Abstract: Concepts and technologies directed to surrogate metadata aggregation for dynamic content assembly are disclosed. Embodiments can include a system that comprises a processor and a memory that stores computer-executable instructions that configure a processor to perform operations. The operations can include obtaining a first visual content from a digital data store, where the first visual content is configured to digitally represent a first scene. The operations can include performing image recognition on the first visual content so as to identify a second visual content that is digitally configured to represent a second scene. The operations can include determining that native original metadata cannot be obtained for the first visual content, where the native original metadata includes information about the first scene digitally represented by the first visual content.

Abstract: Concepts and technologies directed to surrogate metadata aggregation for dynamic content assembly are disclosed. Embodiments can include a system that comprises a processor and a memory that stores computer-executable instructions that configure a processor to perform operations. The operations can include obtaining a first visual content from a digital data store, where the first visual content is configured to digitally represent a first scene. The operations can include performing image recognition on the first visual content so as to identify a second visual content that is digitally configured to represent a second scene. The operations can include determining that native original metadata cannot be obtained for the first visual content, where the native original metadata includes information about the first scene digitally represented by the first visual content.

Abstract: Concepts and technologies disclosed herein are directed to forecasting expenditures to improve customer shopping experience in a store environment. According to one aspect disclosed herein, a device associated with a customer can present a shopping cart user interface and initiate a forecast spend module of a forecast spend application. The device can monitor an item detection module of the forecast spend application for a new item added to a physical shopping cart associated with the shopping cart user interface or otherwise marked for purchase. In response to the new item being added to the shopping cart or otherwise marked for purchase, the device can update, via the forecast spend module, a forecast spend field in the shopping cart user interface with a forecast spend value based upon a cost of the new item.

Abstract: Concepts and technologies directed to surrogate metadata aggregation for dynamic content assembly are disclosed. Embodiments can include a system that comprises a processor and a memory that stores computer-executable instructions that configure a processor to perform operations. The operations can include obtaining a first visual content from a digital data store, where the first visual content is configured to digitally represent a first scene. The operations can include performing image recognition on the first visual content so as to identify a second visual content that is digitally configured to represent a second scene. The operations can include determining that native original metadata cannot be obtained for the first visual content, where the native original metadata includes information about the first scene digitally represented by the first visual content.

Abstract: Concepts and technologies directed to surrogate metadata aggregation for dynamic content assembly are disclosed. Embodiments can include a system that comprises a processor and a memory that stores computer-executable instructions that configure a processor to perform operations. The operations can include obtaining a first visual content from a digital data store, where the first visual content is configured to digitally represent a first scene. The operations can include performing image recognition on the first visual content so as to identify a second visual content that is digitally configured to represent a second scene. The operations can include determining that native original metadata cannot be obtained for the first visual content, where the native original metadata includes information about the first scene digitally represented by the first visual content.

Abstract: Concepts and technologies disclosed herein are directed to forecasting expenditures to improve customer shopping experience in store environment. According to one aspect disclosed herein, a device associated with a customer can present a shopping cart user interface and initiate a forecast spend module of a forecast spend application. The device can monitor an item detection module of the forecast spend application for a new item added to a physical shopping cart associated with the shopping cart user interface or otherwise marked for purchase. In response to the new item being added to the shopping cart or otherwise marked for purchase, the device can update, via the forecast spend module, a forecast spend field in the shopping cart user interface with a forecast spend value based upon a cost of the new item.

Abstract: Concepts and technologies disclosed herein are directed to aspects of customer service based upon in-store field-of-view and analytics. According to one aspect disclosed herein, a store analytics system can collect user information associated with a plurality of users located within an environment. The store analytics system also can collect user device information associated with a plurality of user devices associated with the plurality of users. The store analytics system also can collect estimated fields-of-view associated with the plurality of users. The store analytics system can analyze the user information, the user device information, and the estimated fields-of-view to identify at least one commonality shared among at least two of the plurality of users. The store analytics system can create a logical group. The logical group can include the at least two users of the plurality of users that share the commonality.

Abstract: Concepts and technologies are disclosed herein for event-based security challenges. A computer can execute a security application. The computer can receive a request for authentication information associated with a user device. The computer can access event data corresponding to the user device. The computer can generate, based upon the event data, a challenge question and a response to the challenge question. The computer can provide data indicating the challenge question and the response to a requestor associated with the request.

Abstract: Concepts and technologies disclosed herein are directed to aspects of in-store field-of-view merchandising and analytics. According to one aspect disclosed herein, a system receives a message from a user device. The message can include an orientation of the user device and a location of the user device within an environment, such as a store. The system can obtain a potential field-of-view of a user associated with the user device. The system can determine, based upon the orientation, the location of the user device and the potential field-of-view of the user, an estimated field-of-view of the user. The system can query a database to look-up items located within the estimated field-of-view. The system can receive, in response to the query, a query response identifying an item located within the estimated field-of-view of the user within the environment.

Abstract: Concepts and technologies are disclosed herein for creating and using groups for task collaboration. A computing device can include a processor. The computing device can detect an opportunity to initiate collaboration on a task by a group of devices that includes a collaborating device. The computing device can create the group of devices, provide collaboration data to the collaborating device, and obtain input generated by the collaborating device based upon the collaboration data. The computing device can terminate the group.

