Abstract: The following relates generally to using artificial intelligence (AI) and/or machine learning (ML) to identify patentable ideas from company emails. In some embodiments, one or more processors: access one or more email messages; identify, via a machine learning (ML) chatbot trained to analyze text and generate text, one or more patentable concepts in the one or more email messages; compare the one or more patentable concepts to a patent database including published patent applications with respective publication dates on or before the date of database access, wherein comparing includes generating a comparison document indicating at least one difference and/or at least one similarity between the one or more patentable concepts and the patent applications of the patent database, wherein the comparing includes using the ML chatbot; and generate, based upon the comparison, one or more novelty scores for each of the one or more patentable concepts.

Abstract: The following relates generally to aiding underwriting and insurance agents. In some embodiments, one or more processors: (1) receive, with an AI chatbot (or voice bot) of the one or more processors, an input statement; (2) determine, with the AI chatbot, from the received input statement, a type of insurance policy; (3) determine, with the AI chatbot, from the input statement, a question corresponding to the type of insurance policy; (4) determine, with the AI chatbot, an answer to the question by retrieving insurance information based upon (i) the type of insurance policy, and/or (ii) the question; and/or (5) present, via the AI chatbot, the answer to the question.

Abstract: The following relates generally to using artificial intelligence (AI) and/or machine learning (ML) to recommend a change in insurance coverage. In some embodiments, one or more processors: receive customer information of an insurance customer; determine that an insurance change recommendation trigger has occurred by routing the customer information into an insurance recommendation machine learning and/or artificial intelligence algorithm; and in response to determining the insurance change recommendation trigger, send a recommendation for an insurance policy change for the insurance customer.

Abstract: The following relates generally to building a ground truth insurance database. In some embodiments, one or more processors: (1) receive potential insurance database information comprising (i) insurance company application (app) information, (ii) anonymized insurance claim information, (iii) police report information, and/or (iv) auxiliary information; (2) retrieve, from an insurance ground truth insurance database, existing ground truth insurance information by querying the ground truth database based upon the potential insurance database information; (3) determine if the potential insurance database information should be added to the insurance ground truth database by comparing the potential insurance database information to the existing ground truth insurance information; and/or (4) if the potential insurance database information should be added to the insurance ground truth database, add the potential insurance database information to the insurance ground truth database.

Abstract: The following relates generally to using AI and/or ML to build and/or present an insurance contract. In some embodiments, one or more processors: (1) receive, with an AI chatbot of the one or more processors, an input statement; (2) determine, with the AI chatbot, from the received input statement, a type of insurance policy, wherein the type of insurance policy comprises a homeowners insurance policy, a renters insurance policy, an auto insurance policy, a life insurance policy, a disability insurance policy, and/or an umbrella insurance policy; (3) build, with the AI chatbot, an insurance contract based upon the type of insurance policy; and/or (4) present, via the AI chatbot, the insurance contract to the potential insurance customer.

Abstract: Systems and methods for providing real-time feedback to a driver of a vehicle based on real-time datasets is disclosed. The systems and methods include obtaining one or more sets of real-time data associated with a vehicle. Performing one or more operations on the set of real-time data, wherein the one or more operations are based on the set of real-time data. Generating, a feedback alert based on results of the one or more operations and one or more detected real-time behaviors of the vehicle. Providing the feedback alert for presentation at a user interface on-board the vehicle. The real-time data may include contextual data, environmental data, operating data, data for a plurality of drivers, or combinations thereof.

Abstract: Systems and methods for simulating a vehicle seat in a vehicle using virtual reality. The systems and methods may generate a virtual configuration comprising a virtual vehicle seat model associated with a physical vehicle seat, and a virtual vehicle model associated with a physical vehicle, to be presented via the display of a viewer device.

