Abstract: Operational data generated and used in a vehicle to control various vehicular systems is temporarily stored in a data buffer in the vehicle. A processor in the vehicle is configured to detect anomalous conditions, which can be based on predefined fault codes or user defined conditions (based on a single parameter or a combination of parameters). Whenever such an anomaly is detected, a diagnostic log is conveyed from the vehicle to a remote location. Such a log will include the detected anomaly, and buffered operational data. In at least one embodiment, the diagnostic log includes buffered operational data collected both before and after the anomaly. The diagnostic log is analyzed at the remote location to diagnose the cause of the anomalous condition so a decision can be made as to whether the vehicle requires immediate repair, or whether the repair can be scheduled at a later time.

Abstract: Methods and systems are disclosed that include receiving problem information from a user interface at a resolution identification system, receiving product information at the resolution identification system, and performing machine learning analysis of the problem information and the product information. The machine learning analysis produces one or more model outputs, and is performed by a machine learning system of the resolution identification system, using one or more machine learning models. Each of the one or more machine learning models produces a corresponding one of the one or more model outputs. Such a method can further include generating resolution information by performing an action identification operation using the one or more model outputs, and outputting the resolution information from the resolution identification system. The resolution information is output to the user interface.

Abstract: A device receives current vehicle data that describes a current state of each of a plurality of components of the vehicle. The device accesses historical data describing prior services previously performed on the vehicle and applies the current vehicle data and the historical vehicle data to a trained machine learning model to obtain a set of recommended services, where the model was trained using labeled training data associated with additional vehicles having a threshold similarity to the vehicle. The machine learning model is trained to output a set of recommended services to be performed for a given vehicle based on inputs of given current vehicle data and given historical vehicle data for the given vehicle. The device outputs for display the set of recommended services to be performed on the vehicle to a user.

Abstract: Described herein are methods and systems for generating and applying vehicle maintenance models to vehicle telematics data. A vehicle telematics analytics (VTA) computing device is configured to receive vehicle telematics data associated with operation of a subject vehicle, and apply the received vehicle telematics data to a vehicle maintenance model to determine whether the operation of the subject vehicle is better or worse than standard operation of like vehicles. The VTA computing device may adjust a maintenance cost and/or determine if a user of the vehicle is eligible for a reward based upon this determination. The VTA computing device is configured to transmit an itemized report to the user including the adjusted maintenance cost and/or the reward as well as one or more other vehicle costs.

Abstract: A method for generating a user profile and system including a controller configured to execute instructions to execute the method. The method including determining by a user of a first vehicle that an interactive maneuver is needed to provide a resource, identifying a second vehicle to interact with, contacting a user of the second vehicle, requesting the user of the second vehicle to perform the interactive maneuver, receiving a response from the user of the second vehicle, and generating a user profile for the user of the second vehicle based on the performance of providing the resource.

Abstract: The method for managing the rental of vehicles (1), comprising at least one step of collecting at least one point of data relating to the vehicle (1), one step of transferring said data to a rental vehicle management center (4), and one step of sending at least one instruction from the management center (4) to the vehicle, characterized in that it also comprises at least one step of collecting and sending at least one point of data relating to the user of the vehicle (1) to the management center (4) and one step of sending the user a final updated rate according to the data received by the management center (4). The invention also relates to a device for implementing the invention.

Abstract: An example system is configured for displaying enhancement options and financial analysis. The system may include a server, third party data sources and an augmented reality computing device that includes a processing unit and system memory. The augmented reality computing device is configured to obtain user input regarding a property enhancement option; render the property enhancement options in augmented reality; obtain financial data from the server and the third party data sources; responsive to the obtained user input, automatically generate a financial analysis of the property enhancement option, wherein the financial analysis is based on the obtained financial data; and render the financial analysis with the obtained property enhancement option in augmented reality.

Abstract: Automated vehicle repair estimation by adaptive ensembling of multiple artificial intelligence functions is provided. A method comprises receiving, from a plurality of sources, vehicle repair recommendation sets identifying recommended vehicle repair operations for damaged vehicle components; selecting, by a trained artificial intelligence function, one of the operations for each component based on a plurality of learned states; generating a composite vehicle repair recommendation set identifying the selected operation; providing the composite vehicle repair recommendation set to one or more claims management systems; and repeatedly retraining the trained artificial intelligence function by adjusting the learned states according to the vehicle damage objects received, and the corresponding composite vehicle repair recommendation generated, since the last retraining of the trained artificial intelligence function.

Abstract: A construction management system includes a position determination unit that determines whether or not a transport vehicle associated with a construction site is located within a notification area associated with the construction site, and an output unit that outputs an indication that the transport vehicle is located within the notification area to a communication terminal associated with the construction site when the position determination unit determines that the transport vehicle is located within the notification area.

