A device may receive sensor data from a sensor device located on a particular farm. The device may identify an alert, associated with the particular farm, based on the sensor data and using a model. The model may be created based on imagery data and numeric data relating to a group of farms. The device may determine, using the model, a recommended course of action to address the alert, and provide, to a user device associated with the particular farm, the recommended course of action.
Please help me write a proper abstract based on the patent claims. CLAIM: 1-20. (canceled) 21. A method, comprising: capturing, by a processor of a first device, from a plurality of sensors, and via a network, first data, the plurality of sensors including a plurality of different types of sensors, the first data including at least one of: imagery data, or numeric data; receiving, by the processor, from a plurality of sources, and via the network, second data, the plurality of sources being different than the plurality of sensors, the second data being different than the first data, and the second data including at least one of: the imagery data, or the numeric data; processing, by the processor, the first data to create processed first data; processing, by the processor, the second data to create processed second data; creating, by the processor, a model, the model being created using a machine learning technique, the processed first data, and the processed second data; training, by the processor, the model based on training data, the training data including: information relating to an action taken, and information identifying a result of taking the action; receiving, by the processor and via the network, sensor data, the sensor data being received from one or more sensors, the one or more sensors being located in a geographic location; determining, by the processor and using the model and the sensor data, a recommended course of action; providing, by the processor and for display, information identifying the recommended course of action; receiving, by the processor, a selection relating to the recommended course of action; and causing, by the processor and based on receiving the selection relating to the recommended course of action, a second device, associated with the geographic location, to perform the recommended course of action, the second device being different than the first device. 22. The method of claim 21, where the geographic location is a farm, where the second device includes an unmanned aerial vehicle, where the recommended course of action includes capturing an image of a plot of the farm, and where, when causing the second device to perform the recommended course of action, the method includes: causing the unmanned aerial vehicle to capture the image of the plot of the farm. 23. The method of claim 21, where the geographic location is a farm, and where, when creating the model, the method includes: creating a plurality of models for the farm, the plurality of models including: a first model that is associated with a first portion of the farm, and a second model that is different than the first model and that is associated with a second portion of the farm, the first portion and the second portion corresponding to different plots of the farm or different crops of the farm. 24. The method of claim 21, where the recommended course of action relates to at least one of: maintenance of a piece of farming equipment associated with a farm, the farm relating to the geographic location, malfunction of the piece of farming equipment associated with the farm, harvest of a crop associated with the farm, storage of the crop associated with the farm, sale of the crop associated with the farm, detection of a disease in a plot of the farm, detection of an insect issue in connection with the plot of the farm, or an irrigation issue of the plot of the farm. 25. The method of claim 21, where, when determining the recommended course of action, the method includes: determining a plurality of recommended courses of action; determining, for each recommended course of action of the plurality of recommended courses of action, an impact of performing the recommended course of action or not performing the recommended course of action; ranking the plurality of recommended courses of action, based on determining the impact for each recommended course of action, to create a ranked list; and where, when providing the information identifying the recommended course of action, the method includes: providing information identifying the ranked list to a user device. 26. The method of claim 21, where the geographic location is a farm, where the second device includes an irrigation system, where the recommended course of action relates to watering of a plot of the farm, and where, when causing the second device to perform the recommended course of action, the method includes: causing the irrigation system to water the plot of the farm for a particular period of time. 27. The method of claim 21, where the recommended course of action relates to an issue in connection with a plot of a farm, and where the method further comprises: providing, for display, a user interface, the user interface including: aerial imagery of the plot at a point in time, and an interface that allows aerial imagery of the plot to be viewed at different points in time. 28. A computer-readable medium storing instructions, the instructions comprising: a plurality of instructions, which, when executed by a processor of a first device, cause the processor to: capture, from a plurality of sensors and via a network, first data, the plurality of sensors including a plurality of different types of sensors, the first data including at least one of: imagery data, or numeric data; receive, from a plurality of sources and via the network, second data, the plurality of sources being different than the plurality of sensors, the second data being different than the first data, and the second data including at least one of: the imagery data, or the numeric data; process the first data to create processed first data; process the second data to create processed second data; create a model, the model being created using a machine learning technique, the processed first data, and the processed second data; receive, via the network, sensor data, the sensor data being received from one or more sensors, the one or more sensors being located in a geographic location; determine, using the model and the sensor data, a recommended course of action; provide, for display, information identifying the recommended course of action to a user device; receive a selection relating to the recommended course of action; and cause, based on receiving the selection relating to the recommended course of action, a second device, associated with the geographic location, to perform the recommended course of action, the second device being different than the first device. 