Updated Software Algorithm Can Automatically Predict Algal Blooms, Says LG Sonic

Algal blooms disturb the ecosystem of bodies of water, causing health threats to humans and animals.
Algal blooms disturb the ecosystem of bodies of water, causing health threats to humans and animals.

LG Sonic recently announced it’s making use of artificial intelligence to further develop a software algorithm that aims to automatically predict algal blooms based on water-quality data.

The algorithm also will provide detailed information about the intensity and impact of an algal bloom on a waster body’s ecosystem. The updated algorithm will be implemented in LG Sonic’s water quality software, MPC-View.

LG Sonic’s water quality experts have manually predicted algal blooms by looking at water quality data combined with remote sensing images and meteorological parameters. However, the updated algorithm will automatically predict algal blooms based on data stored in the MPC-View software.

The software receives its data from the MPC-Buoy, a floating solar-powered system that combines real-time water quality monitoring and ultrasonic sound waves to control algae effectively. MPC-View receives water quality parameters related to phytoplankton dynamics such as chlorophyll-a, temperature, DO, pH, turbidity, and redox.



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