The irrigation algorithms decide based on weather forecasts: temperature, humidity, wind, evapotranspiration, solar exposition and 510 addicional weather parameters that can be used on decision making process and events relation. An unprecetended capability to explain what was until now inexplicable.
Capacity to automate processes predictively according to weather information and data colleted in the field.
Automatic detection of events by vision. We train mathematical models that run inside our controllers and interpret the "visual world" with deep learning models. We can act based on vision and generate relevant information for decision making process.
Real time video with computer vision intelligence as sensoring is an important new source of information that allows better systems management
Capability for relating and learning over hundreds of critical factors of decision making. Models include new sensing capabilities and learning models for a autonomous and intelligent decision.
Information extraction from satellite imagery and possibility to combine it with controllers' automatic decision.
Satellite imagery and NDVI representation to obtain more information and a better use of precision irrigation.
Simplified and humanized communication for reporting security events, mal-functions, operations historic, irrigation recommendation and general reports.
Our field controllers have an unprecendent computation power that allows the local management of complex procedures and make decisions in real time that were before considered too complicated to perform. Distributed computation capability to the increasing need for data treatment.
Trigger.systems controllers have the capability of closing the cycle between the several sources of information and decision. Actuating over the systems with valuable actions it is now truly a autonomous and intelligent process.