• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.346-348
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• 2022

A monitoring system was constructed to identify the cause of occurrence based on data on the analysis of the ignition factors of fermentation heat generated from loading waste. Universal Middleware was used to provide a real-time run-time environment for the configuration and speed of scenarios for each type of fire early warning. It is necessary to dynamically recognize the loading height and pressure of the loading waste, the drying of wood, batteries, and plastic waste, which are representative compositional wastes, and the carbonization changes on the surface. Therefore, this IoT situation recognition platform for analyzing low-temperature-fired fire possibility data was dynamically configured and presented.