Abstract: A system and method are provided for controlling an interior configuration of a vehicle following a collision. Sensor data that includes, or is derived from data that includes, data collected by one or more sensors is received, and a vehicle accident condition indicative of an accident having occurred is detected by processing the sensor data. After detecting the vehicle accident condition, an actuator component is caused to prevent a passenger from adjusting an interior vehicle component outside a predetermined range of physical configurations, while allowing the passenger to adjust the interior vehicle component within the predetermined range of physical configurations.

Abstract: Methods and systems for visualizing proper fastening of vehicle seats. The method and systems may include: (1) receiving, by one or more processors, input data that may include one or more of vehicle data, vehicle seat data, and/or child data; (2) receiving, by the one or more processors, underlay layer data indicative of a field of view (FOV) associated with an AR viewer device; (3) generating, by the one or more processors, overlay layer data based upon the input data, the overlay layer data may include an indication of a proper fastening of the vehicle seat; (4) correlating, by the one or more processors, the overlay layer data with the underlay layer data; (5) creating, by the one or more processors, an AR display based upon the correlation; and/or (6) presenting, by the one or more processors to the AR viewer device, the AR display.

Abstract: Methods and systems for validating proper fastening of vehicle seats via an application executing on a mobile computing device. The method and systems may include: obtain input data via an input interface of the mobile computing device, the input data including one or more of vehicle data, vehicle seat data, or child data; obtain underlay layer data generated by an image sensor of the mobile computing device; generate overlay layer data based upon the input data and/or the underlay layer data, the overlay layer data including an indication associated with proper fastening of the vehicle seat; corelate the overlay layer data with the underlay layer data; the one or more processors to create an AR display based upon the correlation; and/or present the AR display via an AR interface of the mobile computing device.

Abstract: Methods and systems for monitoring and analyzing vehicle seats, vehicle seat installation, and/or vehicle seat operation. The systems and methods may include (1) obtaining, by one or more processors, image data of a vehicle seat located within a vehicle, wherein the image data may include one or more connecting points of the vehicle seat to the vehicle; (2) inputting, by the one or more processors, the image data into a machine vision model that is trained: (a) using historical image data of vehicle seats within vehicles, (b) to learn a relationship between extracted features of the historical image data and a properness of an installation of a vehicle seat, and/or (c) to output a determination of a properness of an installation of a vehicle seat in response to detecting input image data; and/or (3) presenting, by the one or more processors, an indication of the output of the machine vision model.

Abstract: Systems and methods for simulating a vehicle seat in a vehicle using augmented reality. The systems and methods overlay a virtual vehicle seat model associated with a physical vehicle seat onto a physical vehicle via a display of the viewer device to generate a virtual configuration of the virtual vehicle seat model in the physical vehicle.

Abstract: Methods and systems for monitoring and analyzing vehicle seats, vehicle seat installation, and/or vehicle seat operation. The systems and methods may include (1) obtaining, by one or more processors, image data of a vehicle seat located within a vehicle, wherein the image data may include one or more connecting points of the vehicle seat to the vehicle; (2) inputting, by the one or more processors, the image data into a machine vision model that is trained: (a) using historical image data of vehicle seats within vehicles, (b) to learn a relationship between extracted features of the historical image data and a properness of an installation of a vehicle seat, and/or (c) to output a determination of a properness of an installation of a vehicle seat in response to detecting input image data; and/or (3) presenting, by the one or more processors, an indication of the output of the machine vision model.

Abstract: Methods and systems for maintaining and classifying data related to vehicle seats stored on a blockchain. The systems and methods may include (1) detecting one or more sets of data relating to vehicle seats; (2) executing a data maintenance smart contact to classify the sets of data as being publicly accessible or proprietary; (3) based upon the classification assigned by the data maintenance smart contract, adding the one or more sets of data to a data repository accessible via a blockchain; (4) detecting a request to access a requested set of proprietary data from a requestor; (5) executing a security smart contract to determine whether the requestor is authorized to access the requested set of proprietary data; and/or (6) enforcing the determination of the security smart contract with respect to the request.

