A method for remote damage assessment of a vehicle is provided. The present disclosure relates to the technical field of artificial intelligence, in particular to the technical field of image and text recognition. An implementation solution is: performing data collection on a target vehicle to determine damage information of the target vehicle; obtaining call content of an insurance claiming call for the target vehicle, and extracting accident-related information from the call content, wherein the accident-related information includes named entities in the call content and a relationship between the named entities; and determining a first fraud probability corresponding to the target vehicle at least based on the damage information and the accident-related information.

An information processing device stores vehicle information on each of a plurality of vehicles, and the information processing device includes one or more processors configured to: acquire an attribute of a user who browses the vehicle information; and change a display content that is the vehicle information displayed on a terminal device based on the attribute.

An information processing system includes an information processing device that records vehicle information of each individual vehicle. The information processing device includes a controller configured to send a first signal for collecting information on buying and selling of a first vehicle in secondary distribution, when the controller detects viewing of vehicle information of the first vehicle.

A system includes a server including a controller. The controller is configured to obtain information regarding consent or non-consent of a user of a vehicle to disclosure of history data of the vehicle to a third party, and determine, when determination is made that consent of the user is not obtained, whether to transmit a signal that prompts for obtaining consent of the user, based on at least one of the history data of the vehicle and user activity information of the user.

A method of managing in-service operation of a fleet of aircraft is provided that includes generating a schedule of flights through an air transportation network that includes airports, and that includes direct flight routes or flight connections between the airports. The method includes performing a fleet assignment of the fleet of aircraft to the schedule of flights based on availability metric values for respective aircraft of the fleet of aircraft, and dispatching the fleet of aircraft serve the schedule of flights to according to the fleet assignment. In this regard, performing the fleet assignment includes, for an aircraft of the fleet of aircraft, accessing reliability metric values for parts of the aircraft. Availability scores for the aircraft are determined based on the reliability metric values from respective ones of the data sources, and the availability scores are combined to determine an availability metric value for the aircraft.

Apparatuses, systems and methods are provided for generating enterprise data relating to roof damage associated with weather and hail data. The apparatuses, systems and methods may determine aspects of a proposed service related to roof damage (e.g., damage extent, repair estimates, or repair timing) based upon the enterprise data and the base-line probable roof loss confidence scores. The apparatuses, systems and methods may generate probable roof loss confidence score data based upon the base-line probable roof loss confidence scores, weather event data and hail event data. The apparatuses, systems and methods may determine aspects of a proposed service related to roof damage (e.g., damage extent, repair estimates, or repair timing) based upon the enterprise data and the probable roof loss confidence score.

A computer-implemented method for automating service provider status and reporting during a service visit includes the initial steps of creating a service provider transaction, initiating the transaction, and calculating an estimated completion time of the transaction. The estimated completion time is based on at least one service condition, which may include the availability of servicing tools and components, the availability of service provider employees, the priority status, if any, of the service provider transaction, and the level of difficulty of service provider transaction, among others. Preferably, the service conditions include constant or variable associated values. The completion time is calculated based upon a sum of these values. If an unexpected service need or service delay arises, the service provider transaction status is updated, which includes recalculating the estimated time of completion based on a new service condition that arose from the unexpected need or delay. When the service provider transaction is complete, the customer reviews the transaction, confirms that the service provider transaction is complete, and schedules a service completion event.

Automated vehicle repair estimation by aggregate ensembling of multiple artificial intelligence functions is provided. A method comprises receiving a plurality of vehicle repair recommendation sets for a damaged vehicle, wherein each of the vehicle repair recommendation sets identifies at least one recommended vehicle repair operation of a plurality of the vehicle repair operations for the damaged vehicle; aggregating a plurality of the recommended vehicle repair operations; generating a composite vehicle repair recommendation set that identifies the aggregated recommended vehicle repair operations; and providing the composite vehicle repair recommendation set to one or more vehicle repair insurance claims management systems.

A preventive maintenance system of a machine tool capable of making determination of presence of an abnormality mechanically and automatically, which has conventionally been performed on the basis of the feeling of an operator and detecting an abnormality more accurately in an earlier stage is provided. The preventive maintenance system includes: a vibration detection unit attached to a mechanism of a machine tool to detect vibration; a sound detection unit that detects acoustic waves produced when a work is machined by the machine tool; a servo motor current value detection unit that detects a current value of a servo motor; an abnormality determination unit that compares the vibration, the acoustic waves, and the current value of the servo motor during operation of the machine tool with vibration data, acoustic wave data, and current value data in a normal state set in advance to determine presence of an abnormality in the mechanism of the machine tool; and a detection start/end command setting unit that adds commands for a detection start point and a detection end point of at least one of the vibration, the acoustic waves, and the current value of the servo motor to a machining program.

The present disclosure generally relates to a computer implemented method for operating an autonomous vehicle, specifically in relation to efficient planning of interactions with service providers. The present disclosure also relates to a corresponding control system and computer program product.