A Robust and Dynamic Fire Detection Algorithm using Convolutional Neural Network 
K.Sivasankari1, Shubham Singh2, Kanhaiya Kumar3, Aman Dubey4
1Mrs. K.Sivasankari, Faculty of Computer Science, SRMIST, Bharathi Salai, Ramapuram, Chennai, Tamil Nadu 600089, India.
2Shubham Singh, Computer Science, SRMIST, Bharathi Salai, Ramapuram, Chennai, Tamil Nadu 600089, India.
3Kanhaiya Kumar, Computer Science, SRMIST, Bharathi Salai, Ramapuram, Chennai, Tamil Nadu 600089, India.
4Aman Dubey, Computer Science, SRMIST, Bharathi Salai, Ramapuram, Chennai, Tamil Nadu 600089, India.
Manuscript received on 30 May 2021 | Revised Manuscript received on 07 June 2021 | Manuscript Accepted on 15 June 2021 | Manuscript published on 30 June 2021 | PP: 6-10 | Volume-1 Issue-2, June 2021 | Retrieval Number: 100.1/ijipr.B1007061221 | DOI: 10.54105/ijipr.B1007.061221
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© The Authors. Published by Lattice Science Publication (LSP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The major part of the underlying idea is going to detect the fire from upcoming smoke and the shade color of the smoke using convolutional neural network. The fire detection followed by the smoke detection is going to depend on the shade and the direction vector analysis in this paper. Image processing from the available set of data is very vague ideation so in order to strengthen the idea we are incorporating two main features that is the smoke shade and direction vector. For this major process we will involve data preprocessing through bi-variate hypothesis to select two variables as the color of smoke and the direction of the smoke and hence do the further analysis on other features that how are they going to help in the upcoming detection neurons for the robust algorithm of fire detection.
Keywords: Smoke Feature Recognition, Yolo, CNN
Scope of the Article: Image Capturing