Fire Detection System using Deep Learning

Fire Detection System using Deep Learning

ASHWINI RENAKE1, PRANJALI SHINDE2, AND PAYAL KEDARE3, KARANDE PRITI4

GUIDE NAME- DR. H.B. JADHAV, ATC , AHMEDNAGR, 414005.

Adsul's Technical Campus Chas , Nimblak By Pass Road, Ahmednagar, Maharashtra 414005

Abstract

YOLO achieved modern performance in categorization of images and other computer vision applications. Including them in fire detection devices will significantly improve detection accuracy, decreasing fire incidents and their effects on the natural world and society as a whole The main problem with founded fire detection technologies is their deployment in actual monitoring networks because to have significant data and computing inference needs. The total number of fires reported each year has risen because of human actions and a dry climate. Several ways of detection have been thoroughly examined. However, because of the significant memory and computing demands for inference, using CNN-algorithm fire detection techniques in actual observation networks is extremely difficult. Establishing a classification in the suggested plan.

Keyword: - Fire detection, CNN, Deep learning,Yolov3 etc