, Infrared technology, Communication and information technologies
Multiple studies about the indoor positioning technologies have been reported. However, literature involving scientometric analysis of indoor positioning technologies is sparse. Here, we use scientometric analysis and a historical review to highlight recent research on indoor positioning technologies. We use the former to examine research on indoor positioning technologies from 2002 to 2022. The latter is used to identify the most frequent keywords in keyword analysis, as well as explore hotspots and indoor position technology trends. Scientometrics analyzed the mainstream positioning technology, changes in research topics, and major research trends, and found that there were 2739 research papers on indoor positioning technology, a 4-fold increase over the last 20 years. These findings offer a vigorous roadmap for further studies in this field.
Human pose estimation is attracting increasing attention from researchers as a fundamental technology for human action recognition, while edge computing applications pose higher challenges. In this paper, we propose an optimization human pose estimation method for edge computing applications. This method uses YOLOv4 to improve the accuracy of AlphaPose at the object detection stage and accelerates human target detection and pose skeleton node inference by optimizing both the object detection model and the pose estimation model. Moreover, the proposed scheme is transplanted onto an embedded development board and compared with current mainstream human pose estimation algorithms. Experimental results show that the proposed algorithm achieves better detection frame rate and accuracy than the compared algorithms on the embedded platform. The algorithm has high real-time performance and accuracy and provides a basis for lightweight human action recognition scheme in edge applications.
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