Research and application of residual network model based on artificial intelligence for smoke detection

Abstract

Abstract: The traditional fire detection system used on portable devices consumes a lot of memory, is vulnerable to the environment, and the accuracy needs to be improved. We propose a fire detection system with a small memory footprint and excellent performance. Using the FireNet neural network we designed to embed in portable hardware products, we tested it on a public data set. Compared with other traditional methods, the test results have significantly improved the accuracy and speed.

Key words: fire Protection, neural networks, embedded systems, smoke detection

CHEN Zhao-hui, CHEN Zhi-yu. Research and application of residual network model based on artificial intelligence for smoke detection[J]. Fire Science and Technology, 2020, 39(12): 1747-1750.

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Research and application of residual network model based on artificial intelligence for smoke detection

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