Abstract: In some examples, a vehicle receives authorization information that identifies an automotive service to be performed on the vehicle, the authorization information further indicating approval of performance of the automotive service on the vehicle by an operator of the vehicle and a vehicle manufacturer. Based on the authorization information, the vehicle enables access of an electronic component of the vehicle by an authorized repair entity to perform the automotive service.

Abstract: Systems and methods for generating a sensor driven optimized maintenance program are provided. A first maintenance plan for an apparatus type is received; the first maintenance plan defining maintenance tasks for the apparatus type and defining intervals at which the maintenance tasks are to be performed. Historical sensor data, historical scheduled maintenance data, and historical unscheduled maintenance data are received and correlated to determine a predictive value of the sensor data. One or more maintenance optimization objectives of an operator of an apparatus of the apparatus type are received, and the sensor driven optimized maintenance program is generated, based at least on the predictive value of the sensor data and the maintenance optimization objectives. The sensor driven optimized maintenance program includes an adjusted one of the defined intervals.

Abstract: A system for prompting vehicle service includes: a processor; a memory module communicatively coupled to the processor and including one or more processor-readable instructions that, when executed by the processor, cause the system to: determine a vehicle location; determine one or more maintenance tasks required by the vehicle; identify a maintenance facility capable of performing the one or more maintenance tasks; determine a location of the maintenance facility capable of performing the one or more maintenance tasks; determine a wait time to perform the one or more maintenance tasks at the maintenance facility; and output a maintenance scheduling prompt based on: a comparison between the wait time and a wait time threshold, and a second comparison between: (i) a magnitude of a distance between the vehicle and the maintenance facility; and (ii) a distance threshold.

Abstract: Review data associated with a guest experience at an event, such as a vacation rental, for example, is transmitted over a communications network to one or more networked computing devices for processing the review data into a review data file for publication. The review data may be generated by an application executing on a processor of a client device such as a smartphone, tablet or pad. The review data may include access credentials and location data that may be processed to validate that the review data is legitimate. The review data may include media content captured in-situ at the event while the guest is experiencing the event. Prior to publishing a review data file, an owner may receive a notice and/or a copy of the pending review data file and the owner may take action to cure a less than stellar review and/or amend the review prior to publication.

Abstract: A system for measuring health data includes a measurement device. The measurement device includes at least one measurement interface to receive a first fluid sample, a processor to measure one or more first characteristics of the first fluid sample, and at least one memory device to store first data. The processor reads the first data and measures the one or more first characteristics of the first fluid sample according to the first data. The at least one memory device also stores second data. The processor reads the second data instead of the first data to reconfigure the measurement device and measures one or more second characteristics of a second fluid sample according to the second data. An external processing device may be communicatively coupled to the measurement device and may execute a healthcare application that communicates with the measurement device and may be employed to reconfigure the measurement device.

Abstract: Health care information for multiple patients is processed to classify patients into categories. Additional data fields related to a category in which a patient is classified are added to the patient record. These data fields are populated in part by automatically processing the existing patient data. Such automatic processing can result in a probability that the underlying data supports having a particular value stored in one of the added data fields, and this probability also can be stored. Over time, additional data can be obtained from patients, caregivers and other sources, for structured data fields based on data entry forms for patient reported outcomes, caregiver reported outcomes, events of interest, survival and resource utilization. A set of factor scores is computed for each patient, for each category in which the patient is classified.

Abstract: A highly immersive, interactive and addictive platform for shopping. The system may provide both an online and retail experience through an immersive environment that enables repeat transactions and enables add-on sales to offers that are completely unique for each customer. The interactive shopping experience generates one or more bundles to any actual or potential user purchase to create a dynamic and favorable shopping experience for the particular user. The bundles are customized for each user based on user history with a merchant, product data, and merchant data, In addition to customizing the bundles, the decision of whether or not to offer one or more bundles is made only confirming that the current time is desirable to make an offer of bundles to the particular user.

Abstract: Exemplary embodiments of the present disclosure relate to systems, methods, and non-transitory computer-readable media for harvesting, parsing, and analyzing item identifiers in networked content to identify fraudulent content.

Abstract: Various embodiments are generally directed to providing a digital negotiation platform. An agent executing on a processor may programmatically negotiate parameters for an agreement based on rules and/or computing models. The agent may generate a smart contract comprising a transcript of communications and executable code operable to enforce the parameters. The smart contract may be stored in a blockchain.

Abstract: A computer method and system for disseminating computerized content via an scratchpad application in which data is received at a computing device, preferably via user input. The data is displayed on the computing device, via the scratchpad application, and a subset of the data is identified which is to be copied and disseminated. A second application is identified that will receive the data subset such that at least a portion of the data will be imported to the second application.

Abstract: The present disclosure pertains to a system configured to facilitate a user interface via device-on-premise detection and event generation based thereon.