Sensing peripheral heuristic evidence, reinforcement, and engagement system

US12536889B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-12536889-B2
Application numberUS-202217969517-A
CountryUS
Kind codeB2
Filing dateOct 19, 2022
Priority dateApr 9, 2018
Publication dateJan 27, 2026
Grant dateJan 27, 2026

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  1. Title

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  2. Abstract

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  5. First independent claim

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  7. Citations and related patents

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Abstract

Official abstract text for this publication.

Systems and methods for identifying a condition associated with an individual in a home environment are provided. Sensors associated with the home environment detect data, which is captured and analyzed by a local or remote processor to identify the condition. In some instances, the sensors are configured to capture data indicative of electricity use by devices associated with the home environment, including, e.g., which devices are using electricity, what date/time electricity is used by each device, how long each device uses electricity, and/or the power source for the electricity used by each device. The processor analyzes the captured data to identify any abnormalities or anomalies, and, based upon any identified abnormalities or anomalies, the processor determines a condition (e.g., a medical condition) associated with an individual in the home environment. The processor generates and transmits a notification indicating the condition associated with the individual to a caregiver of the individual.

First claim

Opening claim text (preview).

What is claimed is: 1 . A computer-implemented method for identifying patterns associated with an individual in a home environment and periodically generating and transmitting indications of the patterns to a device associated with a caregiver of the individual, comprising: capturing data detected by a plurality of sensors associated with the home environment; analyzing, by one or more processors, the captured data using a neural network model trained using a dataset associated with the home environment, to identify one or more of sleep time patterns, wake time patterns, or breathing rate patterns associated with an individual in the home environment; and periodically generating and transmitting, by the one or more processors, to a device associated with a caregiver of the individual, notifications indicating the one or more of sleep time patterns, wake time patterns, or breathing rate patterns associated with the individual, wherein each notification comprises a snapshot report generated periodically and the snapshot report includes an indication of the one or more of sleep time patterns, wake time patterns, or breathing rate patterns associated with the individual and a change from a prior snapshot report. 2 . The computer-implemented method of claim 1 , wherein the plurality of sensors associated with the home environment include one or more sensors configured to capture data indicative of one or more of light, temperature, or moisture associated with the home environment. 3 . The computer-implemented method of claim 1 , wherein the plurality of sensors associated with the home environment include one or more sensors configured to capture data indicative of motion, eye movement, bed wetting, amount of time spent in bed, or wake time associated with the individual. 4 . The computer-implemented method of claim 1 , further comprising: analyzing, by the one or more processors, over a period of time, the data detected by the plurality of sensors to identify one or more patterns in the data; and comparing, by the one or more processors, the data detected by the plurality of sensors to the identified patterns in the data in order to identify instances in which the data detected by the plurality of sensors is inconsistent with the identified patterns. 5 . The computer-implemented method of claim 1 , wherein identifying the one or more of sleep time patterns, wake time patterns, or breathing rate patterns associated with the individual in the home environment comprises: identifying, by the one or more processors, a condition associated with the one or more of sleep time patterns, wake time patterns, or breathing rate patterns associated with the individual. 6 . The computer-implemented method of claim 5 , wherein the condition associated with the individual is a medical condition. 7 . The computer-implemented method of claim 6 , wherein the condition associated with the individual is an emergency medical condition, the computer-implemented method further comprising: requesting, by the one or more processors, based upon the emergency medical condition, an emergency service to be provided to the individual. 8 . A computer system for identifying patterns associated with an individual in a home environment and periodically generating and transmitting indications of the patterns to a device associated with a caregiver of the individual, comprising: one or more sensors associated with the home environment; one or more processors configured to interface with the one or more sensors; and one or more memories storing instructions that, when executed by the one or more processors, cause the computer system to: capture data detected by the one or more sensors; analyze the captured data using a neural network model trained using a dataset associated with the home environment, to identify one or more of sleep time patterns, wake time patterns, or breathing rate patterns associated with an individual in the home environment; and periodically generate and transmit, to a device associated with a caregiver of the individual, notifications indicating the one or more of sleep time patterns, wake time patterns, or breathing rate patterns associated with the individual, wherein each notification comprises a snapshot report generated periodically and the snapshot report includes an indication of the one or more of sleep time patterns, wake time patterns, or breathing rate patterns associated with the individual and a change from a prior snapshot report. 9 . The computer system of claim 8 , wherein the one or more sensors associated with the home environment include one or more sensors configured to capture data indicative of one or more of light, temperature, or moisture associated with the home environment. 10 . The computer system of claim 8 , wherein the one or more sensors associated with the home environment include one or more sensors configured to capture data indicative of motion, eye movement, bed wetting, amount of time spent in bed, or wake time associated with the individual. 11 . The computer system of claim 8 , wherein the instructions, when executed by the one or more processors, further cause the computer system to: analyze, over a period of time, the data detected by the one or more sensors to identify one or more patterns in the data detected by the one or more sensors; and compare the data detected by the one or more sensors to the identified patterns in the data in order to identify instances in which the data detected by the one or more sensors is inconsistent with the identified patterns. 12 . The computer system of claim 8 , wherein the instructions, when executed by the one or more processors, cause the computer system to identify the one or more of sleep time patterns, wake time patterns, or breathing rate patterns associated with the individual in the home environment by: identifying a condition associated with the one or more of sleep time patterns, wake time patterns, or breathing rate patterns associated with the individual. 13 . The computer system of claim 12 , wherein the condition associated with the individual is a medical condition. 14 . The computer system of claim 13 , wherein the condition associated with the individual is an emergency medical condition, and wherein the instructions, when executed by the one or more processors, further cause the computer system to: request, based upon the emergency medical condition, an emergency service to be provided to the individual. 15 . A non-transitory computer-readable storage medium having stored thereon a set of instructions, executable by a processor, for identifying patterns associated with an individual in a home environment and periodically generating and transmitting indications of the patterns to a device associated with a caregiver of the individual, the set of instructions comprising instructions for: capturing data detected by a plurality of sensors associated with the home environment; analyzing the captured data using a neural network model trained using a dataset associated with the home environment, to identify one or more of sleep time patterns, wake time patterns, or breathing rate patterns associated with an individual in the home environment; and periodically generating and transmitting, to a device associated with a caregiver of the individual, notifications indicating the one or more of sleep time patterns, wake time patterns, or breathing rate patterns associated with the individual, wherein each notification comprises a snapshot report generated periodically and the snapshot report includes a

Assignees

Inventors

Classifications

  • ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring · CPC title

  • Cameras to detect unsafe condition, e.g. video cameras · CPC title

  • Presence detectors to detect unsafe condition, e.g. infrared sensor, microphone (G08B21/0476 takes precedence) · CPC title

  • detecting deviation from an expected pattern of behaviour or schedule · CPC title

  • Machine learning · CPC title

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Frequently asked questions

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What does patent US12536889B2 cover?
Systems and methods for identifying a condition associated with an individual in a home environment are provided. Sensors associated with the home environment detect data, which is captured and analyzed by a local or remote processor to identify the condition. In some instances, the sensors are configured to capture data indicative of electricity use by devices associated with the home environm…
Who is the assignee on this patent?
State Farm Mutual Automobile Insurance Co
What technology area does this patent fall under?
Primary CPC classification G08B21/0423. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Jan 27 2026 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 12 related publications on this page (citations in our corpus or others sharing the same primary CPC).