Abstract: Information-security LoRa-wave sensing is used to protect ATMs with LoRa modulator with spread-spectrum modulation techniques and/or transparent laser-guided systems 3D image generation to scan/monitor ATM card slots and ATM keypads for skimmers, fake keypads, etc. Sensor(s) with a DCNN/StNet-based algorithm are trained on 3D dimensions for card slot and keypad. Normal vs. detected constant weight of the keypad as well as weight distribution when keys are depressed are detected. Normal vs. disrupted signals based on the foregoing are observed and used to detect unauthorized objects. NB-IoT LoRa-waves initiate an alarm process. Additional features, functionality, and details are disclosed.

Abstract: Device information may be obtained using LoRaWAN communications. A device information request may be generated and transmitted by a user device and include request parameters such as a device type for which information is desired, a type of information requested, a geographic range for the request, and the like and/or combinations thereof. Device information requests may also be propagated or repeated by intermediary devices to achieve the desired request range. Accordingly, a recipient device of the original request may propagate or repeat, using LoRaWAN, a request signal if it determines that the request range has not been met. If the request range has been met, the recipient device might not repeat the request.

Abstract: Aspects of the disclosure relate to NFT exchanges. A computing platform may generate a plurality of F-NFTs including F-NFT identifiers that configure the F-NFTs for end-to-end tracking. The computing platform may extract, from a voice communication, information of a request to transfer an F-NFT. The computing platform may generate, based on the information of the request, a text file. The computing platform may input, into a GPT-4 algorithm, the text file to produce a F-NFT contract identifying the F-NFT, the transferor of the F-NFT, and a transferee of the F-NFT. The computing platform may send, to an NFT exchange platform, the F-NFT contract, which may cause the NFT exchange platform to transfer custody of the F-NFT from an account of the transferor at a first institution to an account of the transferee at a second institution.

Abstract: Device information may be obtained using LoRaWAN communications. A device information request may be generated and transmitted by a user device and include request parameters such as a device type for which information is desired, a type of information requested, a geographic range for the request, and the like and/or combinations thereof. Device information requests may also be propagated or repeated by intermediary devices to achieve the desired request range. Accordingly, a recipient device of the original request may propagate or repeat, using LoRaWAN, a request signal if it determines that the request range has not been met. If the request range has been met, the recipient device might not repeat the request.

Abstract: Information-security LoRa-wave sensing is used to protect ATMs with LoRa modulator with spread-spectrum modulation techniques and/or transparent laser-guided systems 3D image generation to scan/monitor ATM card slots and ATM keypads for skimmers, fake keypads, etc. Sensor(s) with a DCNN/StNet-based algorithm are trained on 3D dimensions for card slot and keypad. Normal vs. detected constant weight of the keypad as well as weight distribution when keys are depressed are detected. Normal vs. disrupted signals based on the foregoing are observed and used to detect unauthorized objects. NB-IoT LoRa-waves initiate an alarm process. Additional features, functionality, and details are disclosed.

Abstract: Transactions may be performed using a mobile device such as a user-wearable device using LoRaWAN protocol to minimize power consumption while maximizing communication range. Transaction information may be stored in the user-wearable device and transmitted to a transaction processing device using LoRaWAN communications. Transaction information may include user-specific information, payment information, merchant information, product information, user preference information and the like. In some instances, the only communication interface (or wireless communication interface) provided in the mobile device is a LoRaWAN communication interface.

Abstract: Systems, computer program products, and methods are described herein for monitoring and removing drift in machine learning models. The present disclosure is configured to receive, from one or more control automation modules, a data stream, wherein the data stream comprises data associated with the one or more control automation modules; transmit the data stream to a gauging and monitoring module; determine whether the data stream matches a declarative mapping protocol; determine one or more deviation instances in an instance in which the data stream does not match the declarative mapping protocol; determine one or more prescriptive actions for the one or more deviation instances; and implement, using an intelligence restoration module, the one or more prescriptive actions on the one or more control automation modules.

