M-Cubic-ENG

Recently, the occurrence of water quality problems caused by climate change has increased. In addition, there are problems with taste and smell of water caused by harmful blue-green algae, clogging of sand filter caused by diatom.

There is a need for a real-time algae monitoring system to recognize and respond in advance to the inflow of abnormal water quality from water sources.

Traditionally, algae analysis is performed using a microscopic counting method by experts, but it is necessary to use measuring equipment to support the real-time continuous monitoring.

Microalgae in the water are continuously captured by an optical lens and high-resolution CMOS camera, and individual algae images are clipped through image processing.

The species of algae are determined and the number of cells is quantified by comparing with databases classified according to the morphological characteristics of algae.

Deep learning algorithm of artificial intelligence techniques classify characteristics of algae species.

Real-time continuous monitoring in connection with pre-filtering and sample supply device

Rapid analysis compared to microscopic method

Automation of analysis from sample supplying to cleaning process

Enable accurate data acquisition regardless of analyst proficiency

Database update available for new species and species of interest

Supplying data communication protocol for an integrated monitoring system

User friendly interactive Graphic user interface

Display of Real-time analysis algae images and numbers of cells

Display of trends of algae species and diatom size distribution

Database platform for 10 algae species