A method may include receiving a request from a first user for a task to be completed on an agricultural field including an identification of the agricultural field, a piece of agricultural equipment for use on the agricultural field, and a date range for the task; generating a job data structure with the information in the request; executing a query to identify an operator for an available piece of agricultural equipment during the date range; transmitting a notification to a second user, the notification identifying request information, receiving confirmation the operator will complete the task and updating the job data structure based on the confirmation; in response to receiving a completion indication, transmitting a rating request for the piece of agricultural equipment; receiving, from the computing device, a rating for the piece of agricultural equipment; and updating an equipment listing for the second user with the rating.

A method for producing a well includes receiving production information associated with wells within a field; deriving a field specific model from the production information; receiving production information associated with the well; projecting production changes associated with installing artificial lift at the well at a projected date, the projecting using a production analysis engine applied to the field specific model, the projecting including determining a set of artificial lift parameters; and installing the artificial lift at the well in accordance with the artificial lift parameters.

An intelligent task assistant program can identify tasks associated with a user over a reporting period based on an analysis of, and inferences drawn from, data associated with one or more personal information programs, such as an electronic calendar application, an electronic reminder application, an electronic collaborative application, and/or an electronic communication application. The task assistant may also prioritize the identified tasks based on content associated with the tasks. Some or all of the prioritized tasks can be provided to an output device for perception by the user.

Various implementations disclosed herein include devices, systems, and methods that enable improved display of virtual content in computer generated reality (CGR) environments. In some implementations, the virtual content includes a reminder associated with a user and the user's physical environment.

An event scheduling system is described herein. The event scheduling system may configure a forecast model to utilize a plurality of time-based parameters. The event scheduling system may receive historical data that identifies historical workforce arrangements in association with a performance parameter of an organization. The event scheduling system may receive a request to schedule a workforce in association with a forecasted event. The event scheduling system may cause a forecast model to indicate a workforce arrangement for the organization during a time frame associated with the forecasted event. The event scheduling system may schedule a set of resources for work during the time frame in accordance with the workforce arrangement.

Computing device state or activity based task reminders and automatic tracking of statuses of task-related activities are provided. Users are enabled to create reminders that are triggered based on a device state of the user's device or activity signals from the operating system, an application, or a user file. The status of a task item can be inferred from signals collected from one or more sources. The signals provide information associated with tasks that the user performs in various life events. Machine learning, statistical analysis, behavioral analytics, and data mining techniques are applied to the signals, and the user's activities are mapped to task items that the user has created. An inferred status of a task activity can be shared with other systems, or can be used for a variety of functions (e.g., to automatically update the user's task list, or to remind the user of an uncompleted task item).

A user device may detect a message received via a messaging platform of one or more messaging platforms. The user device may determine that the message is from a second user based on a match between a user identifier associated with the message and a second user identifier corresponding to the messaging platform for the second user. The user device may transmit message data that includes: message content of the message, and information that identifies the messaging platform used to transmit the message. The user device may receive task information that indicates a task type for a task determined from the message content, a task priority for the task, and information that identifies the second user, and information that identifies the messaging platform. The user device may present the task information via a user interface of the cross-platform messaging application executing on the user device.

A system for shift design and assignment comprises an interface configured to receive scheduling input data which includes labor demand data, worker data, and scheduling configuration data, and a processor configured to generate a set of shift candidates, determine a set of decision variables, determine a cost function, determine a set of constraints, and determine simultaneously, using a SAT, a MP solver, or a MIP solver, a subset of the shift candidates selected in a final schedule and a set of shift assignments of which worker is assigned to which selected shift candidate of the subset of the shift candidates such that the hard constraints are fully respected, violations to the soft constraints are minimized, and the cost function is minimized.

The present teaching relates to method, system, medium, and implementations for task management. When information related to at least one task to be carried out by a user is received, multiple features associated with each of the at least one task are predicted automatically based on a plurality prediction models, derived based on historic information related to the user in carrying out past tasks. The at least one task is then automatically scheduled in a calendar associated with the user based on the multiple features predicted for each of the at least one task to generate an updated calendar with the at least one task scheduled therein.

A method and an agricultural management system for determining an optimized agricultural cultivation strategy is disclosed. The method includes: determining input factors by one or both of querying or evaluating information that influences one or both of the agricultural cultivation strategy or the crop rotation plan to be determined and information from or transmitted to external data sources independent of the agricultural management system; determining one or more optimization goals; selecting at least one of the specified optimization goals using an input/output unit; optimizing one or both of the agricultural cultivation strategy or crop rotation plan for the at least one selected optimization goal; and outputting the one or both of the optimized cultivation strategy or the optimized crop rotation plan using the input/output unit.