Abstract: Unmanned aerial vehicles (UAVs) may facilitate insurance-related tasks. UAVs may actively be dispatched to an area surrounding a property, and collect data related to property. A location for an inspection of a property to be conducted by a UAV may be received, and one or more images depicting a view of the location may be displayed via a user interface. Additionally, a geofence boundary may be determined based on an area corresponding to a property boundary, where the geofence boundary represents a geospatial boundary in which to limit flight of the UAV. Furthermore, a navigation route may be determined which corresponds to the geofence boundary for inspection of the property by the UAV, the navigation route having waypoints, each waypoint indicating a location for the UAV to obtain drone data. The UAV may be directed around the property using the determined navigation route.

Abstract: Techniques for providing recommendations of actions for a user to perform to improve efficiency in user interactions with a user interface of a user computing device. An intelligent monitoring (IM) computing system may receive data from a user computing device and may determine user interactions associated with the user interface. The user interactions may include selections, an order associated with the selections, times associated with the selections, and/or other data corresponding to user interaction with a user interface. The IM computing device may be configured to determine a fault (e.g., inefficiency) associated with the user interactions and determine an action for the user to perform to correct the fault. The IM computing device may cause a notification including the action to surface on a display of the user computing device, such as to inform the user of a means by which they can improve efficiency of the user interactions.

Abstract: Techniques for identifying faults in a collaborative computing system including a plurality of disparate, geographically separated computing systems are described herein. An intelligent monitoring (IM) server computing system may receive data from the plurality of computing devices and may monitor the health of the collaborative computing system. The IM server computing system may analyze the data and identify one or more faults associated with a portion of the collaborative system (e.g., an associated computing device, platform, network, etc.). In some examples, the IM server computing system may be configured to identify potential future faults associated with the portion of the collaborative system. Based on the fault, the IM server computing device may determine an action to take to remedy the fault and/or prevent the potential future fault. The IM server computing device may either automatically perform the action or send a notification to the associated computing system to perform the action.

Abstract: Systems and methods may facilitate acquisition, distribution, and analysis of information relating to technical events associated with client electronic computing devices within an organization (e.g., malfunctions and other performance issues of hardware and/or software). Graphical user interfaces may facilitate the acquisition of system state information associated with client devices, as well as the acquisition of other user-provided contextual information relating to technical events. Additionally, the systems and methods may facilitate acquisition, distribution, and analysis of information relating to organizational ideas raised by client device users within the organization.

Abstract: The present embodiments relate to detecting fraudulent insurance claims. According to certain aspects, a central monitoring server may receive and examine data detected by at least one unmanned vehicle and generate an estimated insurance claim for a loss event. The central monitoring server may then receive an actual insurance claim relating to the loss event, and may compare the estimated insurance claim to the actual insurance claim to identify potential buildup included in the actual insurance claim. If buildup is detected, the central monitoring server may then process the actual insurance claim accordingly based upon the potential buildup. As a result, claim monies may be paid to insureds that more accurately reflect actual losses resulting from the loss event, and insurance cost savings may be ultimately passed onto typical insurance customers.

Abstract: Systems and methods are described for using data collected by unmanned aerial vehicles (UAVs) to generate insurance claim estimates that an insured individual may quickly review, approve, or modify. When an insurance-related event occurs, such as a vehicle collision, crash, or disaster, one or more UAVs are dispatched to the scene of the event to collect various data, including data related to vehicle or real property (insured asset) damage. With the insured's permission or consent, the data collected by the UAVs may then be analyzed to generate an estimated insurance claim for the insured. The estimated insurance claim may be sent to the insured individual, such as to their mobile device via wireless communication or data transmission, for subsequent review and approval. As a result, insurance claim handling and/or the online customer experience may be enhanced.

Abstract: Various techniques are described utilizing unmanned aerial vehicles (UAVs, or “drones”) for various disaster and/or catastrophe-related purposes. An area at risk of an insurance-related event (catastrophe, hurricane, natural disaster, wild fire, etc.) that requires evacuation may be determined, as well as insured premises or assets within that area. With an insured's permission, drones may be directed to the area to collect image or other data of insured premises or assets before, during, or after the event strikes. The drone data may be received and analyzed to identify losses to insured assets that should properly be classified as theft losses for insurance purposes. Insurance claims may be prepared or adjusted for insureds based upon the theft losses in accordance with various types of insurance policies (auto, home, personal articles, etc.) or endorsements to ensure that insureds are properly and promptly reimbursed for the theft losses.

