Noise/vibration reduction control
US-2018163650-A1 · Jun 14, 2018 · US
US10510220B1 · US · B1
| Field | Value |
|---|---|
| Publication number | US-10510220-B1 |
| Application number | US-201816056233-A |
| Country | US |
| Kind code | B1 |
| Filing date | Aug 6, 2018 |
| Priority date | Aug 6, 2018 |
| Publication date | Dec 17, 2019 |
| Grant date | Dec 17, 2019 |
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Embodiments for implementing intelligent alarm sound control by a processor. A targeted entity may be isolated for a generated sound to be delivered, while noise cancellation is simultaneously provided to prevent an alternative entity from being disturbed by the isolated sound.
Opening claim text (preview).
The invention claimed is: 1. A method for implementing intelligent alarm sound control by a processor, comprising: isolating a targeted entity for a generated sound to be delivered, while simultaneously providing noise cancellation to prevent an alternative entity from being disturbed by the generated sound; wherein the generated sound is activated and isolated within a cone of silence for a selected period of time, and the alternative entity located outside the cone of silence is shielded from the generated sound by initiating the noise cancellation for a duration beginning prior to the selected period of time until the target entity performs a certain action. 2. The method of claim 1 , further including providing the generated sound within the cone of silence for waking the targeted entity and preventing the alternative entity from being disturbed by the generated sound. 3. The method of claim 1 , further including pairing the noise cancellation with the generated sound according to a predictive frequency, volume, and wavelength. 4. The method of claim 1 , further including emitting a preset frequency and sound pattern for the generated sound. 5. The method of claim 4 , further including masking the preset frequency and the sound pattern for the generated sound by the noise cancellation. 6. The method of claim 1 , further including initiating a machine learning operation to learn a plurality of sleep preferences for each entity, historical sleeping activity patterns of the targeted entity, a cognitive state of the targeted entity, contextual factors, the one or more characteristics of the generated sound, feedback data collected from each entity, or a combination thereof. 7. A system for implementing intelligent alarm sound control, comprising: one or more computing components associated with the intelligent alarm sound control with executable instructions that when executed cause the system to: isolate a targeted entity for a generated sound to be delivered, while simultaneously provide noise cancellation to prevent an alternative entity from being disturbed by the generated sound; wherein the generated sound is activated and isolated within a cone of silence for a selected period of time, and the alternative entity located outside the cone of silence is shielded from the generated sound by initiating the noise cancellation for a duration beginning prior to the selected period of time until the target entity performs a certain action. 8. The system of claim 7 , wherein the executable instructions further provide the generated sound within the cone of silence for waking the targeted entity and prevent the alternative entity from being disturbed by the generated sound. 9. The system of claim 7 , wherein the executable instructions further pair the noise cancellation with the generated sound according to a predictive frequency, volume, and wavelength. 10. The system of claim 7 , wherein the executable instructions further emit a preset frequency and sound pattern for the generated sound. 11. The system of claim 10 , wherein the executable instructions further mask the preset frequency and the sound pattern for the generated sound by the noise cancellation. 12. The system of claim 7 , wherein the executable instructions further initiate a machine learning operation to learn a plurality of sleep preferences for each entity, historical sleeping activity patterns of the targeted entity, a cognitive state of the targeted entity, contextual factors, the one or more characteristics of the generated sound, feedback data collected from each entity, or a combination thereof. 13. A computer program product for implementing intelligent alarm sound control by one or more processors, the computer program product comprising a non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising: an executable portion that isolates a targeted entity for a generated sound to be delivered, while simultaneously provide noise cancellation to prevent an alternative entity from being disturbed by the generated sound; wherein the generated sound is activated and isolated within a cone of silence for a selected period of time, and the alternative entity located outside the cone of silence is shielded from the generated sound by initiating the noise cancellation for a duration beginning prior to the selected period of time until the target entity performs a certain action. 14. The computer program product of claim 13 , further including an executable portion that provides the generated sound within the cone of silence for waking the targeted entity and preventing the alternative entity from being disturbed by the generated sound. 15. The computer program product of claim 13 , further including an executable portion that pairs the noise cancellation with the generated sound according to a predictive frequency, volume, and wavelength. 16. The computer program product of claim 13 , further including an executable portion that: emits a preset frequency and sound pattern for the generated sound; and masks the preset frequency and the sound pattern for the isolated sound by the noise cancellation. 17. The computer program product of claim 13 , further including an executable portion that initiates a machine learning operation to learn a plurality of sleep preferences for each entity, historical sleeping activity patterns of the targeted entity, a cognitive state of the targeted entity, contextual factors, the one or more characteristics of the generated sound, feedback data collected from each entity, or a combination thereof.
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