RF beacon proximity determination enhancement
US-10231440-B2 · Mar 19, 2019 · US
US12382933B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12382933-B2 |
| Application number | US-202418811492-A |
| Country | US |
| Kind code | B2 |
| Filing date | Aug 21, 2024 |
| Priority date | Sep 5, 2023 |
| Publication date | Aug 12, 2025 |
| Grant date | Aug 12, 2025 |
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The present disclosure relates to the monitoring feeding behavior(s) of a pet(s), under the control of at least one processor. An example method includes obtaining load data from a load sensor of a pet bowl while the pet is interacting with contents of the pet bowl. The load sensor can have a sensitivity of +/−50 grams or less and the load data is obtained can occur at a sample rate from 10 samples to 150 samples per second. The example method can also include sequentially grouping the load data in 0.01 second to 5 second time increments, wherein individual time increments include multiple samples, and identifying a feeding behavior occurring within one or more of the time increments based on the load data resulting from the pet interacting with the pet bowl or the contents of the pet bowl.
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What is claimed is: 1. A method of monitoring feeding behavior of a pet, under the control of at least one processor, comprising: obtaining load data from a load sensor of a pet bowl while the pet is interacting with contents of the pet bowl, wherein the load sensor has a sensitivity of +/−50 grams or less and the load data is obtained at a sample rate from 10 samples to 150 samples per second; sequentially grouping the load data in 0.01 second to 5 second time increments, wherein individual time increments include multiple samples; and identifying a feeding behavior occurring within one or more of the time increments based on the load data resulting from the pet interacting with the pet bowl or the contents of the pet bowl. 2. The method of claim 1 , further comprising excluding load data in identifying the feeding behavior if determined to be a result of human interaction, a false trigger, or an accidental interaction with the pet bowl or the contents of the pet bowl. 3. The method of claim 1 , wherein the feeding behavior is a count-based feeding behavior selected from lapping, licking, or biting. 4. The method of claim 3 , further comprising characterizing the count-based feeding behavior by counting individual micro-events of the feeding behavior within a single time increment or a time period spanning multiple time increments, wherein the individual micro-events include individual laps, individual licks, or individual bites. 5. The method of claim 4 , wherein characterizing the count-based feeding behavior includes characterizing periods of time spanning one or multiple time increments where the count-based behavior is not occurring. 6. The method of claim 1 , wherein the feeding behavior is a duration-based behavior selected from the pet touching the bowl, moving the bowl, nosing the food, pausing, eating, lapping, licking, or biting. 7. The method of claim 6 , further comprising characterizing the duration-based feeding behavior by sequentially mapping the time increments in which the duration-based behavior occurs or is not occurring. 8. The method of claim 1 , further comprising notifying a custodian of the pet of the feeding behavior or a change in the pet feeding behavior. 9. The method of claim 8 , wherein notifying the custodian of the pet includes warning the custodian that the changes in the pet feeding behavior may be correlated to a potential health or behavior issue. 10. The method of claim 1 , further comprising obtaining secondary data from a secondary sensor associated with the pet bowl, wherein the secondary sensor includes a proximity sensor, a camera, a microphone, an accelerometer, a gyroscope, an inertial measurement unit sensor, or a combination thereof. 11. The method of claim 1 , wherein the pet bowl is a dog water bowl, and wherein the load sensor has a sensitivity of +/−4 grams or less, the sample rate is from 15 samples to 75 samples per second, and the time increments are at least about 0.4 second. 12. The method of claim 1 , wherein the pet bowl is a dog food bowl, and wherein the load sensor has a sensitivity of +/−4 grams or less, the sample rate is from 15 samples to 75 samples per second, and the time increments are at least about 0.3 second. 13. The method of claim 1 , wherein the pet bowl is a cat water bowl, and wherein the load sensor has a sensitivity of +/−2 grams or less, the sample rate is from 15 samples to 75 samples per second, and the time increments are at least about 0.4 second. 14. The method of claim 1 , wherein the pet bowl is a cat food bowl, and wherein the load sensor has a sensitivity of +/−2 grams or less, the sample rate is from 15 samples to 75 samples per second, and the time increments are at least about 0.3 second. 15. The method of claim 1 , further comprising generating a feeding behavior model for the pet, including identifying the feeding behavior of the pet based on frequency of feeding, pet feeding signature behaviors, or a combination thereof. 16. The method of claim 1 , further comprising identifying an identity of a pet in a multi-pet household. 17. A non-transitory machine readable storage medium having instructions embodied thereon, the instructions when executed cause a processor to perform a method of monitoring feeding behavior of a pet, comprising: obtaining load data from a load sensor of a pet bowl while the pet is interacting with the contents of the pet bowl, wherein the load sensor has a sensitivity of +/−50 grams or less and the load data is obtained at a sample rate from 10 to 150 samples per second; sequentially grouping the load data in 0.01 second to 5 second time increments, wherein individual time increments include multiple samples; and identifying a feeding behavior occurring within one or more of the time increments based on the load data resulting from the pet interacting with the pet bowl or the contents of the pet bowl. 18. The non-transitory machine readable storage medium of claim 17 , wherein monitoring feeding behavior of the pet includes monitoring a count-based feeding behavior selected from lapping, licking, or biting. 19. The non-transitory machine readable storage medium of claim 17 , wherein monitoring feeding behavior of the pet includes monitoring a duration-based behavior selected from touching the bowl, moving the bowl, nosing the food, pausing, eating, lapping, licking, or a combination thereof. 20. The non-transitory machine readable storage medium of claim 17 , wherein monitoring feeding behavior of the pet includes notifying a custodian of the pet of: the feeding behavior, a change in the feeding behavior, a potential health issue associated with the feeding behavior, or a combination thereof. 21. The non-transitory machine readable storage medium of claim 17 , wherein the load sensor has a sensitivity of +/−4 grams or less, the sample rate is from 15 samples to 75 samples per second and the time increments are at least about 0.3 second. 22. The non-transitory machine readable storage medium of claim 17 , wherein monitoring feeding behavior of the pet includes identifying the pet for monitoring when the pet is from a multi-pet household.
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