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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 15 Issue 12, 2024.
Abstract: In response to the slow processing speed, weak anti-interference, and low accuracy of autonomous call models in current emergency command scenarios, the research focuses on the fire scenario, aiming to improve the emergency response efficiency through technological innovation. The research innovatively integrates digital signal processing algorithm and two-tone multi-frequency signal detection algorithm to develop a hybrid algorithm. Then, a novel autonomous call model based on the hybrid algorithm is constructed. The comparative experimental results indicated that the accuracy of the hybrid algorithm was 0.9 and the error rate was 0.05, which was better than other comparison models. The average accuracy and comprehensive performance score of the model were 0.95 and 97 points, respectively, both of which were better than comparison models. The results confirm that the autonomous call model proposed in this study can accurately and quickly judge emergency scenarios and handle calls, and provide new ideas and theoretical basis for emergency command and rescue of fire and other disasters, with broad application prospects.
Weiyan Zheng, Chaoyue Zhu, Di Huang, Bin Zhou, Xingping Yan and Panxia Chen, “Construction and Optimization of Multi-Scenario Autonomous Call Rule Models in Emergency Command Scenarios” International Journal of Advanced Computer Science and Applications(IJACSA), 15(12), 2024. http://dx.doi.org/10.14569/IJACSA.2024.0151229
@article{Zheng2024,
title = {Construction and Optimization of Multi-Scenario Autonomous Call Rule Models in Emergency Command Scenarios},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0151229},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0151229},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {12},
author = {Weiyan Zheng and Chaoyue Zhu and Di Huang and Bin Zhou and Xingping Yan and Panxia Chen}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.