AI Article Synopsis
- A low-cost imaging sensor for airborne pollen monitoring could help alleviate hay fever symptoms by providing valuable data.
- The process involves using a white LED and a Raspberry Pi camera to capture scattering patterns of pollen grains, which are then enhanced through deep learning to create higher magnification images.
- This innovative technique may also be useful for monitoring airborne pollutants, with potential applications in environmental science, health science, and agriculture.
Article 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.
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| http://dx.doi.org/10.1016/j.scitotenv.2024.177084 | DOI Listing |
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