Detection of atmospheric emissions by classifying images with convolutional neural networks

Automatic detection of atmospheric emissions is becoming essential in current factories. There is a lack of systems to detect emissions, although there are several systems to detect smoke that could be adapted for detecting emissions. This is the approach followed in this work: using convolutional neural networks (CNN) to classify images as containing emissions or not. Then, emissions are detected by analyzing the sequences of images classified as containing emissions. This detection system, based on a CNN, can be used in any factory simply by training the CNN with images of the factory with and without emissions.