Patent Issued for Connected home system with risk units (USPTO 11783423): Allstate Insurance Company

2023 NOV 01 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Allstate Insurance Company (Northbrook, Illinois, United States) has been issued patent number 11783423, according to news reporting originating out of Alexandria, Virginia, by NewsRx editors.

The patent’s inventors are Bohacz, Trent (Northbrook, IL, US), Klingel, Peggy (Northbrook, IL, US), Mercado, Orlando E. (Rolling Meadows, IL, US), Moats, John Bradley (Gurnee, IL, US), Pellouchoud, Laurie (Northbrook, IL, US), Snyder, Jennifer L. (Northbrook, IL, US), Tyner, Ralph Adam Benjamin (Gurnee, IL, US), Yager, Floyd M. (Park Ridge, IL, US).

This patent was filed on December 16, 2019 and was published online on October 10, 2023.

From the background information supplied by the inventors, news correspondents obtained the following quote: “People are often looking for ways to protect their homes. People buy insurance for exactly that reason-to protect against unforeseen risks. In conventional arrangements, it may be difficult or impossible to know when a failure of a home device may occur that may lead to damage to the home, an insurance claims etc. In addition, homes located in the same neighborhood may be exposed to similar risks such as damage from weather events or neighborhood crime. For example, roof damage from a storm event on one home in a neighborhood may indicate potential damage of other roofs of homes in the same neighborhood. Without accurate information associated with a particular home or neighborhood of homes an insurance company might not be able to accurately assess neighborhood risk and the impact of such risk. This may result in an insurance premium that is based on a generic risk assessment, rather than a risk assessment tailored to the specific home in a specific neighborhood.”

Supplementing the background information on this patent, NewsRx reporters also obtained the inventors’ summary information for this patent: “Aspects of the disclosure generally relate to monitoring and/or sensing of one or more home devices from one or more homes. In particular, various aspects described herein relate to receiving data from one or more sensors associated with one or more home devices from one or more homes and using the data to determine insurance rates or premiums, discounts, incentives, and the like.

“Further, aspects of the disclosure relate to computer hardware and software. In particular, one or more aspects of the disclosure relate to the connected home or smart home market (i.e. connected devices and systems within or related to the home) which is rapidly evolving and growing.

“According to an embodiment, a connected home system may comprise a processing unit comprising a processor; and a memory unit storing computer-executable instructions, which when executed by the processing unit, cause the connected home system to: receive first data from signals received from one or more first sensing devices; receive second data from signals received from one or more second sensing devices; aggregate the first data and the second data; assign in real-time one or more home risk units based on the first data and the one or more home devices in the home; assign in real-time one or more user risk units based on the second data associated with the user and user’s behavior in the home; aggregate in real-time the home risk units and the user risk units to determine an overall risk units associated with the user; generate an insurance premium for the user based on the overall risk units associated with the user; and update in real-time the insurance premium for the user based on any changes to the home risk units, the user risk units, and the overall risk units associated with the user. The one or more first sensing devices may be in communication with a digital network in a home and one or more home devices associated with a user. The first data may comprise operating characteristics of the one or more home devices. The one or more second sensing devices may in communication with the digital network in the home and the second data associated with the user and user’s behavior in the home.

“In further aspects, the connected home system may include the following features. The first data may include one or more of the following: kilowatt hours used, gallons of water flowing into the home, sump pump usage, amount of natural gas used, or an average temperature in the home. The second data may include one or more of the following: megabytes of data flowing through a router of the digital network, number of times a garage door opens and closes, number of time a front door opens and closes, amount of time an alarm system is activated, or loads of dishes/laundry done. Further, the connected home system may: receive third data from signals received from third sensing devices comprising operation parameters of a vehicle; aggregate in real-time the first data, the second data, and the third data; and update in real-time the insurance premium for the user, wherein the insurance premium is adjusted in real-time based on whether the user is located at the home or the vehicle, and the updated insurance premium is based on the first data and the second data for the home and the third data for the vehicle. Additionally, the connected home system may: maintain and aggregate historical first data about the home from previous owners that includes the first data aggregated over time from the first sensing devices; maintain and aggregate historical second data about the user that includes the second data aggregated over time from the user and the user’s behavior in previous homes; and generate a new insurance premium for the user and a new home based on the historical first data. Further, the insurance premium may include a coverage amount for a cost of coverage and a preventative amount for one or more preventative tasks for the home based on the first data and operating characteristics of the one or more home devices. Additionally, the connected home system may provide and integrate a digital safety program based on the first data and the operating characteristics of the one or more home devices and the second data associated with the user and user’s behavior in the home.

“According to another embodiment, a method for a connected home system, may comprise the following steps: receiving first data from signals received from one or more first sensing devices, the one or more first sensing devices being in communication with a digital network in a home and one or more home devices associated with a user, the first data comprising operating characteristics of the one or more home devices; receiving second data from signals received from one or more second sensing devices, the one or more second sensing devices in communication with the digital network in the home and the second data associated with the user and user’s behavior in the home; aggregating the first data and the second data; assigning in real-time one or more home risk units based on the first data and the one or more home devices in the home; assigning in real-time one or more user risk units based on the second data associated with the user and user’s behavior in the home; aggregating in real-time the home risk units and the user risk units to determine an overall risk units associated with the user; generating an insurance premium for the user based on the overall risk units associated with the user; and updating the insurance premium for the user based on any changes to the home risk units, the user risk units, and the overall risk units associated with the user.”