Abstract: Concepts and technologies disclosed herein are directed to aspects of customer service based upon in-store field-of-view and analytics. According to one aspect disclosed herein, a store analytics system can collect user information associated with a plurality of users located within an environment. The store analytics system also can collect user device information associated with a plurality of user devices associated with the plurality of users. The store analytics system also can collect estimated fields-of-view associated with the plurality of users. The store analytics system can analyze the user information, the user device information, and the estimated fields-of-view to identify at least one commonality shared among at least two of the plurality of users. The store analytics system can create a logical group. The logical group can include the at least two users of the plurality of users that share the commonality.

Abstract: Concepts and technologies are disclosed herein for event-based security challenges. A computer can execute a security application. The computer can receive a request for authentication information associated with a user device. The computer can access event data corresponding to the user device. The computer can generate, based upon the event data, a challenge question and a response to the challenge question. The computer can provide data indicating the challenge question and the response to a requestor associated with the request.

Abstract: Concepts and technologies disclosed herein are directed to aspects of customer service based upon in-store field-of-view and analytics. According to one aspect disclosed herein, a store analytics system can collect user information associated with a plurality of users located within an environment. The store analytics system also can collect user device information associated with a plurality of user devices associated with the plurality of users. The store analytics system also can collect estimated fields-of-view associated with the plurality of users. The store analytics system can analyze the user information, the user device information, and the estimated fields-of-view to identify at least one commonality shared among at least two of the plurality of users. The store analytics system can create a logical group. The logical group can include the at least two users of the plurality of users that share the commonality.

Abstract: Concepts and technologies are described herein that involve non-native device authentication. According to one aspect disclosed herein, a method can include receiving an authentication credential at a computing device from an authorizer. The computing device can be non-native to the authorizer and native to an authorizee that the authorizer is attempting to provide authorization for access to content associated with the authorizer. The method can also include generating an authentication request directed to an authentication system. The authentication request can include the authentication credential. The method can also include sending the authentication request to the authentication system. In response to the authentication request, the computing system can receive an indication that the authorizer is authenticated to authorize the authorizee for access to the content associated with the authorizer. The method can also include accessing, by the computing device, the content associated with the authorizer.

Abstract: Concepts and technologies are disclosed herein for event-based security challenges. A computer can execute a security application. The computer can receive a request for authentication information associated with a user device. The computer can access event data corresponding to the user device. The computer can generate, based upon the event data, a challenge question and a response to the challenge question. The computer can provide data indicating the challenge question and the response to a requestor associated with the request.

Abstract: Concepts and technologies are disclosed herein for creating and using groups for task collaboration. A computing device can include a processor. The computing device can detect an opportunity to initiate collaboration on a task by a group of devices that includes a collaborating device. The computing device can create the group of devices, provide collaboration data to the collaborating device, and obtain input generated by the collaborating device based upon the collaboration data. The computing device can terminate the group.

Abstract: Concepts and technologies are disclosed herein for creating and using groups for task collaboration. A computing device can include a processor. The computing device can detect an opportunity to initiate collaboration on a task by a group of devices that includes a collaborating device. The computing device can create the group of devices, provide collaboration data to the collaborating device, and obtain input generated by the collaborating device based upon the collaboration data. The computing device can terminate the group.

Abstract: Concepts and technologies disclosed herein are directed to aspects of in-store field-of-view merchandising and analytics. According to one aspect disclosed herein, a system receives a message from a user device. The message can include an orientation of the user device and a location of the user device within an environment, such as a store. The system can obtain a potential field-of-view of a user associated with the user device. The system can determine, based upon the orientation, the location of the user device and the potential field-of-view of the user, an estimated field-of-view of the user. The system can query a database to look-up items located within the estimated field-of-view. The system can receive, in response to the query, a query response identifying an item located within the estimated field-of-view of the user within the environment.

Abstract: A method includes coordinating delivery by a selected delivery agent to a delivery recipient. A geographical receiving location for a delivery recipient is determined. A delivery agent, of a plurality of potential delivery agents, is identified and selected that is capable of delivering a specific product to the delivery recipient at the geographical location for the delivery recipient, in which the identifying includes analyzing planned geographical routes for each of the plurality of potential delivery agents to determine the delivery agent. A network communications address of the delivery recipient is determined and an electronic communication exchange is established between an entity responsible for providing the product to the delivery recipient and the network communications address of the delivery recipient. The specific product is assigned for delivery to the delivery recipient based on the communications exchange.

Abstract: Concepts and technologies disclosed herein are directed to aspects of in-store field-of-view merchandising and analytics. According to one aspect disclosed herein, a system receives a message from a user device. The message can include an orientation of the user device and a location of the user device within an environment, such as a store. The system can obtain a potential field-of-view of a user associated with the user device. The system can determine, based upon the orientation, the location of the user device and the potential field-of-view of the user, an estimated field-of-view of the user. The system can query a database to look-up items located within the estimated field-of-view. The system can receive, in response to the query, a query response identifying an item located within the estimated field-of-view of the user within the environment.