Patent Issued for Systems and methods for evaluating location data (USPTO 11715563): Massachusetts Mutual Life Insurance Company

2023 AUG 21 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- From Alexandria, Virginia, NewsRx journalists report that a patent by the inventors Fox, Adam (Springfield, MA, US), Maier, Marc (Springfield, MA, US), Merritt, Sears (Groton, MA, US), filed on January 6, 2020, was published online on August 1, 2023.

The patent’s assignee for patent number 11715563 is Massachusetts Mutual Life Insurance Company (Springfield, Massachusetts, United States).

News editors obtained the following quote from the background information supplied by the inventors: “Many health-related consumer protection companies may require health information from consumers for underwriting. Traditionally, the customers may be presented an initial questionnaire, which typically asks general questions related to age, weight, medical history, and the like. However, the customers may need to undergo medical examinations, which typically involve collecting body fluids and different physical measurements. However, collecting such data is often a problem for the customers for a variety of physical and/or psychological reasons and is often a major barrier to health-related customer protection companies and institutions attempting to enroll new customers. More particularly, the consumers often do not want to have blood drawn for fear of needles, do not want to undergo medical screening, do not have the time, and many other reasons.

“The problems associated with transfer and pooling of risk are integral elements in the operation of life insurance systems. By grouping individuals’ risk, the insurance systems are able to cover losses based on possibly future arising risks, out of a common pool of resources captured by the insurance systems. However, in order to maintain some degree of equity among individuals exhibiting different mortality risks, the insurance systems must capture, assess and classify risk of applicants for life insurance according to appropriate criteria or risk factors. While traditional underwriting practice has been to require applicants for life insurance to undergo medical examinations, including collection of body fluids and various physical measurements and analysis of risk factors based on these inputs; in the present disclosure such risk factors are sometimes called but this can be a barrier to enrolling new customers for reasons previously mentioned. What is needed is improve methods for predictive modeling of mortality for applicants for financial products such as life insurance.”

As a supplement to the background information on this patent, NewsRx correspondents also obtained the inventors’ summary information for this patent: “While the traditional medical examinations may be inconvenient and time consuming, the increasingly pervasive passive sensors may provide a new way to estimate customer risk and improve the overall user experience. The sensors may be deployed in a building or office space and generate micro-location data for the customers/users. The micro-location data may replace the lab data on body fluids (e.g., blood sample, urine sample). The micro-location may provide valuable information on a user’s health status.

“For the aforementioned reasons, there is a desire for a more efficient system and method for evaluating customer health and risk by collecting and analyzing micro-location data of the users. Discussed herein are systems and methods for collecting micro-location data from sensors over a period, training an artificial intelligence model on historical data, determining a health score based on the micro-location data using the artificial intelligence model, and determining a recommendation of products or a premium based on the health score.

“In an embodiment, a method comprises periodically monitoring, by a server, location information of a plurality of users by periodically receiving, from an application executing on a mobile device of each user, location signals emitted by a plurality of beacons; continuously updating, by the server, a user activity profile for each user containing a movement pattern representative of the user and based on the location information monitored via the plurality of beacons, a distance traveled within a predetermined time period, and a time spent at a pre-determined location; generating, by the server, an activity score for each user based on the movement pattern in each user’s activity profile; executing, by the server, an artificial intelligence model to determine a health score associated with each user, the artificial intelligence model is trained based on historical data associated with a set of at least one of existing and past users, wherein the artificial intelligence model is configured to, upon receiving a user’s activity score, determine an estimated health score of that user; when the health score satisfies a threshold, determine, by the server using a predetermined pricing algorithm, a premium for each user based on each user’s health score; and when the health score does not satisfy a threshold, routing the user’s activity profile to an electronic device.

“In another embodiment, a method comprises monitoring, by a server, location information of a plurality of users, using location signals received from a plurality of sensors, wherein each of the plurality of sensors is configured to receive signals from a beacon when the beacon is within a predetermined distance from the sensor, wherein the beacon is configured to attach to each user and constantly transmit a signal; continuously generating, by the server, a user activity profile for each user containing a movement pattern representative of the user and based on the location information monitored via the plurality of beacons, a distance traveled within a predetermined time period, and a time spent at a pre-determined location; generating, by the server, an activity score for each user based on the movement pattern in each user’s activity profile; executing, by the server, an artificial intelligence model to determine a health score associated with the user, the artificial intelligence model is trained based on historical data associated with a set of existing or past users, wherein the artificial intelligence model is configured to, upon receiving a user’s activity score, determine an estimated health score of that user; when the health score satisfies a threshold, determining, by the server using a predetermined pricing algorithm, a premium for each user based on each user’s health score; and when the health score does not satisfy a threshold, routing the user’s activity profile to an electronic device.

“It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory and are intended to provide further explanation of the invention as claimed.”

