Abstract: A system and method for image-based irrigation system management. The method includes continuously obtaining sensor signals, wherein the sensor signals include at least one first image showing at least one crop; analyzing the obtained sensor signals, wherein the analysis includes performing machine vision on the at least one first image; determining, based on the analysis, at least one current crop identifier of the at least one crop; and determining, in real-time, a dispersal route for an irrigation system based on the at least one current crop identifier.

Abstract: A system and method for dynamic irrigation management. The method includes continuously obtaining thermal signals captured in a farm area, the farm area including at least one crop; analyzing the obtained thermal signals, wherein the analysis includes comparing the obtained thermal signals to a plurality of combinations of predetermined thermal signals, wherein each combination is associated with a known watering state, each combination including at least one type of thermal signal, wherein the thermal signals are captured by at least one thermal sensor deployed in the farm area; determining, based on the analysis, a current watering state of the at least one crop; and generating, in real-time, an irrigation pattern for the farm area based on the determined current watering state.

Abstract: A system and method for identifying developmental anomalies. The method includes obtaining a first set of at least one multimedia content element showing at least one crop and captured using a first set of at least one capturing parameter; obtaining normal development data for the at least one crop, wherein the normal development data represents at least one normal development characteristic of the at least one crop; analyzing, via machine vision, the first set of at least one multimedia content element to identify a first set of at least one characteristic of the at least one crop; determining, based on the first set of at least one characteristic and the normal development data, whether a suspected anomaly is identified; and verifying if the suspected anomaly is an anomaly using a second set of at least one multimedia content element captured using a second set of at least one capturing parameter.

Abstract: A system and method for determining at least one absolute color value for a target area. The method includes configuring a light source to emit light toward the target area, wherein the target area includes at least one crop; causing a capturing device to capture at least one artificial illumination multimedia content element showing the at least one crop in the target area while the light source emits the light; receiving, from the capturing device, the captured at least one artificial illumination multimedia content element; analyzing, via machine vision, the captured at least one artificial illumination multimedia content element; and determining, based on the analysis, at least one absolute color value of the at least one crop, wherein the at least one absolute color value is utilized to calibrate a plant monitoring system.

Abstract: A system and method for predicting harvest yield. The method includes receiving monitoring data related to at least one crop, wherein the monitoring data includes at least one multimedia content element showing the at least one crop; analyzing, via machine vision, the at least one multimedia content element; extracting, based on the analysis, a plurality of features related to development of the at least one crop; and generating a harvest yield prediction for the at least one crop based on the extracted features and a prediction model, wherein the prediction model is based on a training set including at least one training input and at least one training output, wherein each training output corresponds to a training input.

Abstract: A system and method for optimizing chemigation of a crop. The method includes: identifying at least one image of at least one portion of the crop; analyzing, via machine imaging, the at least one image to identify at least one reference image respective of the crop; determining, based on the at least one reference image, at least one abnormality respective of the crop; and generating a chemical composition for treating the at least one abnormality.

Abstract: A system and method for automatic plant monitoring. The method comprises: identifying at least one test input respective of a test area, wherein the test area includes at least one part of a plant; and generating a plant condition prediction based on the at least one test input and on a prediction model, wherein the prediction model is based on a training set including at least one training input and at least one training output, wherein each training output corresponds to a training input.