Abstract: A system and method of a system provides for tracking and controlling print cartridge ownership transfers using non-fungible tokens (NFTs). A print cartridge manufacture creates a unique NFT for each manufactured print cartridge that is stored on a public blockchain. Each NFT is encoded with a serial number of its associated cartridge, along with manufacturer information stored in the manufacturer's digital certificate. Each NFT may include manufacturer information, transactional information and a smart contract. Sale or resale of a cartridge is accomplished by a sale of its associated NFT on a digital marketplace. Sales are governed by smart contract terms. A buyer scans a cartridge QR code to decode its serial number which is then used to lookup manufacturer information, cartridge information and transactional information. If a purchase permitted and is accepted, the buyer information and sale information are updated to the blockchain with the associated NFT which is placed in the possession of the buyer.

Abstract: A system and method for toner classification from device printouts includes applying machine learning to electronic documents formed from scanned printout images. A training set is formed by scanning documents known to be printed with OEM toner, supplemented by scanning documents known to be printed with non-OEM toner. When new printouts are made, they are scanned and analyzed by an AI/ML server and classified as printed by OEM toner or by non-OEM toner.

Abstract: A system and method for toner classification from device printouts includes applying machine learning to electronic documents formed from scanned printout images. A training set is formed by scanning documents known to be printed with OEM toner, supplemented by scanning documents known to be printed with non-OEM toner. When new printouts are made, they are scanned and analyzed by an AI/ML server and classified as printed by OEM toner or by non-OEM toner.

Abstract: A system and method for predicting device failures and generating proposed resolutions for such an error when occurs includes receiving device status data from each of a plurality of identified multifunction peripherals into a memory. Service history data for each of the multifunction peripherals is stored, the service history data including data corresponding to a plurality of data patterns associated with prior device failures associatively with resolutions implemented to address such failures. Patterns are detected in received device status data. Device failure is predicted for at least one identified multifunction peripheral in accordance with detected patterns and service history data. The predicted device failure is reported along with at least one proposed resolution to address a device error predicted by the predictive device failure data.

Abstract: A system and method for offloading service cloud tasks to multifunction peripherals includes a service cloud that transmits an application to a multifunction peripheral. The multifunction peripheral receives the application into memory and executes the application. The application performs a management task associated with the multifunction peripheral similarly to how the service cloud would perform the management task. Once the management task has been performed, the application transmits synchronization data with the service cloud. Offloading the management task to the multifunctional peripheral substantially reduces the computational load on the service cloud.

Abstract: A system and method for predicting device failures and generating proposed resolutions for such an error when occurs includes receiving device status data from each of a plurality of identified multifunction peripherals into a memory. Service history data for each of the multifunction peripherals is stored, the service history data including data corresponding to a plurality of data patterns associated with prior device failures associatively with resolutions implemented to address such failures. Patterns are detected in received device status data. Device failure is predicted for at least one identified multifunction peripheral in accordance with detected patterns and service history data. The predicted device failure is reported along with at least one proposed resolution to address a device error predicted by the predictive device failure data.

Abstract: A system and method for distributed multifunction peripheral blockchain ledgering includes a group of networked MFPs, each having a document processing engine, a network interface and an intelligent controller with a processor and memory. An electronic blockchain ledger is stored in memory, along with licensing data designating the multifunction peripheral as trusted. Transaction data is received via the network interface and validated. MFPs poll other trusted, networked multifunction peripherals to validate received transaction data, and update the blockchain ledger in accordance with validated transactions.

Abstract: A system and method for distributed multifunction peripheral blockchain ledgering includes a group of networked MFPs, each having a document processing engine, a network interface and an intelligent controller with a processor and memory. An electronic blockchain ledger is stored in memory, along with licensing data designating the multifunction peripheral as trusted. Transaction data is received via the network interface and validated. MFPs poll other trusted, networked multifunction peripherals to validate received transaction data, and update the blockchain ledger in accordance with validated transactions.

Abstract: A system and method for updating of device codes in a multifunction peripheral includes a portable data device having a processor and associated memory and a touchscreen user interface. An input receives a device code set corresponding to a desired multifunction peripheral configuration and the codes are stored in the memory. The processor generates a selectable one click prompt on the touchscreen. The processor enables the input prompt for user selection in when a wireless data interface is in active communication with the multifunction peripheral. The processor determines that the input prompt has been selected and sends the device code set to the multifunction peripheral via the wireless data interface.

Abstract: A system and method for machine learning classification of sensitive data includes a multifunction peripheral having an intelligent controller with a processor and associated memory, and print and scan engines operable in connection with instructions received from the controller. The processor receives electronic document data comprised of a plurality of electronic documents. The processor applies machine learning to the electronic document data and extracts metadata comprised as data patterns which are stored in memory. The processor generates pattern classifications from extracted data patterns to generate telemetry data. Generated telemetry data is sent to an associated server via the network interface. The server provides analytics on received telemetry data to provide enhancements for improving the multifunction peripheral.

