Abstract: Systems and methods of the present disclosure include receiving an aerial image that includes a view of property (e.g., real property, personal property, or other types of property), automatically identifying the property included in the aerial image, automatically determining one or more characteristics of the property based at least in part on the aerial image, and automatically adjusting an insurance policy term for an insurance policy relating to the property based at least in part on the one or more characteristics of the property. Certain embodiments include automatically determining the one or more characteristics of the property also based at least in part on data received from one or more smart home devices associated with the property, one or more public records relating to the property, a supplemental image accessed from a camera located in or around the property, and so forth.

Abstract: A system includes a monitoring device coupled to a vehicle. The monitoring device includes a processor. The monitoring device also includes an output interface coupled to the processor that communicates information to a driver of the vehicle. The monitoring device further includes a communication interface coupled to the processor. The processor receives, via the communication interface, sensor information relating to operating the vehicle. The processor also receives, via the communication interface, a risk factor relating to operating the vehicle based at least in part on the sensor information. The processor further outputs, via the output interface, an adjustment to an insurance premium of the driver, an adjustment to an insurance deductible of the driver, or a payment amount of the driver, based at least in part on the risk factor.

Abstract: The present disclosure relates to analyzing data related to smart home activity that is useful to risk analysis, service cost determination/adjustment, and behavioral incentivization. A monitoring system may acquire maintenance information, contextual information, and/or financial information with minimal user input to assess risk associated with user behavior and home activity associated with a smart home. Based on generating a risk factor associated with the smart home, the monitoring system may provide a user with an accurate service cost (e.g., home insurance quote) related to the smart home activity.

Abstract: An audio modification system includes one or more processors configured to receive audio data indicative of communication of a user while the user is positioned in a first portion of a control area, determine that the communication of the user is confidential based on the audio data, determine generated audio data configured to render the communication of the user at least partially inaudible in a second portion of the control area, and output a control signal indicative of instructions to provide the generated audio data.

Abstract: A textured window film has a prismatic effect that allows a substantial amount of incoming light to pass through a window while refracting the light at random or semi-random angles in a manner that distorts viewed images. The result is a window film that is brighter and more vibrant while also providing visual privacy. The textured window film can therefore better simulate real textured and colored glass.

Abstract: A system may include a vehicle system configured to monitor one or more monitor variables related to a vehicle. The system may also include a processor that may receive a selection of the one or more monitor variables to monitor and receive data from the vehicle system. The data may be limited based on the selection of the one or more monitor variables. The processor may then determine a fixed rate premium for at least two years based on the data and display a visualization that may include the fixed rate premium on a display.

Abstract: A system includes a computing device comprising a memory storing instructions configured to cause a processor to receive: purchase data associated with products purchased by a user, online activity data performed by the user and other users and associated with information pertaining to the products, and vendor information comprising retail sales data, after-market sales data, and product availability associated with the products. The processor determines one or more values of the products based on the purchase data, the online activity data, and the vendor information and whether the purchased products correspond to specialty products based on the purchase data, the online activity data, and the values of the products. The processor may then send a notification to the user comprising an offer for insurance for the products in response to determining the products correspond to specialty products.

Abstract: A system may include a vehicle system configured to monitor one or more monitor variables related to a vehicle. The system may also include a processor that may receive a selection of the one or more monitor variables to monitor and receive data from the vehicle system. The data may be limited based on the selection of the one or more monitor variables. The processor may then determine a fixed rate premium for at least two years based on the data and display a visualization that may include the fixed rate premium on a display.

Abstract: The present disclosure is related to a method for a monitor system containing a processor that may receive position data from one or more sensors associated with one or more electronic devices. The position data may represent the devices' various locations over time. The monitor system may determine whether the locations represented by the position data correspond to expected locations generated by a predictive model. After determining that the locations and expected locations do not correspond to one another, the monitor system may send an alert to a computing device.

Abstract: Techniques are described for adjusting policy characteristics based on a determined similarity between routes. A similarity metric may be determined indicating the similarity between a first route followed by a vehicle and/or driver and a second (e.g., previous) route followed by the vehicle and/or driver. A similarity metric may indicate the similarity in movements, and changes in movement, exhibited by the vehicle on the routes. The similarity metric may be determined through analysis of real time data collected by in-vehicle sensor(s), mobile user device(s), external sensors or other data sources. Based on the similarity metric, a premium, a deductible, a price, or other characteristic(s) of a policy may be determined. In some examples, policy characteristics may be adjusted (e.g., in real time) based on the analysis according to changing risk conditions if a driver is following routes that are dissimilar from typical routes.

Abstract: Systems and methods of the present disclosure include receiving an aerial image that includes a view of property (e.g., real property, personal property, or other types of property), automatically identifying the property included in the aerial image, automatically determining one or more characteristics of the property based at least in part on the aerial image, and automatically adjusting an insurance policy term for an insurance policy relating to the property based at least in part on the one or more characteristics of the property. Certain embodiments include automatically determining the one or more characteristics of the property also based at least in part on data received from one or more smart home devices associated with the property, one or more public records relating to the property, a supplemental image accessed from a camera located in or around the property, and so forth.

