Abstract: System and methods for detecting anomalous water usage at a property having a water supply system using machine learning (ML) are provided. An ML model may generate an estimated water usage of the property associated with the property data set, where the property data set may include attributes of the property influencing the water usage of the property. The ML model may be configured to learn relationships between a historical water usage data set and a historical property data set. The systems and methods may compare the water usage of the property and the estimated water usage of the property. If the comparison indicates the water usage exceeds a threshold, a notification may be generated and provided to a user device.

Abstract: A computer system may include one or more processors configured to: (1) obtain insurance claim information; (2) generate, via an ML chatbot (or voice bot), the customized presentation based upon the insurance claim information; and/or (3) provide, via the ML chatbot, the customized presentation to a user device, such as a visual depiction and/or a verbal description of the customized presentation.

Abstract: Receiving a first notice of loss (FNOL) using a machine learning (ML) chatbot (or voice bot) when initiating an FNOL session with a user device to obtain FNOL information. Generating one or more requests for claim information by the ML chatbot based upon the FNOL information to provide to the user device during the FNOL session. Receiving the claim information by the ML chatbot from the user device based upon the one or more requests for the claim information. Analyzing information from the FNOL session to determine one or more session actions and implementing the one or more session actions.

Abstract: An autonomous vehicle (AV) computing device including at least one processor may be provided. The at least processor may be programmed to (i) receive a proposed trip including a destination location and a departure time, (ii) determine environmental conditions data based on the destination location and the departure time, (iii) retrieve current software ecosystem data for the AV, (iv) retrieve aggregated data for a plurality of AVs, the aggregated data including a plurality of correlations, each correlation including a) an interaction between at least one software application and at least one environmental condition and b) an adverse performance outcome associated with the interaction, (v) compare the environmental conditions data for the proposed trip and the current software ecosystem data for the AV to the plurality of correlations to identify an adverse performance outcome, and (vi) execute a remedial action to avoid the adverse performance outcome.

Abstract: An autonomous vehicle (AV) computing device including at least one processor may be provided. The at least processor may be programmed to (i) receive a proposed trip including a destination location and a departure time, (ii) determine environmental conditions data based on the destination location and the departure time, (iii) retrieve current software ecosystem data for the AV, (iv) retrieve aggregated data for a plurality of AVs, the aggregated data including a plurality of correlations, each correlation including a) an interaction between at least one software application and at least one environmental condition and b) an adverse performance outcome associated with the interaction, (v) compare the environmental conditions data for the proposed trip and the current software ecosystem data for the AV to the plurality of correlations to identify an adverse performance outcome, and (vi) execute a remedial action to avoid the adverse performance outcome.

Abstract: Techniques are described herein for marking virtual objects. An exemplary system includes one or more processors; and a non-transitory computer-readable medium coupled to the one or more processors and storing instructions thereon. The instructions, when executed by the one or more processors, cause the one or more processors to: (1) receive a transaction listing from a first entity, the transaction listing including (i) a digital asset that is associated with a virtual object in a virtual environment and (ii) a status of the digital asset indicating an active association with the first entity, (2) generate a transaction based upon the transaction listing, the transaction including an indication of the virtual object, (3) record the transaction in a distributed ledger, and (4) responsive to recording the transaction in the distributed ledger, cause the status of the digital asset to be displayed when the virtual object is viewed in the virtual environment.

Abstract: Techniques are described herein for minting digital assets associated with user achievements in a distributed network. An exemplary system includes one or more processors; and a non-transitory computer-readable medium coupled to the one or more processors and storing instructions thereon. The instructions, when executed by the one or more processors, cause the one or more processors to: (1) receive an update from a platform application on a user computing device, the update including (i) an association indication between a first entity of the user computing device and a second entity and (ii) an achievement of the first entity; (2) generate a transaction based upon the update, the transaction including a digital asset associated with the update; (3) record the transaction in a distributed ledger; and (4) responsive to recording the transaction in the distributed ledger, transmit a notification to the user computing device indicating the digital asset.

