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.