Machine Learning Applications for Fire Detection in a Residential Building

Fire is one of the most serious accidents that can occur in houses, schools, offices and companies. This can lead to several losses, causalities and serious equipment damages. It is highly essential to put in place advanced disaster response mechanisms in order to safeguard against fire disaster in our environment. Recently, modern buildings possess surveillance cameras for security purpose, such cameras can be utilized for fire detection in buildings. In this paper, deep learning and computer vision are applied for detecting fire incident in different systems. The proposed model utilizes an advanced image processing and classification algorithms via deep learning and convolutional neural networks (CNN) to improve the performance of residential fire alarms and eradicate nuisance alarm scenarios.

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