Natural environments rarely behave in perfectly predictable ways.
Environmental variables interact continuously, often producing complex behaviours that are difficult to identify using fixed analytical rules.
Artificial Intelligence is particularly effective at recognising recurring patterns within large historical datasets.
Examples may include:
- recurring responses to irrigation schedules
- characteristic behaviour of specific soil types
- seasonal climatic influences
- crop-specific hydraulic behaviour
- relationships between atmospheric conditions and soil dynamics
Pattern recognition enables the platform to progressively improve its understanding of each monitored installation.