29. The computer-readable medium of claim 28, where the geographic location is a farm, where the second device includes an unmanned aerial vehicle, where the recommended course of action includes capturing an image of a plot of the farm, and where the plurality of instructions, that cause the processor to cause the second device to perform the recommended course of action, cause the processor to: cause the unmanned aerial vehicle to capture the image of the plot of the farm. 30. The computer-readable medium of claim 28, where the geographic location is a farm, and where the plurality of instructions, that cause the processor to create the model, cause the processor to: create a plurality of models for the farm, the plurality of models including: a first model, the first model being associated with a first portion of the farm, and a second model, the second model being different than the first model, the second model being associated with a second portion of the farm, and the first portion and the second portion corresponding to different crops of the farm or different plots of the farm. 31. The computer-readable medium of claim 28, where the geographic location is a farm, where the sensor data is associated with a plot of the farm, where the recommended course of action relates to an insect infestation or a disease, and where the plurality of instructions, when executed by the processor, further cause the processor to: provide, to the user device, a set of images of the plot, the set of images providing a timeline of an effect of the insect infestation or the disease on the plot over time. 32. The computer-readable medium of claim 28, where the geographic location is a farm, and where the recommended course of action relates to at least one of: maintenance of a piece of farming equipment associated with the farm, malfunction of the piece of farming equipment associated with the farm, harvest of a crop associated with the farm, storage of the crop associated with the farm, sale of the crop associated with the farm, detection of a disease in a plot of the farm, detection of an insect issue in connection with the plot of the farm, or an irrigation issue of the plot of the farm. 33. The computer-readable medium of claim 28, where the plurality of instructions, that cause the processor to determine the recommended course of action, cause the processor to: determine a plurality of recommended courses of action; determine, for each recommended course of action of the plurality of recommended courses of action, an impact of performing the recommended course of action or not performing the recommended course of action; order the plurality of recommended courses of action, based on determining the impact for each recommended course of action, to create an ordered list; and where the plurality of instructions, that cause the processor to provide the information identifying the recommended course of action, cause the processor to: provide the ordered list to the user device. 34. The computer-readable medium of claim 28, where the recommended course of action relates to an issue in connection with a plot of a farm, and where the plurality of instructions, when executed by the processor, further cause the processor to: provide, for display, a user interface, the user interface including: aerial imagery of the plot at a point in time, and an interface that allows aerial imagery of the plot to be viewed at different points in time. 35. A first device, comprising: a memory to store instructions; and a processor to execute the instructions to: capture, from a plurality of sensors and via a network, first data, the plurality of sensors including a plurality of different types of sensors, the first data including at least one of: imagery data, or numeric data; receive, from a plurality of sources and via the network, second data, the plurality of sources being different than the plurality of sensors, the second data being different than the first data, and the second data including at least one of: the imagery data, or the numeric data; process the first data to create processed first data; process the second data to create processed second data; create a model, the model being created using a machine learning technique, the processed first data, and the processed second data; receive, via the network, sensor data, the sensor data being received from one or more sensors, the one or more sensors being associated with a geographic location; determine, using the model and the sensor data, a recommended course of action; provide, for display, information identifying the recommended course of action to a user device; receive, from the user device, a selection relating to the recommended course of action; and cause, based on receiving the selection relating to the recommended course of action, a second device, associated with the geographic location, to perform the recommended course of action, the second device being different than the first device. 36. The first device of claim 35, where the geographic location is a farm, where the second device includes an unmanned aerial vehicle, where the recommended course of action includes spraying a plot of the farm, and where, when causing the second device to perform the recommended course of action, the processor is to: cause the unmanned aerial vehicle to spray the plot of the farm. 37. The first device of claim 35, where, when determining the recommended course of action, the processor is to: determine an impact of performing the recommended course of action or not performing the recommended course of action, and provide, for display, information identifying the impact of performing the recommended course of action or not performing the recommended course of action. 38. The first device of claim 35, where the geographic location is a farm, and where, when creating the model, the processor is to: create a plurality of models for the farm, the plurality of models including: a first model, the first model being associated with a first portion of the farm, and a second model, the second model being different than the first model, the second model being associated with a second portion of the farm, and the first portion and the second portion corresponding to different crops of the farm or different plots of the farm. 39. The first device of claim 35, where the recommended course of action relates to harvesting, storing, or selling a crop associated with a farm, and where the processor is further to: determine a peak price time period, during a period of time, for the crop, determine a growth degree days maturity time period, during the calendar year, for the crop, determine a peak price harvest period, during the period of time, based on the peak price time period and the growth degree days maturity time period, determine a peak yield time period, during the period of time, for the crop, predict a yield gross, for a period during the period of time, based on the peak price harvest period and the peak yield time period, determine financial information based on the predicted yield gross, and provide, for display, the financial information. 40. The first device of claim 35, where, when determining the recommended course of action, the processor is to: determine a plurality of recommended courses of action, determine, for each recommended course of action of the plurality of recommended courses of action, an impact of performing the recommended course of action or not performing the recommended course of action, order the plurality of recommended courses of action, based on determining the impact for each recommended course of action, to create an ordered list, and where, when providing the information identifying the recommended course of action, the processor is to: provide the ordered list to the user device.