Forecasting Pollen Concentration using ML and Pollen Taxa Classification using CNN
- 8 July 2021
- preprint
- Published by Elsevier BV in SSRN Electronic Journal
Abstract
Natural fluctuations within the climate and increase in emission of greenhouse gases are now considered to be a heavy issue for inflicting environmental conditions. Effect of which can also be seen as an increase in the distribution of plants releasing allergic pollen. Thus, predicting pollen count and classification of the pollen taxa can be very useful for those who are prone to seasonal allergies like hay fever, allergic rhinitis, etc. The proposed work in this paper focuses on the development of a web-based application using Django which will be forecasting the concentration of airborne pollen for the next two days using Random Forest Regressor, a machine learning algorithm, by considering various meteorological variables and performing classification of pollen taxa using CNN based architecture Inception_V3, a deep learning approach.This publication has 5 references indexed in Scilit:
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