A print management device includes: an estimation unit that estimates a completion prediction time of a print process that is planned in advance according to a processing capability of a printing device, the estimation unit estimating, in response to occurrence of an abnormality in the printing device, the completion prediction time based on actual performance information on the processing capability from a start of printing by the printing device to the occurrence of the abnormality and a recovery time determined in advance, the recovery time being a time needed for dealing with the abnormality; and a notification unit that notifies the completion prediction time estimated by the estimation unit.

An image processing apparatus includes a processing section and a control section configured to instruct operation of the processing section. The control section executes, before sending, to the processing section, a first instruction corresponding to an instruction that caused an error in the past, an error avoidance operation based on instruction history information and operation state history information acquired from a storing section that stores the instruction history information and the operation state history information, the instruction history information indicating an instruction given to the processing section by the control section, the operation state history information indicating an operation state of the processing section caused by the instruction.

A method of monitoring messages from a sensor using an integrated circuit is provided. The messages include data measured by that sensor. The method includes reading a first message from interconnect circuitry of the integrated circuit. The interconnect circuitry connects the sensor to one or more core devices configured to process the messages. A first hash value is calculated for the first message. The first hash value is compared to one or more prior hash values stored in a hash store. Each prior hash value of the one or more prior hash values corresponds to a message that was read from the interconnect circuitry prior to the first message. A corrective action is performed when a difference between the first hash value and at least one of the prior hash values stored in the hash store is below a predetermined threshold.

A displaying equipment at least including an image controlling module, a primary system module, and a system controlling module is disclosed. The image controlling module continuously receives an input image from an image sensitive device after activates, and directly outputs the received input image. The system controlling module constantly monitors the primary system module after activates to determine whether the primary system module activates completely. The primary system module runs an operating system after being activated to process the input image and to generate a processed image. After the primary system module activates completely, the image controlling module outputs both the input image and the processed image simultaneously. When the primary system module is abnormal, the image controlling module restores to output the input image only.

A fault management system for functional safety of an automotive grade chip includes: an out-of-chip system and an automotive-grade chip, where the automotive-grade chip includes a processor, a system controller, a system configuration module, a fault management device, and an on-chip function module; and the fault management device is configured with a fault classification management model.

An example of an apparatus including a communication interface to receive an image file is provided. The image file represents a scanned image of a output generated by a printing device. The apparatus further includes an identification engine to process the image file with a convolutional neural network model to identify a feature. The feature may be indicative of a potential failure. The apparatus also includes an image analysis engine to indicate a life expectancy of a part associated with the potential failure based on the feature. The image analysis engine uses the convolutional neural network model to determine life expectancy.

Disclosed is systems and methods for controlling a video display of a computing device during malfunction. The systems and methods can include receiving a first video stream and determining that the first video stream includes an error message for display on the video display. Once an error message is detected, a second video stream can be transmitted to the video display. The second video stream can include an alternate message for display on the video display.

An image forming apparatus includes a wireless tag communication device to write data to, and read data from, a wireless tag attached to a sheet. An image forming device in the apparatus is configured to form an image on the sheet. A controller in the apparatus is configured to determine whether a writing of data to a wireless tag was successful based on a notification from the wireless tag communication device and generate investigation support information if the writing was not successful and control the image forming device to form an investigation support image corresponding to the investigation support information if the writing was not successful.

An information processing apparatus, an information processing method, and a non-transitory recording medium. The information processing apparatus determines an external device with maximum capacity among a plurality of external devices with non-volatile storage media for storing log information, changes an amount of log information according to a capacity of the external device with the maximum capacity, and outputs the log information to the external device with the maximum capacity.

A server apparatus collects, from a plurality of information processing apparatuses, time series information indicating a change over time in settings and a state of each information processing apparatus, and error information indicating an error that has occurred in each information processing apparatus, generates learning data including the collected information, and generates a diagnostic model, which is a trained model for a malfunction diagnosis in the information processing apparatus, through learning based on the generated learning data. The information processing apparatus obtains the diagnostic model from the server apparatus, outputs a diagnosis result indicating a likelihood that an error will occur in the information processing apparatus by collecting information necessary for the malfunction diagnosis within the information processing apparatus and executing the malfunction diagnosis using the collected information and the obtained diagnostic model.