The claims supplied by the inventors are:

“1. A method comprising: periodically monitoring, by a server, location information of a plurality of users by periodically receiving, from an application executing on a mobile device of each user, location signals emitted by a plurality of beacons; continuously updating, by the server, a user activity profile for each user containing a movement pattern representative of the user and based on the location information monitored via the plurality of beacons, a distance traveled within a predetermined time period, and a time spent at a pre-determined location; generating, by the server, an activity score for each user based on the movement pattern in each user’s activity profile; executing, by the server, an artificial intelligence model to determine a health score associated with each user, the artificial intelligence model is trained based on historical activity data associated with a set of at least one of existing and past users, wherein the artificial intelligence model is configured to, upon receiving a user’s activity score, determine an estimated health score of that user; when the health score satisfies a threshold, determining, by the server using a predetermined pricing algorithm, a premium for each user that corresponds to each user’s health score; when the health score does not satisfy a threshold, routing the user’s activity profile to an electronic device; and upon receiving an updated health score for the user, dynamically updating, by the server, the artificial intelligence model based on the updated health score and the health score.

“2. The method of claim 1, wherein the user activity profile comprises health attributes, habits, lifestyles, behaviors, and activities.

“3. The method of claim 2, further comprising: determining, by the server, the health attributes of the user by executing the artificial intelligence model based on the location information.

“4. The method of claim 2, further comprising: determining, by the server, behaviors by aggregating each user’s location information at different timestamps.

“5. The method of claim 1, further comprising: determining, by the server, a mortality risk based on the user’s activity profile.

“6. The method of claim 1, further comprising: iteratively training, by the server, the artificial intelligence model each time an erroneous health score is identified.

“7. The method of claim 1, further comprising: determining, by the server, micro-locations of each user by mapping the location information to a region of a predetermined space.

“8. The method of claim 1, wherein the location information is in JavaScript Object Notation (JSON) format.

“9. The method of claim 1, further comprising: determining, by the server, the location information of each user based on a strength of the location signals emitted by the plurality of beacons.

“10. A method comprising: monitoring, by a server, location information of a plurality of users, using location signals received from a plurality of sensors, wherein each sensor of the plurality of sensors is configured to receive signals from a beacon within a plurality of beacons when the beacon is within a predetermined distance from the sensor, wherein the beacon is configured to attach to each user and constantly transmit a signal; continuously generating, by the server, a user activity profile for each user containing a movement pattern representative of the user and based on the location information monitored via the plurality of beacons, a distance traveled within a predetermined time period, and a time spent at a pre-determined location; generating, by the server, an activity score for each user based on the movement pattern in each user’s activity profile; executing, by the server, an artificial intelligence model to determine a health score associated with the user, the artificial intelligence model is trained based on historical data associated with a set of existing or past users, wherein the artificial intelligence model is configured to, upon receiving a user’s activity score, determine an estimated health score of that user; when the health score satisfies a threshold, determining, by the server using a predetermined pricing algorithm, a premium for each user based on each user’s health score; when the health score does not satisfy a threshold, routing the user’s activity profile to an electronic device; and upon receiving an updated health score for the user, dynamically updating, by the server, the artificial intelligence model based on the updated health score and the health score.

“11. The method of claim 10, wherein the user activity profile comprises health attributes, habits, lifestyles, behaviors, and activities.

“12. The method of claim 11, further comprising: determining, by the server, the health attributes of the user by executing the artificial intelligence model based on the location information.

“13. The method of claim 11, further comprising: determining, by the server, behaviors by aggregating each user’s location information at different timestamps.

“14. The method of claim 10, further comprising: determining, by the server, a mortality risk based on the user’s activity profile.

“15. The method of claim 10, further comprising: determining, by the server, biometric parameters that are measured by collecting body fluid based on the location information.

“16. The method of claim 10, further comprising: determining, by the server, micro-locations of each user by mapping the location information to a region of a predetermined space.

“17. The method of claim 10, wherein the location information is in JavaScript Object Notation (JSON) format.

“18. A computer system comprising: a plurality of beacons where each beacon is configured to broadcast location signals; a plurality of mobile devices operated by a plurality of users where each mobile device is configured to receive location signals from at least one beacon; a server in communication with at least the plurality of mobile devices, the server configured to: periodically monitor location information of the plurality of users by periodically receiving, from an application executing on a mobile device of each user, location signals emitted by the plurality of beacons; continuously update a user activity profile for each user containing a movement pattern representative of the user and based on the location information monitored via the plurality of beacons, a distance traveled within a predetermined time period, and a time spent at a pre-determined location; generate an activity score for each user based on the movement pattern in each user’s activity profile; execute an artificial intelligence model to determine a health score associated with each user, the artificial intelligence model is trained based on historical activity data associated with a set of at least one of existing and past users, wherein the artificial intelligence model is configured to, upon receiving a user’s activity score, determine an estimated health score of that user; when the health score satisfies a threshold, determining, by the server using a predetermined pricing algorithm, a premium for each user that corresponds to each user’s health score; when the health score does not satisfy a threshold, routing the user’s activity profile to an electronic device; and upon receiving an updated health score for the user, dynamically update the artificial intelligence model based on the updated health score and the health score.

“19. The computer system of claim 18, wherein the user activity profile comprises health attributes, habits, lifestyles, behaviors, and activities.

“20. The computer system of claim 19, wherein the server is further configured to: determine the health attributes of the user by executing the artificial intelligence model based on the location information.”

For additional information on this patent, see: Fox, Adam. Systems and methods for evaluating location data. U.S. Patent Number 11715563, filed January 6, 2020, and published online on August 1, 2023. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(11715563)&db=USPAT&type=ids

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