• Tanay Zope
• Saba Syed
• Shrikant Dandge
• Gunjan Sharma
• Mansi Phadatare

In this paper, we propose a deep CNN-based fire detection system that can accurately and efficiently detect fires in real-time. After detecting fire it goes one step further by trying to detect the presence of any fire extinguishers at one of the connected devices so that we not only quickly detect fire but also quickly control it. Our fire detection model uses a deep convolutional neural network with multiple layers of convolution and pooling to extract features from the input images. [We evaluate the performance of our system on a publicly available dataset of fire and non-fire images and achieve a high accuracy of over 98%.] Our proposed system has the potential to be used in various applications, such as fire monitoring in buildings, and can greatly improve the efficiency and effectiveness of fire detection and prevention

Convolutional neural networks (CNNs), Deep Learning, Fire Detection, Image Classification.

"Fire Detection Using Image Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.o357-o364, May-2023, Available :http://www.jetir.org/papers/JETIR2305F46.pdf

"Fire Detection Using Image Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppo357-o364, May-2023, Available at : http://www.jetir.org/papers/JETIR2305F46.pdf