1. Imaging pollen using a Raspberry Pi and LED with deep learning.
- Author
-
Mills B, Zervas MN, and Grant-Jacob JA
- Subjects
- Air Pollution, Air Pollutants analysis, Deep Learning, Pollen, Environmental Monitoring methods
- Abstract
The production of low-cost, small footprint imaging sensor would be invaluable for airborne global monitoring of pollen, which could allow for mitigation of hay fever symptoms. We demonstrate the use of a white light LED (light emitting diode) to illuminate pollen grains and capture their scattering pattern using a Raspberry Pi camera. The scattering patterns are transformed into 20× microscope magnification equivalent images using deep learning. We show the ability to produce images of pollen from plant species previously unseen by the neural network in training. Such a technique could be applied to imaging airborne particulates that contribute to air pollution, and could be used in the field of environmental science, health science and agriculture., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)
- Published
- 2024
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