Abstract: Aspects of the disclosure relate to processing asset transfers. A computing platform may receive an asset transfer request, and may modify a distributed ledger to include a new block corresponding to the asset transfer request. The computing platform may identify, for each of a plurality of consensus methods, a subset of existing blocks that, when used to perform the corresponding consensus method, uses a minimum number of the existing blocks to perform the corresponding consensus method. The computing platform may store, in the distributed ledger, block combinations having the minimum number for each of the plurality of consensus methods, and may execute, using each corresponding identified subset of the existing blocks, each of the plurality of consensus methods. Based on establishing the consensus, the computing platform may direct an event processing platform to process the asset transfer request, which may cause the event processing platform to process the request.

Abstract: A system and method for parallel data processing using photonic quantum computing. A method includes receiving tasks represented by classical binary bits. The tasks are converted to a first photon beam including converted tasks, which are represented by photonic quantum bits. The first photon beam is split into split photon beams. Each split photon beam corresponds to a subset of the converted tasks that have a same work type. The split photon beams are received by a quantum neural network, which includes quantum neural network clusters. Each split photon beam is received by a respective quantum neural network cluster. Each subset of the converted tasks is processed by a respective quantum neural network cluster in parallel. Processing the converted tasks includes identifying and removing one or more duplicate tasks in each subset of the converted tasks. Outputs are generated based on respective converted tasks as a second photon beam.

Abstract: A system and method for image processing using photonic quantum computing. A method includes receiving image data represented by classical binary bits. The image data is converted to a photon beam including converted image data represented by photonic quantum bits. The photon beam is split into red-, green-, and blue-channel photon beams, which are received by a quantum neural network including quantum neural network clusters. The converted image data is processed by processing the red-, green-, and the blue-channel photon beams. Each beam is processed by a respective neural network cluster in parallel. Processing the red-channel photon beam includes converting converted red-channel image data into first grayscale image data. First filters are applied to the first grayscale image data to extract first features. The first features are compared to pre-trained features. In response to the first features matching respective pre-trained features, identified first features are identified.

Abstract: A system and method for voice processing using photonic quantum computing. A method includes receiving voice data represented by classical binary bits. The voice data is converted to a first photon beam including converted voice data represented by photonic quantum bits. The first photon beam is split into split photon beams. The split photon beams are received by a quantum neural network, which includes quantum neural network clusters. The converted voice data is processed by processing the split photon beams. Each of the split photon beams is processed by a respective neural network cluster in parallel. Processing the converted voice data includes extracting voice features. Word embeddings are created based on the voice features. Sentences are determined based on the word embeddings.

Abstract: Transactions between entities may be validated using LoRaWAN communications to more quickly process those transactions. In the example of check depositing, a first entity associated with a check payee may transmit a check clearance request to a second entity associated with a check payor using LoRaWAN communications. The LoRaWAN signaling and communications may be performed between devices within LoRaWAN range. For example, a check depositing device may receive a check deposit where the payor is associated with a different financial institution or entity. Accordingly, the check depositing device may communicate with another device associated with the payor institution or entity using LoRaWAN signals to confirm check clearance.

Abstract: Aspects of the disclosure relate to NFT exchanges. A computing platform may generate a plurality of F-NFTs including F-NFT identifiers that configure the F-NFTs for end-to-end tracking. The computing platform may extract, from a voice communication, information of a request to transfer an F-NFT. The computing platform may generate, based on the information of the request, a text file. The computing platform may input, into a GPT-4 algorithm, the text file to produce a F-NFT contract identifying the F-NFT, the transferor of the F-NFT, and a transferee of the F-NFT. The computing platform may send, to an NFT exchange platform, the F-NFT contract, which may cause the NFT exchange platform to transfer custody of the F-NFT from an account of the transferor at a first institution to an account of the transferee at a second institution.

