The University of Hong Kong (20240328928). METHOD AND APPARATUS FOR MICROPLASTIC IDENTIFICATION WITH POLARIZED DIGITAL HOLOGRAPHY simplified abstract
Contents
METHOD AND APPARATUS FOR MICROPLASTIC IDENTIFICATION WITH POLARIZED DIGITAL HOLOGRAPHY
Organization Name
Inventor(s)
Yin Mun Edmund Lam of Hong Kong (HK)
METHOD AND APPARATUS FOR MICROPLASTIC IDENTIFICATION WITH POLARIZED DIGITAL HOLOGRAPHY - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240328928 titled 'METHOD AND APPARATUS FOR MICROPLASTIC IDENTIFICATION WITH POLARIZED DIGITAL HOLOGRAPHY
The abstract describes a method for identifying aquatic microplastics using a laser beam, a polarization camera, and a morphology analyzing module with a lightweight convolutional neural network model.
- Emitting a laser beam through a liquid sample containing microplastic samples in a sample channel and capturing a sample image with a polarization camera.
- Analyzing the interference patterns in the sample image using a morphology analyzing module with a convolutional neural network model.
- Real-time tracking and classification of microplastic samples based on the analysis of the interference patterns.
Potential Applications: - Environmental monitoring of microplastic pollution in aquatic ecosystems. - Research on the sources and distribution of microplastics in water bodies. - Quality control in industries producing products that may contribute to microplastic pollution.
Problems Solved: - Difficulty in identifying and tracking microplastic particles in water samples. - Lack of real-time analysis tools for monitoring microplastic pollution. - Limited efficiency in classifying different types of microplastics.
Benefits: - Enhanced accuracy and efficiency in identifying microplastics in aquatic environments. - Real-time tracking and analysis of microplastic pollution for timely intervention. - Improved understanding of the impact of microplastics on aquatic ecosystems.
Commercial Applications: Aquatic research institutions, environmental monitoring agencies, water treatment facilities, and industries producing plastic products could benefit from this technology for monitoring and managing microplastic pollution in water bodies.
Questions about the technology: 1. How does the use of a convolutional neural network model improve the classification of microplastic samples? 2. What are the potential limitations of using a polarization camera for identifying microplastics in water samples?
Original Abstract Submitted
a method for aquatic microplastic identification is provided. the method includes steps as follows: emitting a laser beam from a laser source, such that the laser beam passes through a liquid sample with mp samples in a sample channel and then a polarizer and is received by polarization camera; capturing a sample image of the mp samples by the polarization camera, wherein the sample image comprises interference patterns resulting from superposition of object and reference waves; and feeding the interference patterns into a morphology analyzing module for real-time tracking and analyzing by using a lightweight convolutional neural network (cnn) model, so as to classify the mp samples.
