Abstract: A method and system may display real-time aerial images of insured properties in a neighborhood captured from an unmanned aerial vehicle (UAV), a manned aerial vehicle (MAV), or from a satellite device. For example, aerial images of a neighborhood having insured properties, that have been affected by a catastrophe, may be received from the UAV, MAV, or the satellite device. Aerial images of each insured property may be analyzed to determine a damage severity level and assign a damage severity level indicator to the damage severity level. As a result, the property owner may receive a notification that a catastrophe has impacted her neighborhood. Moreover, the real-time images, with damage severity level indicators overlaying the property, may be transmitted via a web page to the property owner's web-enabled device after the property owner logs in to a customer account.

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 for monitoring a local environment for abnormal conditions (e.g., burglary, intrusion, fire, or flooding) are disclosed. Sensors of a smartphone, tablet computer, or other computing device may be used to obtain sensor data regarding the environment. Such sensor data may relate to sounds, temperatures, lighting, or other conditions within the environment. The observed environmental conditions may be compared against reference levels or patterns to determine abnormal conditions. When abnormal conditions are identified, a response may be determined and implemented, such as alerting a user or contacting an emergency service (e.g., police or fire services). In some circumstances, a training period may be used to determine baseline or threshold levels of normal environmental conditions. Different modes or profiles may be used, which may be associated with different environments (e.g., home, hotel, etc.).

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: 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: A crash detection system is disclosed that utilizes a mobile computing device to detect a vehicular accident via one or more sensors integrated into the mobile computing device. The system monitors the sensor metrics measured by one or more sensors and generates an event sensor profile that may include the plurality of sensor metrics and additional status data, such as an indication of whether the mobile computing device was located within a vehicle when the event occurred. By comparing the plurality of sensor metrics to other crash sensor metrics, a determination may be made whether the event requires emergency assistance, which may be confirmed by determining whether the data included in the event sensor profile meets one or more exception conditions. If the event requires emergency assistance and an exception condition is not met, the mobile computing device may place a call to the appropriate emergency response personnel.

Abstract: Systems and methods for using unassisted vehicles to assess damage in a particular location are described. According to certain aspects, the systems and methods may utilize an unmanned ground vehicle (UGV) and a plurality of unmanned aerial vehicles (UAVs). The UGV and the UAVs may be configured with various sensors to capture various damage or environmental data. The UGV and/or the UAVs may also transmit captured data to a central facility for processing. The UGV may serve as a mobile docking and recharging platform for the UAVs and may therefore extend the range and endurance of the UAVs. The UGV may be configured for remote operation, thus eliminating the need to send personnel into a potentially dangerous environment.

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 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: A method and system may assess the damage to 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 affected by a catastrophe and having a large concentration of 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 the extent and/or severity of the damage may be automatically determined based on the received aerial images. The aerial images along with indications of the extent of the damage may be displayed.

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: 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: A method and system may assess the damage to insured properties in a neighborhood using aerial images captured from an unmanned aerial vehicle (UAV), a manned aerial vehicle (MAV) or from a satellite device. Specifically, a neighborhood that has been affected by a natural or man-made disaster may be identified for assessing damage. The UAV, MAV, or satellite device may then capture aerial images within an area which surrounds the identified neighborhood. Subsequently, the aerial images may be analyzed to identify insured properties, and determine a condition and the extent and/or severity of the damage to each insured property. Furthermore, the aerial images along with indications of the extent of the damage to each insured property may be displayed on a computing device.

Abstract: A crash detection system is disclosed that utilizes a mobile computing device to detect a vehicular accident via one or more sensors integrated into the mobile computing device. The system monitors the sensor metrics measured by one or more sensors and generates an event sensor profile that may include the plurality of sensor metrics and additional status data, such as an indication of whether the mobile computing device was located within a vehicle when the event occurred. By comparing the plurality of sensor metrics to other crash sensor metrics, a determination may be made whether the event requires emergency assistance, which may be confirmed by determining whether the data included in the event sensor profile meets one or more exception conditions. If the event requires emergency assistance and an exception condition is not met, the mobile computing device may place a call to the appropriate emergency response personnel.

Abstract: A method and system may display real-time aerial images of insured properties in a neighborhood captured from an unmanned aerial vehicle (UAV), a manned aerial vehicle (MAV), or from a satellite device. For example, a neighborhood which has been affected by a catastrophe and has a large concentration of properties which are insured by a particular insurance provider may be identified. Aerial images of the entire neighborhood may then be received from the UAV, MAV, or the satellite device. As a result, the property owner may receive a notification that a catastrophe has impacted her neighborhood. The notification may also indicate that real-time images of the owner's property may be viewable by logging in to a customer account. Moreover, the real-time images may be transmitted via a web page to the property owner's web-enabled device after the property owner logs in to the customer account.

Abstract: Systems and methods for using unassisted vehicles to assess damage in a particular location are described. According to certain aspects, the systems and methods may utilize an unmanned ground vehicle (UGV) and a plurality of unmanned aerial vehicles (UAVs). The UGV and the UAVs may be configured with various sensors to capture various damage or environmental data. The UGV and/or the UAVs may also transmit captured data to a central facility for processing. The UGV may serve as a mobile docking and recharging platform for the UAVs and may therefore extend the range and endurance of the UAVs. The UGV may be configured for remote operation, thus eliminating the need to send personnel into a potentially dangerous environment.

Abstract: Systems and methods for monitoring a local environment for abnormal conditions (e.g., burglary, intrusion, fire, or flooding) are disclosed. Sensors of a smartphone, tablet computer, or other computing device may be used to obtain sensor data regarding the environment. Such sensor data may relate to sounds, temperatures, lighting, or other conditions within the environment. The observed environmental conditions may be compared against reference levels or patterns to determine abnormal conditions. When abnormal conditions are identified, a response may be determined and implemented, such as alerting a user or contacting an emergency service (e.g., police or fire services). In some circumstances, a training period may be used to determine baseline or threshold levels of normal environmental conditions. Different modes or profiles may be used, which may be associated with different environments (e.g., home, hotel, etc.).

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 having a large concentration of 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, and the aerial images along with indications of the level of risk may be displayed.

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.