Abstract: Transactions between entities may be validated using LoRaWAN communications to more quickly process those transactions. In the example of check depositing, a first entity associated with a check payee may transmit a check clearance request to a second entity associated with a check payor using LoRaWAN communications. The LoRaWAN signaling and communications may be performed between devices within LoRaWAN range. For example, a check depositing device may receive a check deposit where the payor is associated with a different financial institution or entity. Accordingly, the check depositing device may communicate with another device associated with the payor institution or entity using LoRaWAN signals to confirm check clearance.

Abstract: Communication, authentication, and/or validation may be required in various types of device interactions. For example, for some types of device functions, user or device authentication may be required to confirm that the function can and should be performed. Authentication information may be communicated and authentication and/or validation may be performed using LoRaWAN signaling. LoRaWAN signaling provides low power and long-range communication capabilities to efficiently and effectively perform authentication processes. In some arrangements, LoRaWAN signals may be generated by both a first device (e.g., a user device) and a second device (e.g., a function-performing device) and subsequently compared to determine whether they correspond. This correspondence may provide the requisite authentication or validation of the first device and/or an associated user.

Abstract: Device information may be obtained using LoRaWAN communications. A device information request may be generated and transmitted by a user device and include request parameters such as a device type for which information is desired, a type of information requested, a geographic range for the request, and the like and/or combinations thereof. Device information requests may also be propagated or repeated by intermediary devices to achieve the desired request range. Accordingly, a recipient device of the original request may propagate or repeat, using LoRaWAN, a request signal if it determines that the request range has not been met. If the request range has been met, the recipient device might not repeat the request.

Abstract: Transactions may be performed using a mobile device such as a user-wearable device using LoRaWAN protocol to minimize power consumption while maximizing communication range. Transaction information may be stored in the user-wearable device and transmitted to a transaction processing device using LoRaWAN communications. Transaction information may include user-specific information, payment information, merchant information, product information, user preference information and the like. In some instances, the only communication interface (or wireless communication interface) provided in the mobile device is a LoRaWAN communication interface.

Abstract: Aspects of the disclosure relate to processing asset transfers. A computing platform may receive an asset transfer request and extract information from it. The computing platform may modify a distributed ledger to include a new block corresponding to the asset transfer request. The computing platform may identify a consensus method by identifying, for each of a plurality of consensus methods, a subset of blocks from the distributed ledger that, when used to execute the corresponding consensus method, result in a lowest energy consumption value in comparison to remaining subsets of blocks. The computing platform may execute each consensus method using the corresponding identified subset of blocks, which may result in establishing consensus to process the asset transfer request. Based on establishing the consensus, the computing platform may direct an event processing platform to process the asset transfer request, which may cause the event processing platform to process the request accordingly.

Abstract: Aspects of the disclosure relate to processing asset transfers. A computing platform may receive an asset transfer request and extract information from it. The computing platform may modify a distributed ledger to include a new block corresponding to the asset transfer request. The computing platform may identify a consensus method by identifying, for each of a plurality of consensus methods, a subset of blocks from the distributed ledger that, when used to execute the corresponding consensus method, result in a lowest energy consumption value in comparison to remaining subsets of blocks. The computing platform may execute each consensus method using the corresponding identified subset of blocks, which may result in establishing consensus to process the asset transfer request. Based on establishing the consensus, the computing platform may direct an event processing platform to process the asset transfer request, which may cause the event processing platform to process the request accordingly.

Abstract: Aspects of the disclosure relate to processing asset transfers. A computing platform may receive an asset transfer request and extract information from it. The computing platform may modify a distributed ledger to include a new block corresponding to the asset transfer request. The computing platform may identify a consensus method by identifying, for each of a plurality of consensus methods, a subset of blocks from the distributed ledger that, when used to execute the corresponding consensus method, result in a lowest energy consumption value in comparison to remaining subsets of blocks. The computing platform may execute each consensus method using the corresponding identified subset of blocks, which may result in establishing consensus to process the asset transfer request. Based on establishing the consensus, the computing platform may direct an event processing platform to process the asset transfer request, which may cause the event processing platform to process the request accordingly.