Abstract: A system and method for predictive inventory management includes a processor and memory. A network interface receives device status data from each of a plurality of multifunction peripherals into the memory. The memory stores service history data and service call history data for the multifunction peripherals, in addition to replacement parts data corresponding to replacement parts used in prior device repairs. The processor detects patterns in the service history data, the service call history data and the replacement parts data and generates predictive replacement part data for future replacement parts that will be needed based on the device status data and the detected patterns. The processor then outputs the predictive replacement part data.

Abstract: A system and method for paper jam prediction includes a processor, memory and a network interface. Ongoing paper jam data is received from an identified, networked multifunction peripheral. Service call data for the multifunction peripheral indicative of prior service calls is stored in the memory. A sampling window of the paper jam data prior to a service call date is defined and a point in the sampling window when no symptoms of a forthcoming paper jam were present is determined so as to define a prediction window. A relationship between paper jam data in the prediction window of the sampling window and paper jam data outside the prediction window in the sampling window is determined and incoming paper jam data is monitored relative to the relationship data. A paper jam warning is generated when monitored incoming paper jam data indicates a forthcoming paper jam on the multifunction peripheral.

Abstract: A system and method for paper jam prediction includes a processor, memory and a network interface. Ongoing paper jam data is received from an identified, networked multifunction peripheral. Service call data for the multifunction peripheral indicative of prior service calls is stored in the memory. A sampling window of the paper jam data prior to a service call date is defined and a point in the sampling window when no symptoms of a forthcoming paper jam were present is determined so as to define a prediction window. A relationship between paper jam data in the prediction window of the sampling window and paper jam data outside the prediction window in the sampling window is determined and incoming paper jam data is monitored relative to the relationship data. A paper jam warning is generated when monitored incoming paper jam data indicates a forthcoming paper jam on the multifunction peripheral.

Abstract: A system and method for multifunction peripheral device failure prediction includes a processor, memory and a network interface. The system receives device status data from each of a plurality of identified multifunction peripherals. Service history data for each of the multifunction peripherals is stored in memory. The processor detects anomalies in received device status data and generates predictive device failure data for at least one identified multifunction peripheral in accordance with detected anomalies and service history data. Predictive device failure data can be used to schedule technician visits or add device maintenance to previously scheduled visits. Such scheduling can include scheduling of service to geographically clustered devices.

Abstract: A system and method for multifunction peripheral device failure prediction includes a processor, memory and a network interface. The system receives device status data from each of a plurality of identified multifunction peripherals. Service history data for each of the multifunction peripherals is stored in memory. The processor detects anomalies in received device status data and generates predictive device failure data for at least one identified multifunction peripheral in accordance with detected anomalies and service history data. Predictive device failure data can be used to schedule technician visits or add device maintenance to previously scheduled visits. Such scheduling can include scheduling of service to geographically clustered devices.

Abstract: A system and method for predicting device failures and generating proposed resolutions for such an error when occurs includes receiving device status data from each of a plurality of identified multifunction peripherals into a memory. Service history data for each of the multifunction peripherals is stored, the service history data including data corresponding to a plurality of data patterns associated with prior device failures associatively with resolutions implemented to address such failures. Patterns are detected in received device status data. Device failure is predicted for at least one identified multifunction peripheral in accordance with detected patterns and service history data. The predicted device failure is reported along with at least one proposed resolution to address a device error predicted by the predictive device failure data.

Abstract: A system and method for obfuscating indicia on reused printing media includes a scanner and a printer. A sheet feeder communicates a paper sheet for scanning and the sheet is scanned to generate a digital image which is analyzed to determine a presence of indicia on the paper surface. One or more areas of the paper surface containing indicia are identified and an overprint is commenced in the one or more areas encompassing identifiable indicia. The overprinted sheet containing the indicia and the overprint is then erased.

Abstract: A system and method for generating culturally appropriate customizable cards on multifunction peripherals includes a touchscreen user interface that displays customizable cards that can be selected and customized by users. A processor generates an electronic image of a customized card, and a document processing engine of the multifunction peripheral renders printed output from the electronic image. The multifunction peripheral sends identifying information to a card template server that provides culturally relevant customizable card templates to the multifunction peripheral based on an identified culture associated with the users of the multifunction peripheral, the geographic region where the multifunction peripheral is located, and the date.

Abstract: A system and method for multifunction peripheral cloning includes a device controller with a processor and associated memory and a network interface. Device configuration data is stored on the device for configuring device components such as a scan engine and a print engine. A controller processor of a multifunction peripheral designated as a leader device generates a master clone file from a copy of its device configuration data and communicates it to at least one networked multifunction peripheral via the network interface via a push to targeted devices or responsive to a request for a copy of the master clone file from follower devices.

Abstract: A system and method for multifunction peripheral cloning includes a device controller with a processor and associated memory and a network interface. Device configuration data is stored on the device for configuring device components such as a scan engine and a print engine. A controller processor of a multifunction peripheral designated as a leader device generates a master clone file from a copy of its device configuration data and communicates it to at least one networked multifunction peripheral via the network interface via a push to targeted devices or responsive to a request for a copy of the master clone file from follower devices.