There are provided systems and methods for location-based embedded patterns for vehicle detection and data processing. A user's device, which may be connected to or associated with a vehicle may include a directional camera capable of capturing images in a direction for a directional perspective of the vehicle, such as a front, side, or back. The image captured may have an embedded pattern or code that is associated with data that may decoded or retrievable using the embedded pattern. The vehicle's device may utilize the code to determine the data and may activate a process for an application based on the data. In some embodiments, the data may also be loaded to the process or may cause the process to load or retrieve other data. The vehicle's device may utilize the process based on a location of the vehicle, as well as services provided at the location.

A system and method for card control includes a card control computing system configured to enforce a card control rule based upon transactions made with a payment card. The card control computing system includes a memory unit configured to store information associated with a card control dashboard, and a processing unit configured to cause presentation of the card control dashboard via a display associated with a remote computing device, such that the card control dashboard is associated with the payment card and the card control rule. The card control dashboard includes a user interface. The processing unit is further configured to receive an input via the user interface to activate or deactivate one or more features associated with the card control rule, and trigger the card control rule based upon the one or more features that are activated or deactivated.

Embodiments provide methods and systems for facilitating scheduled payment transactions to users via an application provided by the server system, the application available on the user device. The method performed by the server system includes receiving a transaction request message from the user device, the transaction request message includes scheduled transaction instruction provided by the user in natural language format. The method includes authenticating the user based on a plurality of user authentication factors received from the user at pre-defined time intervals. In an embodiment, the server system is configured to train a data model using ML algorithms by learning the plurality of user authentication factors based on which the user is automatically authenticated by the server system. Upon successful authentication, the method includes parsing the transaction request message to determine a scheduled transaction instruction. The method includes facilitating, processing of the scheduled transaction based on the scheduled transaction instruction.

Implementations of a computer implemented method and system to transform transportation and freight capacity units with two waypoints or a destination waypoint or a series sequence of waypoints into multi-modal objects which are tradable as commodities such as wheat, oil, corn, stocks, foreign exchange, fixed income or other forward or securitized markets. The present disclosed invention relates to combining the concepts of objected oriented programming and navigation systems and social networking, price-time priorities queues, replacement costs, termination valuations, financial markets, commodity structuring transformation and transportation and freight as a fungible asset class or tradable market.

Methods and apparatus for providing authentication of information of a user are described. Upon validation of this information, a first hash function is applied to the user's information to create a hash. A public attest key is generated by combining the hash of the user's information with one or more public keys. An attestation address is generated based on the public attest key. A signed transaction which includes the attest key is communicated for storage in a centralized or distributed ledger at the attestation address.

A computer-implemented method for real-time fraudulent activity verification, comprising: displaying, on a user device, a first notification which prompts entry of a user-selected geographic area, the user-selected geographic area defining a valid region for processing of transactions associated with a user; receiving, by the user device, user-defined geographic data, the user-defined geographic data specifying at least one user-selected geographic area and defining the valid region for processing of transactions; transmitting, by the user device, the user-defined geographic data along with user data, the user data identifying the user device or the user; receiving, the user device, a second notification, the second notification being an authentication request message received in response to a proposed transaction associated with a user identifier related to the user; displaying, by the user device, the second notification; receiving, by the user device, user-provided authentication data; and transmitting, by the user device, the user-provided authentication data.

A system can visually track which items in a store are selected for purchase by a shopper. The system can form a virtual shopping cart by analyzing multiple images, over time, to determine which purchasable items are located with the shopper, such as in a physical shopping cart, in a basket, or held by the shopper. By analyzing multiple images, over time, the system can account for items misidentified in one or more images, or fully or partially obscured in one or more images as the shopper traverses the store. Alternatively, the system can form a virtual shopping cart by analyzing instances in which a purchasable item is removed from a shelf or placed on a shelf. Items removed from, but not returned to, a shelf can be considered to be selected for purchase. The system can include a frictionless checkout that charges the shopper for the selected items.

A device may receive customer data, and store the customer data in a secure memory device of the device. The device may implement a backup mode in which the device utilizes the customer data to authorize requests based on determining that the device lacks a network connection. The device may receive, when the device is in the backup mode, a request for currency that includes authentication information. The device, while in the backup mode, may authorize the request for currency based on comparing the authentication information and the customer data. The device may dispense currency based on a result of comparing the authentication information and the customer data. The device may store transaction data associated with dispensing of the currency to permit the transaction data to be transmitted when the network connection is restored.

A processor may detect a transaction made using a point of sale system. The processor may determine that the transaction indicates a smart device is not in use. The processor may send a command causing the smart device to operate in an away mode.

Techniques are provided for identifying anomalies in an Internet of Things (IoT) activity profile of a user using an analytic engine. An exemplary method comprises obtaining data from a plurality of IoT devices of a user, wherein at least one IoT device comprises an agent device that performs an action on behalf of the user; applying the obtained data to a feature engineering module to convert the obtained data into time-series features that capture behavior and/or characteristics of an IoT environment of the user, and applying the time-series features to an analytic engine comprising a multi-variate anomaly detection method that learns one or more patterns in the IoT activity profile of the user for a normal state and identifies an anomaly with respect to an action performed by the agent device based on a health score indicating a deviation from the learned patterns.