Abstract: Methods, systems, and devices are described. Indoor wayfinding may be performed using a set of layers overlayed on a map, such as a site map of the surrounding environment of a building, using a combination of static and dynamic images. For example, a user device may transmit a request to a server for a route to a desired location of a floor of a building. In some cases, the server may, in response to the request, generate the route using a set of map layers that includes a static image of the site, a static image of a floor plan of the floor housing the location, a vector image of features such as rooms and offices of the floor that includes the desired location, and a vector image of a route from a starting location of the floor, such as an entrance or elevator, and the desired location.

Abstract: A system may deliver personalized content to a user. The system may create a user persona based on demographic information and stored clickstream data of the user. The system may learn which functionalities the user typically uses on a webpage, and the system may create a personalized version of the webpage for the user.

Abstract: Methods, systems, and devices to support techniques for dynamically and securely managing user rewards are described. A system may issue digital assets that include a user-specific code to a user, and the system may store the digital assets on a distributed ledger (e.g., in a digital wallet associated with the user). The system may issue one or more digital assets to the user in response to determining that the user has performed one or more actions corresponding to the one or more digital assets. In some examples, each digital asset may include a same user-specific code, such as a quick response (QR) code, embedded in a respective image associated with each digital asset. The user may present an owned digital asset to a third-party vendor, and the third-party vendor may scan the user-specific code associated with the digital asset to identify and provide rewards available to the user.

Abstract: Methods, systems, and devices are described. A virtual environment may perform a multi-step authentication process to verify identities of both a user and a representative of an organization interacting within the virtual environment. Within the virtual environment, the representative may perform a first verification process to verify the identity of the user and the representative by validating the user's account information and an identifier of the representative against a distributed ledger. Upon success of the first verification process, the representative may initiate a second verification process. As part of the second verification process, the distributed ledger may provide one or more questions posed to the user by the representative, which may be answered within the virtual environment, external to the virtual environment, or both. Upon the user successfully answering the one or more questions, the virtual environment may display an indication that the user and the representative are verified.

Abstract: A system may deliver personalized content to a user. The system may create a user persona based on demographic information and stored clickstream data of the user. The system may learn which functionalities the user typically uses on a webpage, and the system may create a personalized version of the webpage for the user.

Abstract: Methods, systems, and devices are described. Indoor wayfinding may be performed using a set of layers overlayed on a map, such as a site map of the surrounding environment of a building, using a combination of static and dynamic images. For example, a user device may transmit a request to a server for a route to a desired location of a floor of a building. In some cases, the server may, in response to the request, generate the route using a set of map layers that includes a static image of the site, a static image of a floor plan of the floor housing the location, a vector image of features such as rooms and offices of the floor that includes the desired location, and a vector image of a route from a starting location of the floor, such as an entrance or elevator, and the desired location.

Abstract: A blockchain-based loyalty point system that comprises a host computing device for interfacing with authorized devices and loyalty partner websites in a loyalty point network. In one example, the loyalty point network includes a blockchain network and a host computing device. The host computing device is configured to receive a registration request from a client device for access to the loyalty point network. The host computing device causes a registration proposal for the client device to be written to the blockchain network and receives a point adjustment request from a loyalty partner website. The host computing device executes a smart contract in response to receiving the point adjustment request from the loyalty partner website, and the smart contract is executed to adjust the account balance of the customer account based at least in part on the point adjustment request.

Abstract: A blockchain-based loyalty point system may include a blockchain API host that receives a request to transfer an amount of loyalty points from a first customer account to a second customer account. The system may validate the request by performing a cryptographic operation on the request using a public key associated with the first customer account. The system may also propagate a proposal to consensus participants for writing to a blockchain, wherein the proposal comprises the first customer account, the second customer account, and the amount of loyalty points. The system may also receive an exchange request from a loyalty wallet associated with the second customer account, validate the exchange request by performing the cryptographic operation on the exchange request using a public key, and propagate an exchange proposal to the consensus participants for writing to the blockchain.

Abstract: The system may validate a data source having a structured format and a grammar that includes tags. The system may identify a tag in the grammar. The system may parse the data source to extract attributes and/or values associated with the tags in response to successful validation. The system may also write the attributes and/or values to an output file separated by a preselected delimiter. A configuration file may identify the grammar, the preselected delimiter, and/or the data source. The data source may be in an XML format or a JSON format. The system may generate execution ready code in response to the validating the data source and the grammar. The output file may be a load ready file for ingestion into a big data storage format. The tag may include a parent tag and a sub tag corresponding to a hierarchy in the data source.

Abstract: A system receives a source and a metadata layer that describes the source. The source may comprise source records with fields containing source data, and the metadata layer may include metadata comprising at least one of a field data type, a field data length, a field description, or a record length. The processor may further validate the metadata layer against the source and write results to a log. The processor may further be configured for transforming the source records into transformed records for a load ready file. The processor may further balance a number of records in the source against a number of transformed records in the load ready file to generate a transformation failure rate.

Abstract: A blockchain-based loyalty point system may include a blockchain API host that receives a request to transfer an amount of loyalty points from a first customer account to a second customer account. The system may validate the request by performing a cryptographic operation on the request using a public key associated with the first customer account. The system may also propagate a proposal to consensus participants for writing to a blockchain, wherein the proposal comprises the first customer account, the second customer account, and the amount of loyalty points. The system may also receive an exchange request from a loyalty wallet associated with the second customer account, validate the exchange request by performing the cryptographic operation on the exchange request using a public key, and propagate an exchange proposal to the consensus participants for writing to the blockchain.

Abstract: A system may deliver personalized content to a user. The system may create a user persona based on demographic information and stored clickstream data of the user. The system may learn which functionalities the user typically uses on a webpage, and the system may create a personalized version of the webpage for the user.

Abstract: The system may validate a data source having a structured format and a grammar that includes tags. The system may identify a tag in the grammar. The system may parse the data source to extract attributes and/or values associated with the tags in response to successful validation. The system may also write the attributes and/or values to an output file separated by a preselected delimiter. A configuration file may identify the grammar, the preselected delimiter, and/or the data source. The data source may be in an XML format or a JSON format. The system may generate execution ready code in response to the validating the data source and the grammar. The output file may be a load ready file for ingestion into a big data storage format. The tag may include a parent tag and a sub tag corresponding to a hierarchy in the data source.

Abstract: A system receives a source and a metadata layer that describes the source. The source may comprise source records with fields containing source data, and the metadata layer may include metadata comprising at least one of a field data type, a field data length, a field description, or a record length. The processor may further validate the metadata layer against the source and write results to a log. The processor may further be configured for transforming the source records into transformed records for a load ready file. The processor may further balance a number of records in the source against a number of transformed records in the load ready file to generate a transformation failure rate.