Abstract: In response to the problems of low recognition rate and long system operation time in equipment detection management in the existing IoT information training room management system. A research has proposed an IoT information training room equipment detection management system on the ground of an improved YOLOV4 detection and recognition algorithm to solve the above problems. Firstly, it used the YOLOV algorithm to detect and identify equipment in the IoT information training room. Then, it used clustering methods to improve the YOLOV algorithm, thereby enhancing the detection accuracy and robustness of the algorithm, and thereby enhancing the performance of the equipment management system in the equipment management process of the training room. Finally, performance validation of the training room management system was conducted using datasets and simulation experiments. The results showed that the loss value of the training room equipment management system constructed using the improved YOLOv4 algorithm during the training process was 0.16. The accuracy and recall rates of device recognition were 95.71% and 92.83%, respectively. And the detection false alarm rate during the device detection and recognition process was only 2.15%, with a mAP value of 91.66%, and the detection and recognition indicators are higher than those of the comparison method. This indicates that the training room equipment management system constructed in the study has good adaptability in equipment detection and recognition in IoT information training rooms. The research aims to provide effective technical support for the management system of IoT training room equipment.

Huiling Hu. “The Management System of IoT Informatization Training Room Based on Improved YOLOV4 Detection and Recognition Algorithm”. International Journal of Advanced Computer Science and Applications (IJACSA) 15.2 (2024). http://dx.doi.org/10.14569/IJACSA.2024.0150299

@article{Hu2024,
title = {The Management System of IoT Informatization Training Room Based on Improved YOLOV4 Detection and Recognition Algorithm},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0150299},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0150299},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {2},
author = {Huiling Hu}
}