Systems and methods for automated event detection of controlled-environment facility residents, such as identification of potential dangers and/or issues concerning correctional facility inmates. The system and method employs at least one biometric capture device or mechanism disposed within a controlled-environment area configured to capture biometrics of residents of the controlled-environment facility within the controlled-environment area. A controlled-environment facility administration and management system, or the like, is configured to enroll key biometric identification biometric features of residents of the controlled-environment facility and compare captured biometrics of the residents to enrolled key biometric features of residents of the controlled-environment facility to identify the resident. The system also identifies parameters that define an occurrence of an event. The system monitors the conditions within the facility to detect the occurrence of such an event.

A calendar application server, a computer-readable storage medium, and corresponding methods for third-party resource management within the context of a calendar application are described herein. The computer-readable storage medium includes computer-executable instructions that, when executed one or more processors, cause the processor(s) to associate a third-party resource with an event within a calendar application in response to a user command received via an event UI functionality provided by the calendar application, to connect with the third-party resource via an API corresponding to the third-party resource in response to another user command received via the event UI functionality (where the API is provided within the context of the calendar application), to generate third-party resource data for the event in response to user interaction with the third-party resource via the API, and to reconcile the third-party resource data with event data within the calendar application.

A method, apparatus, system, and computer program code for autonomous management of request-for-approvals within an organization. The computer system receives a request-for-approval submitted by an employee of the organization. The computer system determines whether a set of rules has been configured for autonomously managing a human capital operation associated with the request-for-approval. Responsive to determining that the set of rules has been configured, the computer system determines whether a set of parameters for applying a particular rule has been met. Responsive to determining that the set of parameters for the particular rule has been met, the computer system applies the particular rule to determine an outcome. The computer system determines whether outcomes are consistent for each rule of the set of rules that was applied. Responsive to determining that the outcomes are consistent, the computer system autonomously performs the human capital operation according to the outcomes. Responsive to performing the human capital operation, the computer system transmits a confirmation of the human capital operation to an employee-manager.

A system and method for generating a cue sheet for submission to a performing rights organization. The system comprising a processor for executing the steps of: receiving an electronic file associated with a broadcast production comprising a list of cues used in the broadcast production and associated use data; extracting irrelevant data from the electronic file by determining and deleting irrelevant cues, determining and deleting unnecessary and unrelated use data from each cue, and determining and deleting duplicative cues, so that relevant cues and associated use data remain after extracting; searching a music catalog database to retrieve identification data for each relevant cue; storing each relevant cue with its associated use data and identification data in a memory; and generating a cue sheet comprising relevant cues with associated use data and identification data for each relevant cue.

A system and method for advanced inventory management using deep neural networks. The system may be disposed in a business establishment or it may be a cloud-based network comprising a one or more databases to store and retrieve including patron data, recipe data, business data, and inventory data, mobile and compute devices, staff and suppliers, one or more gateways for vendors and staff to interface with other third-party business, and an inventory analysis server. Taken together or in part, optimize organizational operations by predicting and optimizing key inventory decisions using artificial intelligence or other computerized methods around inventory management based upon a large amount of variables associated with the enterprise.

A system and method for transport management includes a back-end system controlling a display depicting real-time location tracking for drivers or commodities requiring location tracking, route status tracking for driveaway vehicles and towable unites, and freight using a location tracking device including a GPS device connected to a cloud-based infrastructure. A server of the back-end system executes a plurality of modules including at least: a trip management module configured to facilitate control of a trip, including request of the trip by a driver and assignment of the trip to the driver by the back-end system; a driver management module configured to facilitate control of driver operations, including canceling the trip or abandoning a trip and notifying the driver via the end-user device; and a settlement management module configured to facilitate settlement or completion of the trip, including submission of inspection documents of the freight or the transportation vehicle before the trip begins and after the trip has ended. Units are also monitored by utilizing geo fences to monitor zones where units are stored, managed, serviced, and inspected.

Disclosed herein are embodiments of systems, methods, and products comprises a server for monitoring and tracking user activities based on different events in a security log. The server may retrieve the security log and parse the security log to identify a set of predetermined events for a user based on the event IDs, including logon events, logoff events, and privileged events. Based on the time point when privileged events occur at least partially during the pattern of having more logon events than logoff events, the server may determine when the user starts to work. Based on the time point when the logoff events and logon event starts to show the pattern that there are more logoff events than logon events and the difference increasing into a threshold, the server may determine when the user stops working. The server may generate a heat map indicating different users' work time length.

A method for detecting anomalous data is provided. The method comprises collecting a training dataset comprising a number of transactional time series, wherein the time series comprise non-anomalous data entries for a specified transaction type. The training dataset is fed into a gated recurrent unit (GRU) network, which learns the data distribution for the transactional time series. The GRU predicts expected future values of the specified transaction type according to the learned data distribution. An upper bound and a lower bound for future values are calculated based a standard deviation of the predicted values. When new data entries of the specified transaction type are received their values are compared to the upper bound and the lower bound, and an error notification is provided if the values of the new data entries fall outside the upper bound or lower bound.

A process management method includes a work time acquisition step, an image acquisition step, and an association step. The work time acquisition step includes acquiring work time information about a work time for which a person performs work, including a predetermined operation, in a work area. The image acquisition step includes acquiring image information about an image captured by an image capture device and covering at least the work area. The association step includes associating the work time information acquired in the work time acquisition step and the image information acquired in the image acquisition step with each other as association information.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining true utilization based on productive behaviors of operators in a digital environment. One of the methods includes automatically determining productivity for each of multiple users of an organization. Timing data for a user is received that indicates available work time for the user. Interaction data is received for the user for interactions by the user during the available work time for the user. Productivity rules for an organization of the user are received that define productivity of interactions by users of the organization. Productivity of interactions of the user is determined based on the interaction data and the productivity rules. True utilization for the user is determined based on the productivity of the interactions and the timing data. Action data is generated based on the determined true utilization action is taken based on the action data.