Abstract: Systems, apparatuses, methods, and computer program products are disclosed for translating control instructions for a machine interface. An example method includes identifying a machine based on a machine identifier. The example method further includes selecting a machine-readable interface based on the machine identifier. The example method further includes generating control data comprising instructions to cause an executable action by the machine. The example method further includes causing execution of the control data by the machine. The example method may further include contacting an NFC sensor associated with the machine. The example method may further include scanning an indicia that is within a distance of the machine. The example method may further include generating request data indicating a user request to complete the executable action by the machine.

Abstract: Disclosed are example methods, systems, and devices that allow for secure data processing using data packages generated by edge devices. A computing device can generate a biometric signature from a scan of a physical feature of a user and encrypt user data based on the biometric signature and a device identifier to produce encrypted user data decryptable with a first digital key. The first digital key can be transmitted to a first computing system to receive a security token indicating validity of at least part of the user data. The encrypted user data and security token can be stored in a data package such that alterations invalidate the token. A second digital key corresponding to the data package can be generated and transmitted with the data package to a second computing system to provide a service.

Abstract: Disclosed are example methods, systems, and devices that allow for secure data processing using data packages generated by edge devices. The techniques include generating a biometric signature using information captured by a computing device, and encrypting user data obtained via the computing device using the biometric signature and a device identifier of the computing device. A security token can be generated and utilized by the computing device to generate a data package, which is configured such that any change to the data package would cause a validation process of the data package using the security token to fail. The data package can be encrypted using various digital keys and provided to secondary computing systems.

Abstract: A method includes: generating a dataset based on a first digital identity profile of a first entity and a second digital identity profile of a second entity; inputting the dataset to an artificial intelligence (AI) agent to generate a linkage definition and a set of activation elements; determining that at least one activation element of the set of activation elements has been triggered; in response to determining that the at least one activation element has been triggered, generating one or more security access tokens based on the linkage definition, the one or more security access tokens indicating that access to the one or more assets is granted; and transmitting the one or more security access tokens to at least one of a first device identified in the first digital identity profile or a second device identified in the second digital identity profile.

Abstract: Disclosed are example methods, systems, and devices that allow for secure digital authorization via generated datasets. The techniques include receiving a first dataset of a first user and a second dataset of a second user and generating a first set of identity elements and a second set of identity elements based on the first dataset and the second dataset, respectively. A linkage definition can be generated based on the first and second datasets, which can be associated with a set of activation elements. The techniques include determining that a set of inputs satisfy one or more of the set of activation elements and, in response, generating a set of security access tokens based on the linkage condition. The security access tokens can be transmitted to a computing device upon analyzing and verifying biometric data received from that computing device.

Abstract: Disclosed are example methods, systems, and devices that allow for executing machine-learning models for real-time and secure analysis of digital metrics. The techniques include generating metrics for identity elements stored in digital profiles of users. A subset of profiles can be identified that have metrics that fall below a predetermined thresholds, with which a training dataset can be generated. Machine-learning models can be executed over the training dataset to train an artificial intelligence agent that receives digital profiles as input and outputs translational elements corresponding to identity elements in the digital profiles. After training, additional profiles can be input to the machine-learning models of the artificial intelligence agent to identify a second subset of digital profiles with corresponding metrics. Electronic messages corresponding to the second subset can be generated and transmitted to one or more computing devices identified in the second subset of digital profiles.

Abstract: Disclosed are example methods, systems, and devices for sensor data processing for monitoring devices. These techniques include receiving scan data from a computing device that corresponds to a scan by an imaging device and analyzing the scan data to determine that the scan data corresponds to a manufactured article. An indication can be transmitted with a request for audiovisual data corresponding to an operation of the manufactured article, and the audiovisual data can be received from an imaging device or a microphone of the computing device. A sound sample corresponding to the operation of the manufactured article is extracted, and a status metric for the article is generated based on a comparison of the sound sample to a sound signature in an identity profile of the manufactured article. The status of the manufactured article can then be determined.

Abstract: Disclosed are example methods, systems, and devices that allow for secure generation of authentication datasets from network activity. The techniques include accessing secured data sources to generate a first dataset of secured data, and extracting information from one or more unsecured data sources to generate a second dataset comprising a second dataset. A third set of data elements can be generated from the first and second datasets, and may be utilized to authenticate credentials that can be utilized to access secured data via a network. The techniques can transmit indications that credentials are invalid if the credentials fail to satisfy aspects of the third dataset.

Abstract: Disclosed are example methods, systems, and devices that allow for executing machine-learning models for real-time and secure analysis of digital metrics. The techniques include generating metrics for identity elements stored in digital profiles of users. A subset of profiles can be identified that have metrics that fall below a predetermined thresholds, with which a training dataset can be generated. Machine-learning models can be executed over the training dataset to train an artificial intelligence agent that receives digital profiles as input and outputs translational elements corresponding to identity elements in the digital profiles. After training, additional profiles can be input to the machine-learning models of the artificial intelligence agent to identify a second subset of digital profiles with corresponding metrics. Electronic messages corresponding to the second subset can be generated and transmitted to one or more computing devices identified in the second subset of digital profiles.

Abstract: Disclosed are example methods, systems, and devices that allow for secure generation of authentication datasets from network activity. The techniques include accessing secured data sources to generate a first dataset of secured data, and extracting information from one or more unsecured data sources to generate a second dataset comprising a second dataset. A third set of data elements can be generated from the first and second datasets, and may be utilized to authenticate credentials that can be utilized to access secured data via a network. The techniques can transmit indications that credentials are invalid if the credentials fail to satisfy aspects of the third dataset.

Abstract: Disclosed are example methods, systems, and devices that allow for secure digital authorization via generated datasets. The techniques include receiving a first dataset of a first user and a second dataset of a second user and generating a first set of identity elements and a second set of identity elements based on the first dataset and the second dataset, respectively. A linkage definition can be generated based on the first and second datasets, which can be associated with a set of activation elements. The techniques include determining that a set of inputs satisfy one or more of the set of activation elements and, in response, generating a set of security access tokens based on the linkage condition. The security access tokens can be transmitted to a computing device upon analyzing and verifying biometric data received from that computing device.

Abstract: Disclosed are example methods, systems, and devices that allow for secure multi-verification of biometric data in a distributed computing environment. The techniques include receiving a request to grant authorization to a second user. The request can include biometric data of the first user and second user. An authorization token can be generated based on the request, which can be transmitted to a second computing device of the second user. A second request can be received from a third computing device that includes the authorization token and third biometric data. The second request can be verified based on the authorization token, the third biometric data, and provenance data, and an indication that the grant of authorization to the second user is verified can be transmitted to the first, second, or third computing devices.

Abstract: A low cost, light weight, high performance phase shifter mounting structure which allows high density packaging of phase control modules for phased array antennas. The mounting structure is a bimetallic sandwich design in the shape of an I-beam having a top flange for mating to radiating elements, a bottom flange for mating to a feed network, and a center web for mounting phase control modules. The I-beam is formed from a single piece of laminated stock comprising an outer layer of aluminum and a core layer of titanium forming an anisotropic thermal expansion composite material. The titanium center web matches the coefficient of thermal expansion of the typical ferrite, MIC, or MMIC phase shifter and driver circuits. The aluminum flange material allows easy machining of microwave transitions at each end of the I-beam and matches the expansion of typical radiating element structure and feed networks.