The claims supplied by the inventors are:

“1. A connected home system comprising: a processing unit comprising a processor; and a non-transitory memory unit storing computer-executable instructions, which when executed by the processing unit, cause the connected home system to: receive first data from one or more first sensing devices, the first data comprising operating characteristics of one or more home devices in a home; receive second data from one or more second sensing devices, the second data indicating a behavior of a user in the home; determine in real-time, using a machine learning algorithm operating on the processor, one or more home risk units based on the first data, wherein the machine learning algorithm learns one or more patterns from sensor feedback and is configured to determine the one or more home risk units by predicting a first pattern associated with the first data; determine in real-time, using the machine learning algorithm, one or more user risk units based on the second data, wherein the machine learning algorithm is configured to determine the one or more user risk units by predicting a second pattern associated with the second data; maintain historical first sensor data about the home from previous owners of the home; maintain historical second sensor data about a behavior of the user in one or more previous homes of the user; determine in real-time an overall risk value associated with the user based on the one or more home risk units, the one or more user risk units, the historical first sensor data, and the historical second sensor data; and generate an insurance premium for the user based on the overall risk value.

“2. The connected home system of claim 1, wherein the first data includes one or more of: kilowatt hours used, gallons of water flowing into the home, sump pump usage, amount of natural gas used, or an average temperature in the home.

“3. The connected home system of claim 1, wherein the second data includes one or more of: megabytes of data flowing through a router of a digital network, number of times a garage door opens and closes, number of time a front door opens and closes, amount of time an alarm system is activated, or loads of dishes or laundry done.

“4. The connected home system of claim 1, wherein the memory unit stores computer-executable instructions, which when executed by the processing unit, further cause the connected home system to: receive third data from third sensing devices comprising operation parameters of a vehicle, wherein the insurance premium is generated based on the third data.

“5. The connected home system of claim 1, wherein the insurance premium includes a coverage amount for a cost of coverage and a preventative amount for one or more preventative tasks for the home.

“6. The connected home system of claim 1, wherein the memory unit stores computer-executable instructions, which when executed by the processing unit, further cause the connected home system to: provide and integrate a digital safety program to protect the first data and the second data.

“7. A method, comprising: receiving, by a processor executing on a connected home sensing system, first data from one or more first sensing devices, the first data comprising operating characteristics of one or more home devices in a home; receiving, by the processor, second data from one or more second sensing devices, the second data indicating a behavior of a user in the home; determining in real-time, using a machine learning algorithm operating on the processor, one or more home risk units based on the first data, wherein the machine learning algorithm learns one or more patterns from sensor feedback and is configured to determine the one or more home risk units by predicting a first pattern associated with the first data; determining in real-time, using the machine learning algorithm, one or more user risk units based on the second data, wherein the machine learning algorithm is configured to determine the one or more user risk units by predicting a second pattern associated with the second data; maintaining, by the processor, historical first sensor data about the home from previous owners of the home; maintaining, by the processor, historical second sensor data about a behavior of the user in one or more previous homes of the user; determining in real-time an overall risk value associated with the user based on the one or more home risk units, the one or more user risk units, the historical first sensor data, and the historical second sensor data; and generating, by the processor, an insurance premium for the user based on the overall risk value.

“8. The method of claim 7, wherein the first data includes one or more of: kilowatt hours used, gallons of water flowing into the home, sump pump usage, amount of natural gas used, or an average temperature in the home.

“9. The method of claim 7, wherein the second data includes one or more of: megabytes of data flowing through a router of a digital network, number of times a garage door opens and closes, number of time a front door opens and closes, amount of time an alarm system is activated, or loads of dishes or laundry done.

“10. The method of claim 7, further comprising: receiving, by the processor, third data from third sensing devices comprising operation parameters of a vehicle, wherein the insurance premium is generated based on the third data.

“11. The method of claim 7, wherein the insurance premium includes a coverage amount for a cost of coverage and a preventative amount for one or more preventative tasks for the home.

“12. The method of claim 7, further comprising: providing and integrating, by the processor, a digital safety program to protect the first data and the second data.

“13. One or more non-transitory computer-readable media storing instructions that, when executed by a computing device, cause the computing device to: receive, by a processor executing on the computing device, first data from one or more first sensing devices, the first data comprising operating characteristics of one or more home devices in a home; receive, by the processor, second data from one or more second sensing devices, the second data indicating a behavior of a user in the home; determine in real-time, using a machine learning algorithm operating on the processor, one or more home risk units based on the first data, wherein the machine learning algorithm learns one or more patterns from sensor feedback and is configured to determine the one or more home risk units by predicting a first pattern associated with the first data; determine in real-time, using the machine learning algorithm, one or more user risk units based on the second data, wherein the machine learning algorithm is configured to determine the one or more user risk units by predicting a second pattern associated with the second data; maintain, by the processor, historical first sensor data about the home from previous owners of the home; maintain, by the processor, historical second sensor data about a behavior of the user in one or more previous homes of the user; determine, by the processor, in real-time an overall risk value associated with the user based on the one or more home risk units, the one or more user risk units, the historical first sensor data, and the historical second sensor data; and generate, by the processor, an insurance premium for the user based on the overall risk value.

“14. The one or more non-transitory computer-readable media of claim 13, wherein the instructions, when executed by the computing device, further cause the computing device to: receive, by the processor, third data from third sensing devices comprising operation parameters of a vehicle, wherein the insurance premium is generated based on the third data.

“15. The one or more non-transitory computer-readable media of claim 13, wherein the insurance premium includes a coverage amount for a cost of coverage and a preventative amount for one or more preventative tasks for the home.”

For the URL and additional information on this patent, see: Bohacz, Trent. Connected home system with risk units. U.S. Patent Number 11783423, filed December 16, 2019, and published online on October 10, 2023. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(11783423)&db=USPAT&type=ids

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