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.

In some implementations, a device may receive data identifying products and encoded data identifying smart tags of the products. The device may map the data and the encoded data to generate encoded product data. The device may receive encoded data provided by smart tags of products received by a store. The device may receive images of the products. The device may compare the encoded data and the encoded product data to identify a set of the products received by the store. The device may correlate the images with the set of the products. The device may process the correlated data to identify locations of the set of the products in the store. The device may generate an instruction to relocate a product to a new location and may provide the instruction to a device, associated with the store, to cause the product to be relocated to the new location.

Embodiments of the present invention provide systems and methods for automated and intelligent analysis of information. The system receives interaction data, interaction metadata, and external information in order to identify parties of interactions, subjects of interactions, and infer relationships between parties and subjects based on the content, context, frequency, and amount of available interaction data. Weighted score scores are generated and used to rank the inferred relationships and determined relevance between parties and subjects. This data may be stored in a graphical database and later used to response to user data queries to facilitate collaboration.

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 control method according to the present disclosure is executed by a first server of servers in a system including one or more IoT devices and the servers. The method includes: obtaining first transaction data including malfunction information indicating that one of the IoT devices is malfunctioning, and time information indicating a time when the IoT device has obtained the malfunction information; transferring the obtained first transaction data to second servers different from the first server; executing, together with the second servers, a first consensus algorithm for an agreement on an authenticity of the first transaction data; and recording a block containing the first transaction data in a distributed ledger of the first server, when the authenticity of the first transaction data is verified by the first consensus algorithm.

There is included a method and apparatus comprising computer code configured to cause a processor or processors to perform obtaining an input of at least one of a task and a workflow, setting a timeout for the input of the at least one of the task and the workflow, determining whether the at least one of the task and the workflow observes a lack of data of the input for a duration equal to the timeout, determining, in response to determining that the at least one of the task and the workflow observed the lack of data of the input for the duration equal to the timeout, an unavailability of further data of the input, applying an update to the at least one of the task and the workflow based on determining the unavailability, and processing the at least one of the task and the workflow.

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.

A method schedules maintenance on aircraft of a fleet. The method includes: determining the required items of maintenance of an aircraft, including deadlines; if the deadline of the maintenance is within the first period of time: specifying a maintenance station adequately equipped for carrying out the maintenance work in the flight network for carrying out the maintenance work in a specific ground time of the aircraft; if that deadline is in the second period of time: specifying a time span required for carrying out the maintenance within the second period of time, and specifying the routing of all aircraft in the flight network in consideration of the technical data of the aircraft and the technical requirements of the individual flight routes. and carrying the maintenance work at the specified maintenance station in the provided ground time.