The global water quality monitoring market is expected to reach $4.69 billion by 2025 at compound annual growth rate of 4.54%. The significant size of this market is partially due to the value of water as a precious resource, but also because uncontaminated fresh water supplies are in significant decline, which necessitates innovative monitoring and remediation efforts to change this tragic trend. Therefore, one of the most significant tools that is needed to combat water contamination are accurate, timely, efficient and effective water quality monitoring solutions that will be able to not only track particles and identify pollution, but also characterize its type and source. The current water monitoring approaches suffer from a combination of issues, including being expensive, low-throughput, requiring expertise to operate, lacking accuracy and not offering automated capabilities for micro-object detection and classification.<br/><br/>Based on technology invented at the University of California Los Angeles in Prof. Aydogan Ozcan's group, we have developed aqusens - an AI-based lens-free platform for automated identification and characterization of micro-object/organisms in water. This platform integrates capabilities of not only a particle counter, but also is capable of performing particle characterization (in terms of size, shape, color, etc), perform automated identification and classification of potentially dangerous microorganisms and pathogens, as well as records sample images for offline analysis and reporting. Due to its design, the aqusens platform is low-cost, field portable, high-throughput and has an ultra-wide dynamic range. These characteristics make aqusens versatile for various applications from scientific monitoring of phytoplankton, identification of potentially toxic algae and cyanobacteria, professional use at water treatment plants to in-home tap water monitoring.

Aqusens: AI-based lens-free platform for automated identification and characterization of micro-object/organisms in water

2019 Fall National Meeting

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