An agricultural data collection framework is provided in a system and method for tracking and managing livestock, and for analyzing animal conditions such as health, growth, nutrition, and behavior. The framework uses ultra-high frequency interrogation of RFID tags to collect individual animal data across multiple geographical locations, and incorporates artificial intelligence techniques to develop machine learning base models for statistical process controls around each animal for evaluating the animal condition. The framework provides a determination of normality at an individual animal basis or for a specific location, and generates alerts, predictions, and a targeted processing or application schedule for prioritizing and delivering resources when intervention is needed.

A method for monitoring disease across agricultural areas of interest is provided comprising displaying at least one virtual zone corresponding to an agricultural geographic area of interest on a map in an application on a first device, and receiving an alert message when the first device is in proximity to a virtual zone. The at least one virtual zone is defined by at least one geofence. Each virtual zone is associated with a level of risk that indicates a likelihood of an outbreak of a disease detrimental to agriculture. Each virtual zone is configured to receive access notification information from each geofence when tracked devices enter an area defined by that geofence. The access information includes the level of risk associated with other virtual zones from which the tracked devices came. The alert message indicates if the first device should enter that virtual zone.

A method for monitoring disease across agricultural areas of interest is provided comprising displaying at least one virtual zone corresponding to an agricultural geographic area of interest on a map in an application on a first device, and receiving an alert message when the first device is in proximity to a virtual zone. The at least one virtual zone is defined by at least one geofence. Each virtual zone is associated with a level of risk that indicates a likelihood of an outbreak of a disease detrimental to agriculture. Each virtual zone is configured to receive access notification information from each geofence when tracked devices enter an area defined by that geofence. The access information includes the level of risk associated with other virtual zones from which the tracked devices came. The alert message indicates if the first device should enter that virtual zone.

A system (100), method and computer program product for optimization of crop protection. A generator module (120) accesses one or more configuration data structures (220) wherein the one or more configuration data structures include data fields to store crop data (221), advice data (222) related to respective crop data, and crop protection product data (223) related to respective advice. Further, it accesses a plurality of code snippets (230) wherein each code snippet (231, 232, 233) has a condition which relates either to at least one property field of the one or more data structures (220) or to a result of another code snippet, and further includes generic program logic associated with the condition, and wherein each property field is used in the condition of at least one code snippet. The plurality of code snippets is applied to the one or more configuration data structures to generate an advice logic program.

A system (100), method and computer program product for optimization of crop protection. A generator module (120) accesses one or more configuration data structures (220) wherein the one or more configuration data structures include data fields to store crop data (221), advice data (222) related to respective crop data, and crop protection product data (223) related to respective advice. Further, it accesses a plurality of code snippets (230) wherein each code snippet (231, 232, 233) has a condition which relates either to at least one property field of the one or more data structures (220) or to a result of another code snippet, and further includes generic program logic associated with the condition, and wherein each property field is used in the condition of at least one code snippet. The plurality of code snippets is applied to the one or more configuration data structures to generate an advice logic program.

A plan structure and a method for creating a plan for forming/operating a sub-sea or sub-terranean well, in an automated planner, are disclosed. The plan defines logical, sequential and conditional interrelationships between events in the plan, so that a controller can carry out the plan in a flexible and time-independent manner to complete the sequenced events. The definition of the logical, sequential and conditional interdependencies permits flexibility in how the controller uses the time and resources available to it so that the plan directs the controller in a non-prescriptive manner, allowing greater flexibility in plan execution and reducing the necessity for re-planning to occur when changes in the world or environment in which the controller executes the plan are detected.

A plan structure and a method for creating a plan for forming/operating a sub-sea or sub-terranean well, in an automated planner, are disclosed. The plan defines logical, sequential and conditional interrelationships between events in the plan, so that a controller can carry out the plan in a flexible and time-independent manner to complete the sequenced events. The definition of the logical, sequential and conditional interdependencies permits flexibility in how the controller uses the time and resources available to it so that the plan directs the controller in a non-prescriptive manner, allowing greater flexibility in plan execution and reducing the necessity for re-planning to occur when changes in the world or environment in which the controller executes the plan are detected.

Some implementations herein relate to a graphical user interface (GUI) that facilitates dynamically partitioning agricultural fields into clusters on an individual agricultural field-basis using agricultural features. A map of a geographic area containing a plurality of agricultural fields may be rendered as part of a GUI. The agricultural fields may be partitioned into a first set of clusters based on a first granularity value and agricultural features of individual agricultural fields. The individual agricultural fields may be visually annotated in the GUI to convey the first set of clusters of similar agricultural fields. Upon receipt of a second granularity value different from the first granularity value, the agricultural fields may be partitioned into a second set of clusters of similar agricultural fields. The map of the geographic area may be updated so that individual agricultural fields are visually annotated to convey the second set of clusters.

Some implementations herein relate to a graphical user interface (GUI) that facilitates dynamically partitioning agricultural fields into clusters on an individual agricultural field-basis using agricultural features. A map of a geographic area containing a plurality of agricultural fields may be rendered as part of a GUI. The agricultural fields may be partitioned into a first set of clusters based on a first granularity value and agricultural features of individual agricultural fields. The individual agricultural fields may be visually annotated in the GUI to convey the first set of clusters of similar agricultural fields. Upon receipt of a second granularity value different from the first granularity value, the agricultural fields may be partitioned into a second set of clusters of similar agricultural fields. The map of the geographic area may be updated so that individual agricultural fields are visually annotated to convey the second set of clusters.

A cognitive computing system for enhancing workflow performance in the oil and gas industry, in some embodiments, comprises: neurosynaptic processing logic including multiple electronic neurons operating in parallel; input and output interfaces coupled to the neurosynaptic processing logic; and one or more information repositories accessible to the neurosynaptic processing logic, wherein the neurosynaptic processing logic receives a workflow enhancement request via the input interface, accesses the one or more information repositories to obtain information pertaining to the request, uses said information to perform a probability analysis, produces an option relating to the workflow enhancement request based on said probability analysis, and presents said option via the output interface.