Abstract: Techniques are described herein for managing transactions associated with vehicles using a distributed ledger maintained by a plurality of participants. An exemplary system includes one or more processors; and a non-transitory computer-readable medium coupled to the one or more processors and storing instructions thereon. The instructions, when executed by the one or more processors, cause the one or more processors to: (1) receive a transaction listing from a first entity, the transaction listing including (i) entity data corresponding to the first entity, (ii) a non-fungible token (NFT) corresponding to a vehicle, and (iii) an updated state of the vehicle; (2) generate a transaction including a description of the transaction listing; and (3) record the transaction in a distributed ledger. A vehicle identification number (VIN) of the vehicle may be linked to the NFT in the distributed ledger.

Abstract: Systems and methods are provided for dampening impact to a vehicle. The system may include a vehicle frame component; a plurality of adjustable exterior vehicle body components coupled to the frame component, wherein the vehicle body components are on different sides of a vehicle and are configurable to dampen an external force exerted on the vehicle; a plurality of actuator components configured to adjust physical configurations of the vehicle body components relative to the frame component; a component configured to collect data representing an external environment of the vehicle; and one or more processors configured to detect, by processing the data, an external driving condition, wherein the external driving condition is an impending collision between the vehicle and one or more objects external to the vehicle, and when the external driving condition is detected, cause the actuator components to correspondingly adjust the physical configurations of the vehicle body components.

Abstract: Systems and methods relating to improving the experience of gig-economy workers are disclosed, with particular reference to gig-economy work involving vehicle use. Such systems and methods include automatically monitoring and evaluating activities such as driving during performance of gigs, as well as providing recommendations based thereupon. Transferable tokens may be used to apply information across various types of gig activities. Such a transferable token may represent one or more risk levels associated with a gig-economy worker to provide reputational information between gig-economy platforms or between types of gig-economy activities. Thus, the transferable token may enable a gig-economy worker to transfer high customer ratings across gig-economy platforms.

Abstract: Systems and methods for real-time detection and mitigation anomalous behavior of a remote vehicle are provided, e.g., vehicle behavior that is consistent with distracted or unexpectedly disabled driving. On-board and off-board sensors associated with a subject vehicle may monitor the subject vehicle's environment, and behavior characteristics of a remote vehicle operating within the subject vehicle's environment may be determined based upon collected sensor data. The remote vehicle's behavior characteristics may be utilized to detect or determine the presence of anomalous behavior, which may be anomalous for the current contextual conditions of the vehicles' environment. Mitigating actions for detected remote vehicle anomalous behaviors may be suggested and/or automatically implemented at the subject vehicle and/or at proximate vehicles to avoid or reduce the risk of accidents, injury, or death resulting from the anomalous behavior. In some situations, authorities may be notified.

Abstract: A computer-implemented method includes receiving a vehicle condition query via a computer network and retrieving condition data corresponding to a vehicle from a vehicle condition database. Further, the method includes determining a condition of the vehicle based on a collective analysis of the condition data, where the condition of the vehicle includes a market value of the vehicle and an overall quality level of the vehicle, and receiving a geographic location of a computing device. Still further, the method includes generating a vehicle condition report, where the vehicle condition report includes an interactive image of a first set of one or more visual condition descriptors indicative of the condition of the vehicle. Moreover, the method includes customizing the vehicle condition report according to the climate associated with the geographic location for the computing device, and communicating the vehicle condition report to the second computing device.

Abstract: Systems and methods relating to improving the experience of gig-economy workers are disclosed, with particular reference to gig-economy work involving vehicle use. Such systems and methods include automatically monitoring and evaluating activities such as driving during performance of gigs, as well as providing recommendations based thereupon. Gig-related activities may be automatically detected based upon data provided by a mobile device associated with the gig-economy worker, thereby automatically generating a record of such activities for the worker. Telematics data indicative of movement of a vehicle may be collected and analyzed to detect gig-economy activities. During or after performance of gig-economy work, data automatically collected may be used to generate and present recommendations or education points to the gig-economy worker.

