Automated respite beacon based on identified user condition and identified user context

1 . A computing system comprising:

a processor; and

a memory having a set of instructions, which when executed by the processor, cause the computing system to:

receive first data and second data from one or more first internet-of-things devices associated with a user, wherein the first data includes biological measurements of the user at different times, further wherein the second data includes previous events that occurred prior to each of the different times;

determine that the user experienced a user condition at each of the different times based on the biological measurements;

determine at least one common event from the previous events that occurred prior to each of the different times;

determine that the at least one common event is associated with the user interacting with an application on a user device associated with the user;

determine a first action to mitigate the user condition based on the at least one common event being associated with the user interacting with the application, wherein the first action blocks the application from executing on the user device;

receive third data from one or more second internet-of-things devices;

determine from the third data that a probability of the user condition occurring in the future is above a threshold;

provide the first action to the user device associated with the user based on the probability being above the threshold; and

execute, by the user device, the first action to block the application from executing on the user device.

2 . The computing system of claim 1 , wherein:

the user condition is one or more of anxiety, fear or anger;

the one or more first and second internet-of-things device includes one or more of a smartwatch, an artificial intelligence voice assistant, a connected car, a speaker, a microphone, a mobile device, a computing device, a continuous glucose monitor or an imaging device; and

the first data includes one or more of, an audio, a location of the user, or a velocity of the user.

3 . The computing system of claim 1 , wherein the instructions of the memory, when executed, cause the computing system to:

repeatedly measure a user characteristic of the user a plurality of times to generate a plurality of baseline biological measurements;

determine a baseline measurement for the user based on the plurality of baseline biological measurements; and

compare the first data to the baseline measurement associated with the user.

4 . The computing system of claim 1 , wherein the instructions of the memory, when executed, cause the computing system to:

set a threshold based on a past record of heart rate variability of the user;

identify a first heart variability rate of the user from the first data;

identify that the first heart variability rate is below a threshold; and

determine that the user has the user condition based on the first heart variability rate being below the threshold.

5 . The computing system of claim 1 , wherein the instructions of the memory, when executed, cause the computing system to:

access a past record of the user;

identify previous actions that mitigated previous conditions associated with the user based on the past record; and

select the first action based on the previous actions and the user condition.

6 . The computing system of claim 1 , wherein the first internet-of-things devices are the same as the second internet-of-things devices.

7 . The computing system of claim 1 , wherein the first internet-of-things devices are different from the second internet-of-things devices.

8 . At least one non-transitory computer readable storage medium comprising a set of instructions, which when executed by a computing system, cause the computing system to:

receive first data and second data from one or more first internet-of-things devices associated with a user, wherein the first data includes biological measurements of the user at different times, further wherein the second data includes previous events that occurred prior to each of the different times;

determine that the user experienced a user condition at each of the different times based on the biological measurements;

determine at least one common event from the previous events that occurred prior to each of the different times;

determine that the at least one common event is associated with the user interacting with an application on a user device associated with the user;

determine a first action to mitigate the user condition based on the at least one common event being associated with the user interacting with the application, wherein the first action blocks the application from executing on the user device;

receive third data from one or more second internet-of-things devices;

determine from the third data that a probability of the user condition occurring in the future is above a threshold;

provide the first action to the user device associated with the user based on the probability being above the threshold; and

execute, by the user device, the first action to block the application from executing on the user device.

9 . The at least one non-transitory computer readable storage medium of claim 8 , wherein:

the user condition is one or more of anxiety, fear, sadness or anger;

the one or more first and second internet-of-things device includes one or more of a smartwatch, an artificial intelligence voice assistant, a connected car, a speaker, a microphone, a mobile device, a computing device a continuous glucose monitor or an imaging device; and

the first data includes one or more of, an audio, a location of the user, or a velocity of the user.

10 . The at least one non-transitory computer readable storage medium of claim 8 , wherein the instructions, when executed, cause the computing system to:

repeatedly measure a user characteristic of the user a plurality of times to generate a plurality of baseline biological measurements;

determine a baseline measurement for the user based on the plurality of baseline biological measurements; and

compare the first data to the baseline measurement associated with the user.

11 . The at least one non-transitory computer readable storage medium of claim 8 , wherein the instructions, when executed, cause the computing system to:

set a threshold based on a past record of heart rate variability of the user;

identify a first heart variability rate of the user from the first data;

identify that the first heart variability rate is below a threshold; and

determine that the user has the user condition based on the first heart variability rate being below the threshold.

12 . The at least one non-transitory computer readable storage medium of claim 8 , wherein the instructions, when executed, cause the computing system to:

access a past record of the user;

identify previous actions that mitigated previous conditions associated with the user based on the past record; and

select the first action based on the previous actions and the user condition.

13 . The at least one non-transitory computer readable storage medium of claim 8 , wherein the first internet-of-things devices are the same as the second internet-of-things devices.

14 . The at least one non-transitory computer readable storage medium of claim 8 , wherein the first internet-of-things devices are different from the second internet-of-things devices.

15 . A method comprising:

receiving first data and second data from one or more first internet-of-things devices associated with a user, wherein the first data includes biological measurements of the user at different times, further wherein the second data includes previous events that occurred prior to each of the different times;

determining that the user experienced a user condition at each of the different times based on the biological measurements;

determining at least one common event from the previous events that occurred prior to each of the different times;

determining that the at least one common event is associated with the user interacting with an application on a user device associated with the user;

determining a first action to mitigate the at least one common event being associated with the user interacting with the application, wherein the first action blocks the application from executing on the user device;

receiving third data from one or more second internet-of-things devices;

determining from the third data that a probability of the user condition occurring in the future is above a threshold;

providing the first action to the user device associated with the user based on the probability being above the threshold; and

executing, by the user device, the first action to block the application from executing on the user device.

16 . The method of claim 15 , wherein:

the user condition is one or more of anxiety, fear or anger;

the one or more first and second internet-of-things device includes one or more of a smartwatch, an artificial intelligence voice assistant, a connected car, a speaker, a microphone, a mobile device, a computing device, a continuous glucose monitor or an imaging device; and

the first data includes one or more of, an audio, a location of the user, or a velocity of the user.

17 . The method of claim 15 , further comprising:

repeatedly measuring a user characteristic of the user a plurality of times to generate a plurality of baseline biological measurements;

determining a baseline measurement for the user based on the plurality of baseline biological measurements; and

comparing the first data to the baseline measurement associated with the user,

wherein the first internet-of-things devices are the same as the second internet-of-things devices.

18 . The method of claim 15 , further comprising:

setting a threshold based on a past record of heart rate variability of the user;

identifying a first heart variability rate of the user from the first data;

identifying that the first heart variability rate is below a threshold; and

determining that the user has the user condition based on the first heart variability rate being below the threshold.

19 . The method of claim 15 , further comprising:

accessing a past record of the user;

identifying previous actions that mitigated previous conditions associated with the user based on the past record; and

selecting the first action based on the previous actions and the user condition.

20 . The method of claim 15 , further wherein the first internet-of-things devices are different from the second internet-of-things devices.