An electronic device that includes a display screen and circuitry is provided. The display screen displays map data and a user interface (UI) element. The circuitry receives a first user input, via the UI element. The first user input indicates a geographical region on the displayed map data. The circuitry extracts geo-location information from vehicle data associated with a vehicle. The circuitry further controls a communication of a first portion of the vehicle data with a server based on a first geo-location in the extracted geo-location information of the vehicle data and the indicated geographical region. The first portion of the vehicle data corresponds to the first geo-location.

Provided are a computer program product, system, and method for generating constraints based on reported crop arrivals to marketplaces and remote sensed data to estimate farm yields of farm fields. A total arrival quantity constraint for a marketplace is generated comprising a function of a reported arrival of crops at a marketplace and an estimated arrival to the marketplace comprising a sum of farm yields for the farm fields, wherein the farm yields comprise variables to optimize. Sensed data of the farm fields is used to determine relationships of the farm yields for the farm fields. Comparative farm yield constraints are generated comprising relationships of the farm yields for different pairs of farms. A constraint optimization problem is solved based on the total arrival quantity constraint and comparative farm yield constraints to calculate the farm yields of the farm fields.

A system for training a bidding model comprising: a plurality of tactics stored on at least one database; a plurality of hyperparameters; in response to an available inventory from a publisher relayed through a real time bid server, computing a bid on the available inventory; sending the bid to the real time bid server; receiving an auction result in response to the bid; calculating a plurality of rewards based on the auction result and the tactics; calculate a plurality of q values based on the rewards; calculate a plurality of losses; backpropogating the losses through the bidding model.

A computer-implemented system comprising a processor for an electronic data exchange using Internet to facilitate request for bids from prospective restaurant customers which become binding upon restaurants when the prospective customer honors, in full, his conditional promises to a restaurant. The processor receives offer from the restaurant's system including a minimum dollar amount, a range of time for which the offer is valid, and a customer discount associated with the offer, which are matched with the received RFB from the consumer's device, the RFB including a geographic location of restaurant, a minimum amount of money to spend and a range of time at which the consumer will promise to honor a deal. The processor searches the restaurant offers database to match one or more restaurant offers with the RFB criteria and serves said identified one or more restaurant offers to the consumer for acceptance.

An exemplary non-limiting embodiment of an economic development and collaboration system, which enables individuals within a community to efficiently identify and express their interests in one or more economic propositions, is disclosed herein. The economic development and collaboration system comprises a software application which is configured to allow users to uniquely interface with the one or more economic propositions. The system allows for its users to efficiently identify and express support or disapproval of one or more economic propositions. A variety of engagement mechanisms are provided by the economic development and collaboration system to assist users in democratizing their interests. The system allows for a variety of forms of financial support of each economic proposition and provides valuable statistical data which may be utilized by entrepreneurs, business owners, developers, lenders, investors, or public officials when considering whether to implement or support the implementation of one or more economic propositions.

A method of optimizing an offer value to be offered to a selected group of consumers includes selecting a series of products, wherein each are serialized unique code marked; selecting a target group of consumers from a consumer database, each consumer with a registered consumer profile in the consumer database, the selecting based on a set of criteria; selecting a first subgroup of consumers from the target group of consumers; determining an initial offer value of the uniquely code marked product to be presented to the initial first subgroup of consumers; distributing (offering) the initial offer value to the selected initial first subgroup of consumers; a number of the selected initial first subgroup of consumers accepting the offer; associating the code of the uniquely code marked product to the acceptance of offer to the consumer profile of each the accepting consumer in the first subgroup of consumers; summing the number of accepted uniquely code marked products to a first uptake value as a function of the initial offer value; registering the initial offer value and the first uptake value in order to calculate a first initial profit value; repeating, for a number of second, third, . . . time, the following steps: selecting a second, third, . . . subgroup of consumers from the target group of consumers; determining a second (third, . . . ) offer value of the uniquely code marked product to be presented to the second, third, . . . subgroup of consumers, being different from the first offer value; distributing (offering) the second (third, . . . ) offer value to the selected second, third, . . . subgroup of consumers; a number of the selected second group of consumers accepting the second, third, . . . offer; associating the code of the uniquely code marked product to the accepted second (third, . . . ) offer value to the consumer profile of each the accepting consumer; summing the second (third, . . . ) number of accepted uniquely code marked products to a second (third, . . . ) uptake value as a function of the second (third, . . . ) offer value; registering the second (third, . . . ) offer value and the second (third, . . . ) uptake value in order to calculate a second, (third, . . . ) initial profit value; thus establishing a set of uptake values as a function of offer values, and their calculated or estimated corresponding profit values; based on these data points, establishing a relationship of profit as a function of offer value; selecting from the relationship a near-optimal offer value giving a near-optimal profit; distributing (offering) the optimal offer value to a large part of or all of the selected target group of consumers.

Methods and apparatus to generate audience metrics using third-party privacy-protected cloud environments. An example apparatus includes at least one memory, programmable circuitry, and instructions to cause the programmable circuitry to generate a first demographic correction model based on a first matrix, the first matrix including first data indicative of user accesses to media, the first matrix associated with a first demographic, generate a second demographic correction model based on a second matrix, the second matrix including second data indicative of user accesses to the media, the second matrix associated with a second demographic, and generate predicted demographics of a user associated with the user accesses based on the first demographic correction model and the second demographic correction model, the predicted demographics including the first demographic and the second demographic.

Systems and methods for on demand local commerce are described. One example embodiment includes a device gathering location information and product interest associated with clients and client devices. The system may use location information in determining that the first plurality of client devices are within a first geographic area during a first time period, and may further use the interest information in calculating an interest level for a first product. A threshold may be identified and used in determining that the interest level for the first product exceeds the threshold. When the calculated interest level exceeds the threshold, a local commerce action is initiated. In various embodiments, the local commerce action may be a live on demand auction at a particular location, an offer associated with a geofenced area, a sales location recommendation to a merchant, or any other such local commerce action.

Techniques are disclosed utilizing cognitive computing to improve banking experiences. A user's financial account(s) may be monitored to predict when a surplus of funds is unnecessarily present and for how long this will likely be the case. Once this is determined, techniques include automatically drafting funds from the account to another account having a higher interest rate where the funds may accrue more interest. The techniques also include predicting when an overdraft may occur and taking appropriate action when such a prediction is made. Predictions may be based upon different weighted inputs used in accordance with a predictive modeling system, which may attempt to predict for a particular user, location, and retailer, whether the user will spend an anticipated amount in excess of the user's current balance. If so, passive (e.g., notifications) and active (e.g., transferring cover funds) actions may be performed.

A system may receive information indicating a service area of a shared mobility service, calculate information indicating one or more of risk or revenue associated with the provision of shared mobility services in the service area, determine an adjusted service area, wherein the adjusted service area is associated with one or more of a reduction in risk or an increase in revenue, and transmit information indicating the adjusted service area to a device associated with the shared mobility service.