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Artificial Intelligence for Rapid and Reliable Detection of Cryptosporidium oocysts and Giardia cysts (GWF Pillar 1 Ph2)
Section 1: Project Information
Artificial Intelligence for Rapid and Reliable Detection of Cryptosporidium oocysts and Giardia cysts
firstname.lastname@example.org 905 525 9140 ext 24802
Classification (e.g., "GWF Pillar 3", "CCRN", etc.)
GWF Pillar 1 Ph2
Protozoan cysts (Cryptosporidium oocysts and Giardia cysts) cause serious human health risks not only in urbanized areas but also in the cold and remote regions. Since these protozoan cysts are hardly inactivated in conventional drinking water treatment, reliable and rapid detection of the pathogenic cysts is urgently demanded, especially for communities without advance disinfection facilities, such as ozonation.
This project will develop a novel sensor system where water samples are examined under optical/fluorescent microscopes and the pathogenic cysts on the microscopic images are detected by artificial intelligence (AI).
Detailed research objectives and tasks are:
(1) to build a sufficient database of microscopic image for machine learning training of AI;
(2) to develop a filtration/resuspension system that selectively collects Cryptosporidium oocysts and Giardia cysts from other particles in natural water (natural organic matter particles, non-pathogenic microorganisms); and
(3) to apply fluorescent-labeled antibodies and genomic fragment amplification to enhance the sensor accuracy and reliability.
The new sensor system will be transformative as it will help improve water safety and control waterborne human diseases.
Position, Institution, and Contact Information
Current Status of this Project
◉ In Progress
T-2021-11-23-q3q1q3drowUwkixq2G7letxDUw Project 1.2