Can AI Tech Help Your Farm Stand Strong in a Storm? Yes

By Growing Produce

For any given hurricane season, all it takes is one storm to cause chaos, reports Growing Produce. Farmers who operate in hurricane-prone zones know this well. Proper preparation is paramount to maintain business during and after the storm. Advanced forecasting technology has come a long way to help in this regard. And it continues to grow in scale and scope thanks to artificial intelligence. Christopher Safieh, Head of Growth for UniSpice, says AI is helping the international foodservice company and its network of growers stay steps ahead of extreme weather events.

Currently, he says four AI-based technologies are being used by the company:

Deep Learning Models: Convolutional Neural Networks and Recurrent Neural Networks analyze large datasets from satellite imagery and weather stations.
Machine Learning Algorithms: Random Forests and Gradient Boosting predict storm patterns by analyzing historical weather data and identifying trends.
Natural Language Processing (NLP): NLP models interpret vast amounts of textual data from meteorological reports and scientific publications.
Ensemble Models: Combining multiple models improves prediction accuracy, aggregating the outputs of individual predictors for more reliable forecasts. A good example of this is what is referred to as “spaghetti models.”

Safieh says these AI models have several advantages over traditional forecasting. Most important of these is higher accuracy. “Our AI models process and analyze more data at a faster rate, leading to more accurate predictions,” he says.

A trio of other advantages also stand out to Safieh. These include:

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Improved Pattern Recognition: “Machine learning models excel at recognizing complex patterns in large datasets, which traditional models may overlook.”
Adaptability: “AI models continuously learn and improve from new data, enhancing their predictive capabilities over time.”
Real-Time Analysis: “AI allows for real-time data processing, enabling more timely and responsive forecasting compared to traditional methods.”

For more, continue reading at Growing Produce.