Abstract: An autonomous vehicle (AV) computing device including at least one processor may be provided. The at least processor may be programmed to (i) receive a proposed trip including a destination location and a departure time, (ii) determine environmental conditions data based on the destination location and the departure time, (iii) retrieve current software ecosystem data for the AV, (iv) retrieve aggregated data for a plurality of AVs, the aggregated data including a plurality of correlations, each correlation including a) an interaction between at least one software application and at least one environmental condition and b) an adverse performance outcome associated with the interaction, (v) compare the environmental conditions data for the proposed trip and the current software ecosystem data for the AV to the plurality of correlations to identify an adverse performance outcome, and (vi) execute a remedial action to avoid the adverse performance outcome.

Abstract: An autonomous vehicle (AV) computing device including at least one processor may be provided. The at least processor may be programmed to (i) receive a proposed trip including a destination location and a departure time, (ii) determine environmental conditions data based on the destination location and the departure time, (iii) retrieve current software ecosystem data for the AV, (iv) retrieve aggregated data for a plurality of AVs, the aggregated data including a plurality of correlations, each correlation including a) an interaction between at least one software application and at least one environmental condition and b) an adverse performance outcome associated with the interaction, (v) compare the environmental conditions data for the proposed trip and the current software ecosystem data for the AV to the plurality of correlations to identify an adverse performance outcome, and (vi) execute a remedial action to avoid the adverse performance outcome.

Abstract: A backup control server for reducing dangers to automation systems of autonomous vehicles includes a memory and a processor. The processor is programmed to detect an anomalous event which may include one of a geomagnetic interference event and a cyber-attack event. The processor may also be programmed to perform a threat assessment for the anomalous event relative to an automation system of a vehicle. The automation system may be configured to control an aspect of autonomous operation of the vehicle. The processor may be further programmed to determine one or more mitigating actions to perform on the automation system based upon the threat assessment. The one or more mitigating actions are configured to reduce a danger to the vehicle presented by the anomalous event. The processor may also be programmed to transmit to the vehicle instructions to perform one or more mitigating actions on the automation system.

Abstract: An electrical computer network system using a blockchain is configured to: (i) receive a first request; (ii) access the blockchain; (iii) store a first new entry in the blockchain, the first new entry including data elements representing aspects of the first policy, a timestamp, and a link to a previous entry, wherein the link includes a hash of the previous entry; (iv) receive a second request for proof of policy; (v) search the blockchain for the first policy; (vi) analyze the data elements representing aspects of the first policy to verify proof of policy; and/or (vii) transmit an alert message to a computer device indicating that proof of policy has been verified.

Abstract: Dangers to autonomous vehicles may be reduced. A backup control computing device includes a memory and a processor. The processor is programmed to (1) receive an indication of an anomalous event, the anomalous event including one of a geomagnetic interference event and a cyber-attack event; (2) perform a threat assessment for the anomalous event relative to an automation system of a vehicle, the automation system is configured to control an aspect of autonomous operation of the vehicle; (3) determine one or more mitigating actions to perform on the automation system based upon the threat assessment, the one or more mitigating actions are configured to reduce a danger to the vehicle presented by the anomalous event; and (4) perform the one or more mitigating actions on the automation system, thereby reducing danger to the vehicle presented by the anomalous event.

Abstract: A computer system for conducting proof of insurance using a blockchain configured to (i) receive a request for proof of insurance for a driver of a vehicle; (ii) search a blockchain for a most recent new policy entry associated with one or more of the driver and the vehicle, the blockchain includes a plurality of policy entries associated with vehicle insurance policies and a plurality of title entries associated with state property titles; (iii) determine that an active policy for the driver exists within the blockchain; and (iv) transmit an alert message indicating that the proof of insurance has been verified for the driver.

Abstract: A backup control server for reducing dangers to automation systems of autonomous vehicles includes a memory and a processor. The processor is programmed to detect an anomalous event which may include one of a geomagnetic interference event and a cyber-attack event. The processor may also be programmed to perform a threat assessment for the anomalous event relative to an automation system of a vehicle. The automation system may be configured to control an aspect of autonomous operation of the vehicle. The processor may be further programmed to determine one or more mitigating actions to perform on the automation system based upon the threat assessment. The one or more mitigating actions are configured to reduce a danger to the vehicle presented by the anomalous event. The processor may also be programmed to transmit to the vehicle instructions to perform one or more mitigating actions on the automation system.