Agribusiness is on the cusp of digital transformation.
Growing demands for food security have led to new methodologies for large-scale crop production. Meanwhile, the impacts of climate change have introduced new variability and risk into the agriculture industry.
The IBM Environmental Intelligence Suite offers farmers and food producers near-real-time weather data sets and agriculture forecasting models powered by machine learning—powerful tools that help the agricultural sector plan for crop production, land utilization, supply chain and market demand.
Satellite imagery, weather forecasts and intricate modeling enable accurate forecasts of market supply, so that food processors and brands can source materials at a competitive price, meet competitive demands, and leverage commodity and futures trading.
A combination of weather and geospatial-temporal data, early detection of demand fluctuations and sophisticated AI modeling delivers accurate forecasts of product demand, enabling strategic resource planning for production, inventory, logistics, sales and operations.
Hyper-local weather data, sophisticated modeling and rich APIs can be used to create customized solutions for planting, feeding, spraying and irrigation scheduling in farms and fields.
IBM and Texas A&M AgriLife are working together to help farmers receive insights for water usage, which can increase crop yield and decrease economic and environmental costs.
Plan21 and IBM improve global food security by helping smallholder farmers in Latin America manage crops more sustainably and productively.
Mercados EMI, a consultancy firm for the energy sector, teamed up with IBM on an AI-based solution using weather data to help predict and prepare for energy demands.