ACOUSTIC EXTINGUISHING OF FLAMES DETECTED BY DEEP NEURAL NETWORKS IN EMBEDDED SYSTEMS release_7fvssuepz5acpf43jovzw6y7l4

by S. Ivanov, S. Stankov

Published in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences by Copernicus GmbH.

2021   Volume XLVI-4/W5-2021, p307-312

Abstract

Abstract. This paper presents the application of an intelligent flame and smoke detection platform based on artificial vision using Deep Neural Networks (DNN). An acoustic fire extinguisher can be connected to such a platform. In light of recent research, the use of acoustic technology is an environmentally friendly way of extinguishing flames. One of the advantages is then extinguishing immediately after positive detection of flames or smoke (without unnecessary time delay), which is a new combination in the field of fire protection. The authors contribution is the presentation of the conception of the intelligent acoustic extinguisher and the research work made to accomplish that including algorithms and tests. The main objective of the paper is to present the possibilities of acoustic extinguishing and fire detection using selected deep neural network models in embedded systems.
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