Abstract: A method and system may assess the damage to infrastructure using aerial images captured from an unmanned aerial vehicle (UAV), a manned aerial vehicle (MAV) or from a satellite device. Specifically, an item of infrastructure may be identified for assessing damage. The UAV, MAV, or satellite device may then capture aerial images within an area which surrounds the identified infrastructure item. Subsequently, the aerial images may be analyzed to determine a condition and the extent and/or severity of the damage to the infrastructure item. Furthermore, the aerial images along with indications of the extent of the damage may be displayed on a computing device, where one indication of the severity of the damage surrounds another indication of the severity of the damage on the display.

Abstract: Various techniques are described utilizing one or more unmanned aerial vehicles (UAVs, or “drones”) for various disaster and/or catastrophe-related purposes. UAVs may collect data in an attempt to predict the occurrence and/or extent of a catastrophe and/or to mitigate the impact of a catastrophe before and, if not at that time, once it has occurred. The UAVs may perform various tasks such that the damage to property caused by a catastrophe (or potential catastrophe) may be eliminated or mitigated. The drone data may be transmitted by the UAVs to an external computing device, which may be associated with an insurer and used, with an insured's permission, to begin and/or facilitate an insurance claim process or other various insurance-related tasks. Damage to insured property may be estimated from the drone data, and proposed or estimated insurance claims may be generated for customer review, modification, or approval.

Abstract: Unmanned aerial vehicles (UAVs) may facilitate the generation of a virtual reconstruction model of a vehicle collision. UAVs may collect data (including images) related to the vehicle collision, such as with the insured's permission, which may be received by an external computing device associated with the insurer and utilized to perform a photogrammetric analysis of the images to determine vehicle impact points, the road layout at the scene of the collision, the speeds and directions of vehicles, etc. This data may be used to generate a virtual reconstruction model of the vehicle collision. An insurer may use the virtual reconstruction model to perform various insurance-related tasks, such as allocating fault to drivers or autonomous vehicles involved in the vehicle collision, and adjustment of insurance pricing based upon the fault allocation. As a result, innocent drivers or vehicles may not be unfairly penalized for vehicle collisions not their fault.

Abstract: Systems and methods are described for using data collected by unmanned aerial vehicles (UAVs) to generate insurance claim estimates that an insured individual may quickly review, approve, or modify. When an insurance-related event occurs, such as a vehicle collision, crash, or disaster, one or more UAVs are dispatched to the scene of the event to collect various data, including data related to vehicle or real property (insured asset) damage. With the insured's permission or consent, the data collected by the UAVs may then be analyzed to generate an estimated insurance claim for the insured. The estimated insurance claim may be sent to the insured individual, such as to their mobile device via wireless communication or data transmission, for subsequent review and approval. As a result, insurance claim handling and/or the online customer experience may be enhanced.

Abstract: Unmanned aerial vehicles (UAVs) may facilitate insurance-related tasks. UAVs may actively be dispatched to an insured asset and the area surrounding an insured asset, such as with the policyholder or insured's permission and collect data related to the insured asset, such as images, video, audio, weather conditions, thermal signatures, wood and soil samples, etc., and transmit this data to a computing device. The computing device may be associated with and/or utilized by an insurance provider to perform insurance-related tasks, such as processing the data to determine an amount of risk associated with the insured asset. If the amount of risk has increased, the computing device may provide a recommendation to a mobile device of the policyholder on how to reduce the risk such that corrective action may be taken. Insurance discounts may be provided based upon following recommendations that mitigate risk.

Abstract: Unmanned aerial vehicles (UAVs) may facilitate insurance-related tasks. UAVs may actively be dispatched to an area surrounding an insured or potentially insured asset, such as with the insurance customer's permission, and collect data related to the insured or potentially insured asset, such as size, height, roof shape, materials (siding, roofing), etc. which may form a basis of the underwriting detail used to evaluate a property. The drone data may reveal site characteristics, such as slope or grade of a parcel; the proximity to other structures (and their uses); trees; rivers; coastlines; and earthquake faults. The drone data may be used by an insurance provider remote server to assess the risk associated with an insured asset, generate or modify an insurance premium or discount, etc. The drone data may also be used to mitigate risk and prevent loss by alerting policyholders of the risk such that corrective action may be taken.

