Predictive monitoring, identification, and control of Microcystis blooms in a drinking water source basin: An integrative artificial intelligence and bioinformatics approach | Synapse
March 3, 2026
Predictive monitoring, identification, and control of Microcystis blooms in a drinking water source basin: An integrative artificial intelligence and bioinformatics approach
Key Points
Effective predictive monitoring can significantly enhance the control of harmful Microcystis blooms.
AI and bioinformatics were integrated for real-time monitoring and identification of harmful algal blooms.
Analysis utilized various environmental data to predict and manage bloom occurrences in drinking water basins.
These findings may enable safer drinking water management and reduce health risks associated with algal toxins.