There is provided a smart drip irrigation emitter to provide intelligent features including on-demand watering, sensors and communication links. The emitters can be activated by a wireless signal to power and/or control water delivery from the emitter. The emitter also may include sensors that gather data pertaining to an individual plant. Based on the data received by the sensors, the emitter intelligently determines whether to water the plant. The smart emitter can form a communication network with other smart emitters.

There is provided a smart drip irrigation emitter to provide intelligent features including on-demand watering, sensors and communication links. The emitters can be activated by a wireless signal to power and/or control water delivery from the emitter. The emitter also may include sensors that gather data pertaining to an individual plant. Based on the data received by the sensors, the emitter intelligently determines whether to water the plant. The smart emitter can form a communication network with other smart emitters.

The present embodiments provide systems, processes and/or methods of controlling irrigation. In some embodiments, methods are provided that receive (4112) water usage information corresponding to a first volumetric water usage at a site location having an irrigation controller (130), wherein the first volumetric water usage corresponds to volumetric water usage from a beginning of a budget period of time to a first time within the budget period of time; determine (4114) automatically whether a volumetric water budget at the site location will be met for the budget period of time based on at least the first volumetric water usage, the volumetric water budget corresponding to a specified volume of water for use during the budget period of time; determine (4116) automatically, in the event the volumetric water budget will not be met, an adjustment to the irrigation by the irrigation controller; and output (4118) signaling to effect the adjustment.

The present embodiments provide systems, processes and/or methods of controlling irrigation. In some embodiments, methods are provided that receive (4112) water usage information corresponding to a first volumetric water usage at a site location having an irrigation controller (130), wherein the first volumetric water usage corresponds to volumetric water usage from a beginning of a budget period of time to a first time within the budget period of time; determine (4114) automatically whether a volumetric water budget at the site location will be met for the budget period of time based on at least the first volumetric water usage, the volumetric water budget corresponding to a specified volume of water for use during the budget period of time; determine (4116) automatically, in the event the volumetric water budget will not be met, an adjustment to the irrigation by the irrigation controller; and output (4118) signaling to effect the adjustment.

There is provided a smart drip irrigation emitter to provide intelligent features including on-demand watering, sensors and communication links. The emitters can be activated by a wireless signal to power and/or control water delivery from the emitter. The emitter also may include sensors that gather data pertaining to an individual plant. Based on the data received by the sensors, the emitter intelligently determines whether to water the plan. The smart emitter can form a communication network with other smart emitters.

There is provided a smart drip irrigation emitter to provide intelligent features including on-demand watering, sensors and communication links. The emitters can be activated by a wireless signal to power and/or control water delivery from the emitter. The emitter also may include sensors that gather data pertaining to an individual plant. Based on the data received by the sensors, the emitter intelligently determines whether to water the plan. The smart emitter can form a communication network with other smart emitters.

Systems and methods automate the design and execution of randomized experiments. Portions of a field are planted using an agricultural vehicle configured to randomly vary planting parameters when planting a portion of the field. A resulting crop outcome across each portion or sub-portion of the field is observed. A training set of data is generated that includes the varied planting parameters and the associated crop outcomes for each portion of the field. A machine-learned model is trained using the training set of data and is configured to predict a crop outcome for a portion of the field based on historical and forecast conditions and a set of planting parameters applied to a portion of the field. For subsequent iterations, for a target portion of the field, the machine-learned model can be applied to identify a set of planting parameters for planting the target portion of the field to optimize a desired crop outcome.

Systems and methods automate the design and execution of randomized experiments. Portions of a field are planted using an agricultural vehicle configured to randomly vary planting parameters when planting a portion of the field. A resulting crop outcome across each portion or sub-portion of the field is observed. A training set of data is generated that includes the varied planting parameters and the associated crop outcomes for each portion of the field. A machine-learned model is trained using the training set of data and is configured to predict a crop outcome for a portion of the field based on historical and forecast conditions and a set of planting parameters applied to a portion of the field. For subsequent iterations, for a target portion of the field, the machine-learned model can be applied to identify a set of planting parameters for planting the target portion of the field to optimize a desired crop outcome.

An automated system for identifying a watering zone malfunction includes a sensor and a controller. The watering zone includes a valve that couples an input conduit to an output conduit. The output conduit terminates at one or more water distributors. The sensor is for capturing mechanical perturbations of the watering zone. The controller is configured to: store a profile defining at least one profile parameter based upon a transient operation of the zone in an intact state, receive the signal from the sensor during a watering operation when the zone is in an unknown state, compute a operation parameter based upon the signal for at least one time window of receiving the signal, determining a malfunction exists, and determine whether to take further action based upon the comparison.

An automated system for identifying a watering zone malfunction includes a sensor and a controller. The watering zone includes a valve that couples an input conduit to an output conduit. The output conduit terminates at one or more water distributors. The sensor is for capturing mechanical perturbations of the watering zone. The controller is configured to: store a profile defining at least one profile parameter based upon a transient operation of the zone in an intact state, receive the signal from the sensor during a watering operation when the zone is in an unknown state, compute a operation parameter based upon the signal for at least one time window of receiving the signal, determining a malfunction exists, and determine whether to take further action based upon the comparison.