Abstract: Unmanned aerial vehicles (UAVs) may facilitate insurance-related tasks. UAVs may actively survey an area or be dispatched to the scene of a vehicle collision or crash, such as with an insured's permission, and collect data related to the vehicle collision or crash, such as vehicle data, insurer data, images, video, audio, weather conditions, etc., and transmit this data to a computing device. The computing device may be associated with an insurer and/or utilized by an insurer to perform insurance-related tasks, such as processing the data to assign fault to one or more parties or vehicles, such as autonomous vehicles, involved in the vehicle collision or crash, using the fault assignment to open or otherwise process an insurance claim, modifying a premium price, updating qualified discounts, etc. The drone data may also assist an insurer in opening an insurance claim by prepopulating fields associated with a submitted claim form.

Abstract: A computer-implemented method for assessing a building structure. The method includes receiving information indicative of captured data, the captured data comprising an image of the building structure. The method includes receiving information indicative of an analysis of the captured data. The method includes based on the analysis of the captured data, performing an assessment of the one or more examined regions. Performing the assessment includes determining one or more classifications each corresponding to a different one of the one or more examined regions, and determining one or more indicators each corresponding to a different one of the one or more classifications. The method includes determining a mapping of the one or more indicators to the one or more examined regions. The method includes providing for display the one or more indicators overlaid onto the image according to the determined mapping.

Abstract: A computer-implemented method for identifying a property usage type based upon sensor data includes, with customer permission or affirmative consent, receiving data generated by various sensors; generating a report that includes a listing of events recorded by each sensor; analyzing data from the report to determine a property usage type score; receiving data regarding types and levels of insurance coverage associated with the property usage type score; receiving data derived from a homeowner's insurance policy; comparing the types and levels of insurance coverage associated with the property usage type score with the types and levels of insurance coverage from the homeowner's current insurance policy; and transmitting a message to the homeowner to update their insurance policy if there are differences between (i) the insurance coverage that the homeowner has, and (ii) the insurance coverage the homeowner should have based upon the property usage type score.

Abstract: Unmanned aerial vehicles (UAVs) may facilitate insurance-related tasks. UAVs may actively be dispatched to an insured asset and the area surrounding an insured asset, such as with the policyholder or insured's permission and collect data related to the insured asset, such as images, video, audio, weather conditions, thermal signatures, wood and soil samples, etc., and transmit this data to a computing device. The computing device may be associated with and/or utilized by an insurance provider to perform insurance-related tasks, such as processing the data to determine an amount of risk associated with the insured asset. If the amount of risk has increased, the computing device may provide a recommendation to a mobile device of the policyholder on how to reduce the risk such that corrective action may be taken. Insurance discounts may be provided based upon following recommendations that mitigate risk.

Abstract: Unmanned aerial vehicles (UAVs) may facilitate insurance-related tasks. UAVs may actively be dispatched to an area surrounding an insured or potentially insured asset, such as with the insurance customer's permission, and collect data related to the insured or potentially insured asset, such as size, height, roof shape, materials (siding, roofing), etc. which may form a basis of the underwriting detail used to evaluate a property. The drone data may reveal site characteristics, such as slope or grade of a parcel; the proximity to other structures (and their uses); trees; rivers; coastlines; and earthquake faults. The drone data may be used by an insurance provider remote server to assess the risk associated with an insured asset, generate or modify an insurance premium or discount, etc. The drone data may also be used to mitigate risk and prevent loss by alerting policyholders of the risk such that corrective action may be taken.

Abstract: Systems and approaches for detecting an event, such as a crash involving a motorized and/or non-motorized vehicle, are described. In one approach, a listening component of a mobile computing device is first activated. This listening component may then monitor the sound proximate thereto (e.g., within the vehicle in which the mobile computing device is disposed). Using one or more processors, an audio source may be detected which was generated by an event (such as, for example, a crash involving the vehicle and/or an alerting triggering phrase) and was sensed by the listening component. Using an audio recognition technique, the detected audio source is processed to determine a severity of the event which generated the audio signal. This detection step may include identifying a type and magnitude of the detected audio signal using audio signal identification data. An information signal based on the severity of the event is then transmitted.

Abstract: A method and system may determine the condition of insured properties in a neighborhood using aerial images captured from an unmanned aerial vehicle (UAV) or from a satellite device. The neighborhood may be selected by identifying a neighborhood that includes properties which are insured by a particular insurance provider. Aerial images of the entire neighborhood may then be captured and received from the UAV or the satellite device. For each insured property in the neighborhood, a condition and level of risk may be automatically determined based on the received aerial images. Then a level of risk indicator may be assigned to the insured property based on the determined level of risk. The aerial images of the insured property may be displayed on a user interface with indications of the level of risk overlaying the aerial images.