HCHODetector: Formaldehyde concentration detection based on deep learning

Abstract

Currently, deep learning technology is developing rapidly. Deep learning is mainly used in the fields of vision and hearing for human beings, but less in the field of olfactory. Formaldehyde is a common gas harmful to human health. However, the traditional methods of Formaldehyde concentration detection are inefficient in some cases. As for this problem, this paper proposes a novel formaldehyde detector namely HCHODetector. Specifically, this detector is based on deep learning and HSV colour space augmentation. Moreover, we propose a novel Mask-guided module and a novel pre-training network to enhance the colour discrimination ability of HCHODetector. As a consequence, the experimental results show that the detection error is within 0.08 mg/m3 in the actual environment, which provides a new idea for Formaldehyde concentration detection.