A fire detection scheme using 5G network-based KNN algorithm

As fire accidents cause large-scale human and material damage, it is necessary to have an active and active response system using information and communications technology. Recently, technologies are being researched using advanced information technology to efficiently respond to various fire situat...

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Bibliographic Details
Main Authors: Yoon, Mahnsuk, Lee, Changkyo, Lim, Gilhwan, Choi, Hyunchul, Cho, Kyucheol
Format: Conference Proceeding
Language:English
Subjects:
5G mobile communication
5G(5th Generation) Network
Deep learning
Detectors
Fire detection algorithm
Fires
Image recognition
Machine Learning
Machine learning algorithms
Multi Sensor
Shape
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Summary:As fire accidents cause large-scale human and material damage, it is necessary to have an active and active response system using information and communications technology. Recently, technologies are being researched using advanced information technology to efficiently respond to various fire situations. It analyzes the data and uses it to recognize the fire situation. However, most of the fire detection uses deep learning technology to detect the shape of a flame using image technology and respond to it. This is the situation. Therefore, in this paper, we apply the KNN(K Nearest Neighbors) machine learning algorithm technique for multi-sensor-based fire/non-fire classification and use 5G communication network technology for real-time response to increase the fire detection hit rate and propose a technology suitable for service supply in large-scale complexes.
ISSN:2162-1241
DOI:10.1109/ICTC55196.2022.9952851