Predicting algal blooms has so far been done manually by LG Sonic water quality experts who analyse the water quality data combined with Remote Sensing images and meteorological parameters. But now, LG Sonic will make use of Artificial Intelligence (AI) to further develop the software algorithm, which will make it possible to predict algal blooms based on water quality data stored in t he MPC-View software automatically. In addition, it will provide detailed information about the intensity and impact of the algal bloom on the ecosystem of the water body.
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, which are all essential for the prediction of harmful algal blooms.
Algal blooms can not only cause health threats to humans and animals, but can disturb the whole ecosystem of the water as well. As algae reduces light penetration, depletes oxygen, and releases toxins, these unfavourable conditions should be prevented. However, there are many contributors to a rise in algal trends, and once an algae bloom is visible, it is more difficult to treat, and the water ecosystem, already harmed.
Having been gathering water quality information for many years in different water bodies all over the world, LG Sonic has now combined water quality and ultrasound technology to provide a complete algae solution for large water surfaces. Presently, LG Sonic is running projects in countries such as Argentina, Belgium, Chile, Singapore, and the United States (U.S.).