How do you identify microplastics in wastewater? When Wayne Parker started out researching the issue, the existing techniques were time-consuming and cumbersome. For a long time, optical or infrared microscopes were used to manually analyze and identify the tiny fragments of plastic waste in the water. However, differentiating microplastics from other substances took time and expertise. “When we started looking at more advanced microscopy methods, we found that the analysis of the images that were being generated from those microscopes had some issues,” Parker, a professor of civil and environmental engineering at the University of Waterloo in Ontario, Canada, told Mongabay in a video interview. “We thought it could be improved upon by using more of a deep learning, AI-based approach.” That led Parker to his colleague Alexander Wong, an expert in artificial intelligence and a professor in the systems design engineering department at the same university. Together, they worked with a PhD candidate to develop an image identification system that could potentially be used by wastewater treatment plants and food producers to identify the presence of microplastics and reduce the harm they pose to human health and the environment. PlasticNet uses deep learning, a subset of artificial intelligence, to identify microplastics based on the signals they produce in response to light exposure. A study published by the team in the journal Environmental Pollution details how they trained the model to detect microplastics based on their interaction with different wavelengths of light. While the tool isn’t publicly available yet, it…This article was originally published on Mongabay
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