Advertisement
Published in:
2021 | OriginalPaper | Chapter
An Efficient Fire Detection System Using Support Vector Machine and Deep Neural Network
Authors : Archana Venugopal, Febi Justin, Linju Santhosh, Riya Binny, NG Resmi
Published in: Smart Technologies for Sustainable Development
Publisher: Springer Singapore
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Abstract
Fire is a dangerous disaster. Uncontrollable fire can cause massive destruction to life and property. Hence fire detection and alarming is a crucial and ever-demanded topic. A fire alarm must be functionally capable and reliable. This paper mainly focuses on a real-time system for fire detection. Videos acquired from CCTVs or webcams are converted to a sequence of images which are then fed to the classifier. Upon detecting fire from the images extracted, an alert is sent to the authorities concerned. Support vector machine (SVM) and deep neural network are used to develop the proposed fire detection system. Both the algorithms are employed to build classification models. Their performances are then compared and the model which gives better accuracy is selected.