Abstract: Systems and methods of the present disclosure include receiving an aerial image that includes a view of property (e.g., real property, personal property, or other types of property), automatically identifying the property included in the aerial image, automatically determining one or more characteristics of the property based at least in part on the aerial image, and automatically adjusting an insurance policy term for an insurance policy relating to the property based at least in part on the one or more characteristics of the property. Certain embodiments include automatically determining the one or more characteristics of the property also based at least in part on data received from one or more smart home devices associated with the property, one or more public records relating to the property, a supplemental image accessed from a camera located in or around the property, and so forth.

Abstract: A system includes a monitoring device coupled to a vehicle. The monitoring device includes a processor. The monitoring device also includes an output interface coupled to the processor that communicates information to a driver of the vehicle. The monitoring device further includes a communication interface coupled to the processor. The processor receives, via the communication interface, sensor information relating to operating the vehicle. The processor also receives, via the communication interface, a risk factor relating to operating the vehicle based at least in part on the sensor information. The processor further outputs, via the output interface, an adjustment to an insurance premium of the driver, an adjustment to an insurance deductible of the driver, or a payment amount of the driver, based at least in part on the risk factor.

Abstract: Techniques are described for adjusting policy characteristics based on a determined similarity between routes. A similarity metric may be determined indicating the similarity between a first route followed by a vehicle and/or driver and a second (e.g., previous) route followed by the vehicle and/or driver. A similarity metric may indicate the similarity in movements, and changes in movement, exhibited by the vehicle on the routes. The similarity metric may be determined through analysis of real time data collected by in-vehicle sensor(s), mobile user device(s), external sensors or other data sources. Based on the similarity metric, a premium, a deductible, a price, or other characteristic(s) of a policy may be determined. In some examples, policy characteristics may be adjusted (e.g., in real time) based on the analysis according to changing risk conditions if a driver is following routes that are dissimilar from typical routes.

Abstract: Techniques are described for adjusting policy characteristics based on a determined similarity between routes. A similarity metric may be determined indicating the similarity between a first route followed by a vehicle and/or driver and a second (e.g., previous) route followed by the vehicle and/or driver. A similarity metric may indicate the similarity in movements, and changes in movement, exhibited by the vehicle on the routes. The similarity metric may be determined through analysis of real time data collected by in-vehicle sensor(s), mobile user device(s), external sensors or other data sources. Based on the similarity metric, a premium, a deductible, a price, or other characteristic(s) of a policy may be determined. In some examples, policy characteristics may be adjusted (e.g., in real time) based on the analysis according to changing risk conditions if a driver is following routes that are dissimilar from typical routes.

Abstract: Systems and methods can leverage images of remotely captured items to extract information, populate forms, authenticate users, and perform other actions.

Abstract: A system includes a monitoring device coupled to a vehicle. The monitoring device includes a communication interface and one or more processors coupled to the communication interface. The one or more processors receive, via the communication interface, sensor information relating to operating the vehicle. The one or more processors also receive, via the communication interface, contextual information based at least in part on the sensor information relating to operating the vehicle. The one or more processors further generate a risk factor relating to operating the vehicle based at least in part on the sensor information and the contextual information.

Abstract: A system includes a monitoring device coupled to a vehicle. The monitoring device includes a processor. The monitoring device also includes an output interface coupled to the processor that communicates information to a driver of the vehicle. The monitoring device further includes a communication interface coupled to the processor. The processor receives, via the communication interface, sensor information relating to operating the vehicle. The processor also receives, via the communication interface, a risk factor relating to operating the vehicle based at least in part on the sensor information. The processor further outputs, via the output interface, an adjustment to an insurance premium of the driver, an adjustment to an insurance deductible of the driver, or a payment amount of the driver, based at least in part on the risk factor.

Abstract: A system may include a vehicle system configured to monitor one or more monitor variables related to a vehicle. The system may also include a processor that may receive a selection of the one or more monitor variables to monitor and receive data from the vehicle system. The data may be limited based on the selection of the one or more monitor variables. The processor may then determine a fixed rate premium for at least two years based on the data and display a visualization that may include the fixed rate premium on a display.

Abstract: Techniques are described for adjusting policy characteristics based on a determined similarity between routes. A similarity metric may be determined indicating the similarity between a first route followed by a vehicle and/or driver and a second (e.g., previous) route followed by the vehicle and/or driver. A similarity metric may indicate the similarity in movements, and changes in movement, exhibited by the vehicle on the routes. The similarity metric may be determined through analysis of real time data collected by in-vehicle sensor(s), mobile user device(s), external sensors or other data sources. Based on the similarity metric, a premium, a deductible, a price, or other characteristic(s) of a policy may be determined. In some examples, policy characteristics may be adjusted (e.g., in real time) based on the analysis according to changing risk conditions if a driver is following routes that are dissimilar from typical routes.