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Academic Journal of Environmental Biology, 2021, 2(4); doi: 10.38007/AJEB.2021.020403.

Air Microbial Pollution in Public Places Based on Convolutional Neural Network


Asian Ullah

Corresponding Author:
Asian Ullah

American University of Afghanistan, Afghanistan


Air microbial pollution in public places is particularly harmful to children who are in the growth and development period and the elderly with reduced physical function. Therefore, it is urgent to improve the ecological environment and give mankind a healthy earth. The purpose of this paper is to study air microbial pollution in public places based on convolutional neural networks. The relevant theoretical knowledge of microbial species identification based on CNN model is introduced in detail. The identification of bacterial and fungal concentrations of microorganisms in medical buildings in colleges and universities is analyzed. The species identification method based on hierarchical CNN is compared with the existing species identification tools RDPClassifier and 16SClassifier based on machine learning algorithms in terms of classification accuracy and identification speed. By comparison, the feasibility and efficiency of the hierarchical CNN-based species identification method are verified.


Convolutional Neural Network, Public Places, Air Pollution, Microbial Pollution

Cite This Paper

Asian Ullah. Air Microbial Pollution in Public Places Based on Convolutional Neural Network. Academic Journal of Environmental Biology (2021), Vol. 2, Issue 4: 19-27. https://doi.org/10.38007/AJEB.2021.020403.


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