A computer-based method for collecting digital wallet data from a digital wallet transaction initiated by a user is provided. The method includes receiving registration data for a user in response to the user registering into a digital wallet application, wherein the registration data includes demographic data and device registration data including a device identifier used for identifying the user device when in communication with another computing device. The method also includes storing the registration data within at least one memory device and receiving digital wallet data as part of a digital wallet transaction initiated by the user using the digital wallet application on the user device, wherein the digital wallet data includes transaction data, device communication data, and biometric data. The method further includes comparing the digital wallet data to the registration data and linking the digital wallet data within the at least one memory device to the registration data.

The discussion relates to context-aware environments. One example can include inwardly-facing cameras positioned around a periphery of an environment that defines a volume. The example can also include sensors positioned relative to the volume and configured to communicate with a user device in the volume. The example can also include an ambient perception component configured to track user locations in the volume and to detect user gestures relative to objects in the volume, and responsive to receiving a query from the user's device, to supplement the query with information derived from the objects.

A method, system, and computer program product for predicting future transactions may obtain merchant data associated with a merchant; determine a geographic location associated with the merchant based on the merchant data; determine one or more other merchants within a first threshold distance of the geographic location; obtain transaction data associated with the one or more other merchants and the merchant; and predict, based on the transaction data, at least one of a future number of transactions for the merchant in a future time period and a future transaction amount for the merchant in the future time period.

An apparatus 10, and system 70 may be embodied as an article 70 or method implementing transactions between a central or “core” application 72, a fulfillment application 96 at a venue, and a wireless communication application 84, 86 hosted on a computing device 10, such as a cell phone, of an attendee at an event at that venue. Customers may sign up online, through various types of web applications 88 or dedicated applications 92, to receive information, such as menus, catalogs, or the like of available products to be at the event. The core application 72 may manage a database 74 of records of customers, products, and fulfilment locations, and may send to fulfilment locations instructions to dispatch “runners” to deliver products to seat locations of customers ordering through wireless computer devices 12 at a venue.

Computer-implemented methods for identifying or assessing any type of risk and/or opportunity that may arise can include either, alone or in combination, band pass filtering, principal component analysis, random matrix theory analysis, synchronization analysis, and early-warning detection. Each technique can also be viewed as a process that takes a set of inputs and converts it to a set of outputs. These outputs can be used as inputs for a subsequent process or the outputs may be directly actionable for formulating certain economic predictions to make certain decisions.

A method, system, and computer program product for managing resources by obtaining a high spatial resolution estimate of behavior adoption are described. The method includes obtaining a low-resolution estimate with a fixed geographic scale, selecting a sample of customers based on the low-resolution estimate, implementing a statistical model to obtain relative probability of adoption of the behavior by each of the sample of customers, and generating a weighted random realization from the sample of customers, the weighted random realization being weighted based on the relative probability of adoption. The method includes iteratively implementing the selecting the sample of customers, the implementing the statistical model, and the generating the weighted random realization to obtain a set of the weighted random realizations, and obtaining the high spatial resolution estimate, providing greater resolution than the low-resolution estimate at a location of interest, based on the set of the weighted random realizations.

The present teaching relates to method, system, and medium for determining audience clusters to be assigned to an advertisement exposure opportunity. A plurality of advertisement exposure opportunities are obtained, wherein each of the plurality of advertisement exposure opportunities is to be used for placing an advertisement. For each of the plurality of advertisement exposure opportunities, a plurality of audience clusters are generated based on at least one criterion associated with the advertisement exposure opportunity. The plurality of audience clusters are ranked based on at least one ranking criterion, and ordered audience clusters are generated based on the ranking. The ordered audience clusters associated with the plurality of advertisement exposure opportunities in response to an event are updated, wherein the ordered audience clusters for each of the plurality of advertisement exposure opportunities are generated prior to receiving a request for placing the advertisement.

Intermodal vehicles may be loaded with items and an aerial vehicle, and directed to travel to areas where demand for the items is known or anticipated. The intermodal vehicles may be coupled to locomotives, container ships, road tractors or other vehicles, and equipped with systems for loading one or more items onto the aerial vehicle, and for launching or retrieving the aerial vehicle while the intermodal vehicles are in motion. The areas where the demand is known or anticipated may be identified on any basis, including but not limited to past histories of purchases or deliveries to such areas, or events that are scheduled to occur in such areas. Additionally, intermodal vehicles may be loaded with replacement parts and/or inspection equipment, and configured to conduct repairs, servicing operations or inspections on aerial vehicles within the intermodal vehicles, while the intermodal vehicles are in motion.

Predicting transportation demand in a predetermined area, based on estimating a present mobility demand and based on user group preferences. Generated transportation need requests include at least a time stamp, a pick-up coordinate, a drop-off coordinate, a user group indication, a pick-up venue category based on the pick-up coordinate, and a drop-off venue category based on the drop-off coordinate. A signal indicative of the transportation need request is provided.

Process for monitoring the audience in a targeted region, the process providing for capturing at least one image of at least one person located in the targeted region, analyzing the image for determining at least one information about the person, registering the determined information in an audience database, and the process further providing for identifying the eventual presence of an exclusion tag related to the person, so as to provide an exclusion mark for the monitoring of the person in the case of such a presence.