Construction and Optimization of Multi-Scenario Autonomous Call Rule Models in Emergency Command Scenarios

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 innovativ...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:International journal of advanced computer science & applications Ročník 15; číslo 12
Hlavní autoři: Zheng, Weiyan, Zhu, Chaoyue, Huang, Di, Zhou, Bin, Yan, Xingping, Chen, Panxia
Médium: Journal Article
Jazyk:angličtina
Vydáno: West Yorkshire Science and Information (SAI) Organization Limited 2024
Témata:
ISSN:2158-107X, 2156-5570
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí: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.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2158-107X
2156-5570
DOI:10.14569/IJACSA.2024.0151229