The global aquaculture industry faces escalating challenges from climate change, including unpredictable weather patterns and increased frequency of harmful algal blooms. Regulatory bodies and consumers are demanding more sustainable and resilient food production systems. This technology directly addresses these pressures by providing critical foresight, enabling proactive risk management, and supporting the transition to more environmentally responsible and economically stable marine operations worldwide.
Achieves long-term, high-accuracy red tide prediction: AI-driven time-series forecasting from multiple water quality and meteorological factors, predicting red tide occurrence up to one month in advance with over 90% accuracy, enabling proactive countermeasures.
Integrates and analyzes diverse environmental factors: Comprehensively analyzes chlorophyll concentration, water temperature, salinity, dissolved oxygen, turbidity, and flow velocity, alongside air temperature, precipitation, and sunshine duration, to elucidate complex marine environments.
Secured stable rights through rigorous examination: A robust patent granted after comparison with 8 prior art documents and multiple office actions, indicating low invalidation risk and providing a stable business foundation.
This patent protects an AI-driven system for long-term, high-accuracy environmental factor prediction, specifically for red tide occurrences, by integrating diverse water quality and meteorological time-series data. The claims are broad and robust, having withstood rigorous examination against 8 prior art documents, indicating strong legal stability.
This patent focuses on predicting marine environmental factors using specific water quality and meteorological data. White space exists in applying similar AI time-series prediction models to terrestrial agricultural pest/disease forecasting or urban air quality management, utilizing different sensor data sets.
Annual damage to aquaculture from red tides can reach hundreds of millions of dollars. High-accuracy prediction up to one month in advance allows for proactive measures such as relocating farmed fish, early harvesting, or adjusting feed. This could avoid approximately 30% of annual damages (e.g., 30% of $3.3M), leading to an estimated economic benefit of over $1.0M annually.
X: Prediction Period Length & Reliability
Y: Factor Comprehensiveness & Accuracy