Abstract: Systems and methods for automatically evaluating a vehicle seat replacement after a vehicle collision. Upon detecting a vehicle collision is detected, obtaining vehicle seat condition data from vehicle seat sensors and vehicle condition data from vehicle sensors. Analyzing the vehicle seat condition data and/or the vehicle condition data to detect one or more collision conditions indicating (i) the vehicle is not drivable, (ii) a vehicle door proximate the vehicle seat is damaged, (iii) an airbag of the vehicle is deployed, and/or (iv) the vehicle seat is visibly damaged. In response to detecting the one or more collision conditions, generating a recommendation to replace the vehicle seat and providing the recommendation to a user device.

Abstract: According to certain aspects, a computer-implemented method for operating an autonomous or semi-autonomous vehicle may be provided. With the customer's permission, an identity of a vehicle operator may be identified and a vehicle operator profile may be retrieved. Operating data regarding autonomous operation features operating the vehicle may be received from vehicle-mounted sensors. When a request to disable an autonomous feature is received, a risk level for the autonomous feature is determined and compared with a driver behavior setting for the autonomous feature stored in the vehicle operator profile. Based upon the risk level comparison, the autonomous vehicle retains control of vehicle or the autonomous feature is disengaged depending upon which is the safer driver—the autonomous vehicle or the vehicle human occupant. As a result, unsafe disengagement of self-driving functionality for autonomous vehicles may be alleviated.

Abstract: Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, an identity of a vehicle operator may be determined and a vehicle operator profile and/or operating data regarding autonomous operation features of the vehicle may be received after the vehicle operator opts into a rewards program and agrees to share their data. Autonomous operation and vehicle operator risk levels associated with operation of the autonomous or semi-autonomous vehicle may be determined. Based upon the risk levels and/or comparison thereof, one or more autonomous operation features may he disengaged. A preparedness level of the vehicle operator to assume or reassume control of operating the vehicle is determined prior to disengagement. If satisfactory, an alert is presented to the vehicle operator prior to disengagement of the autonomous operation features.

Abstract: Systems and methods for determining the performance of a driver of a vehicle based on changes, over time, in the context and environment in which the vehicle operates, and any resultant driver behavior are disclosed. A set of driver response data is created from based on an analysis of time-series data indicative of the driver's operation of the vehicle in conjunction with time-series data indicative of changes in the vehicle's context/environment. The driver response data indicates the types and magnitudes of the driver's responses to various changes in the vehicle's operating context/environment and the driver's time-to-respond for each of the responses. That is, the driver response data indicates how a driver compensated his or her behavior (if at all) in response to different changes in the vehicle's context and/or environment. The driver response data may be compared to one or more thresholds to determine the driver's performance.

Abstract: Vehicles may have autonomous capabilities that permit the vehicle to navigate according to varying levels of participation by a human operator. A human operator may be associated with a driving capability profile and the environment surrounding a vehicle may be associated with an environmental risk profile. A vehicle, or another party in communication with a vehicle, may determine whether, based on the human operator's driving capability profile and the environmental risk profile, it is likely that the vehicle will be navigated more safely if there is a change to the vehicle's autonomous capabilities and a corresponding change to the human operator's driving responsibilities. If it is determined that a change in autonomous vehicle capability is likely to increase safe navigation of the vehicle, an insurer may offer an insurance premium cost reduction if the human operator agrees to the proposed change in autonomous capabilities.

Abstract: Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features arm provided. According to certain aspects, the operating status of the features, the identity of a vehicle operator, risk levels for operation of the vehicle by the vehicle operator, or damage to the vehicle may be determined based upon sensor or other data. According to further aspects, decisions regarding transferring control between the features and the vehicle operator may be made based upon sensor data and information regarding the vehicle operator. Additional aspects may recommend or install updates to the autonomous operation features based upon determined risk levels. Some aspects may include monitoring transportation infrastructure and communicating information about the infrastructure to vehicles.