Abstract: A system and method for maintenance and supplying of a fleet of multifunction peripheral devices includes two or more networked devices including a decision engine. Devices discover one another and one device is designated as a server. The server creates a virtual lobby accessible by other devices and its decision engine is enabled. The server invites other devices into its virtual lobby, and these devices join the lobby in response. Devices provide their device state information to the lobby. The enabled decision engine generates recommendations for consumable replenishment, device servicing or device configuration, relaying the recommendations to a system administrator's tablet or smartphone. The administrator may accept, reject, modify or implement received suggestions. Consumable supplies or servicing recommendations can be done automatically if enabled. Administrator actions are fed back to the server for machine learning to improve future suggestions.

Abstract: A system and method for printing large files from a memory constrained mobile device analyzes image files to determine whether decompressing them for display or printing would result in image data exceeding device capacity. If not, the image data is displayed on the device and sent to a printer. If so, metadata in the image files is altered such that image data is generated at a lower resolution before decompression for displaying and printing.

Abstract: A system and method for printing large files from a memory constrained mobile device analyzes image files to determine whether decompressing them for display or printing would result in image data exceeding device capacity. If not, the image data is displayed on the device and sent to a printer. If so, metadata in the image files is altered such that image data is generated at a lower resolution before decompression for displaying and printing.

Abstract: A system and method for maintenance and supplying of a fleet of multifunction peripheral devices includes two or more networked devices including a decision engine. Devices discover one another and one device is designated as a server. The server creates a virtual lobby accessible by other devices and its decision engine is enabled. The server invites other devices into its virtual lobby, and these devices join the lobby in response. Devices provide their device state information to the lobby. The enabled decision engine generates recommendations for consumable replenishment, device servicing or device configuration, relaying the recommendations to a system administrator's tablet or smartphone. The administrator may accept, reject, modify or implement received suggestions. Consumable supplies or servicing recommendations can be done automatically if enabled. Administrator actions are fed back to the server for machine learning to improve future suggestions.

Abstract: A system and method for managing fleets of network MFPs uses a portable data device such as a networked smartphone to discover and query devices over one or more network subnets. The smartphone sends out a multicast device discovery petition to all network devices and processes responses received asynchronously in parallel. A sequence of smaller multicasts can be used so as not to overwhelm available device resources. Once all devices has responded, all responses are checked sequentially. Devices identified as multifunction peripherals are sent a second petition seeking device state information. Received device state information is stored in a management database.

Abstract: A system and method for maintenance and supplying of a fleet of multifunction peripheral devices includes two or more networked devices including a decision engine. Devices discover one another and one device is designated as a server. The server creates a virtual lobby accessible by other devices and its decision engine is enabled. The server invites other devices into its virtual lobby, and these devices join the lobby in response. Devices provide their device state information to the lobby. The enabled decision engine generates recommendations for consumable replenishment, device servicing or device configuration, relaying the recommendations to a system administrator's tablet or smartphone. The administrator may accept, reject, modify or implement received suggestions. Consumable supplies or servicing recommendations can be done automatically if enabled. Administrator actions are fed back to the server for machine learning to improve future suggestions.