Earpiece advisor

1 . A system comprising:

an earpiece housing;

a plurality of sensors disposed within the earpiece housing;

a processor disposed within the earpiece housing and operatively connected to the plurality of sensors; and

a memory storing instructions that, when executed by the processor, cause the processor to:

receive sensor data from the plurality of sensors;

determine a contextual state of a user based on processing the sensor data using an artificial intelligence framework;

determine a contextually relevant time to provide advice to the user based at least in part on the contextual state; and

delay delivery of the advice until the contextually relevant time.

2 . The system of claim 1 , wherein the plurality of sensors includes at least one of: an inertial sensor, a bone microphone, a physiological sensor, or a temperature sensor.

3 . The system of claim 1 , wherein determining the contextual state includes determining at least one of: whether the user is stressed, whether the user needs to focus, or whether the user needs a distraction.

4 . The system of claim 1 , wherein the contextual state includes at least one of: what the user is doing, who is around the user, what is the time of day, or what is a location of the user.

5 . The system of claim 1 , wherein the plurality of sensors includes a physiological sensor configured to measure at least one of: heart rate, steps, pace, acceleration, respiration, G-force, direction, or body vitals.

6 . The system of claim 1 , wherein the instructions further cause the processor to:

receive data from at least one sensor not disposed within the earpiece housing; and

modify the contextual state based on the received data.

7 . The system of claim 1 , wherein the advice includes at least one of: a product recommendation, a service recommendation, or information.

8 . A method comprising:

monitoring a plurality of sensors using a device, wherein the device comprises an earpiece housing containing the plurality of sensors;

using an artificial intelligence platform of the device to:

generate advice to a user based on contextual understanding using data from the plurality of sensors;

determine a contextually relevant time to deliver the advice to the user; and

deliver the advice to the user at the contextually relevant time.

9 . The method of claim 8 , wherein determining the contextually relevant time includes determining whether the user has made any requests.

10 . The method of claim 8 , wherein determining the contextually relevant time includes determining a location of the user.

11 . The method of claim 8 , wherein determining the contextually relevant time includes determining an activity of the user.

12 . The method of claim 8 , further comprising:

determining whether the user is engaged in a phone conversation; and

delaying delivery of the advice until after the phone conversation if the user is engaged in the phone conversation.

13 . The method of claim 8 , wherein using the artificial intelligence platform includes determining whether the user is at a particular location, with particular people, experiencing a particular emotional state, or engaging in a particular activity.

14 . A system comprising:

an earpiece housing;

at least one speaker disposed within the earpiece housing;

a plurality of sensors disposed within the earpiece housing; and

a processor operatively connected to the plurality of sensors and the at least one speaker, wherein the processor is configured to:

use an artificial intelligence framework to evaluate sensor input from the plurality of sensors to provide advice to a user;

determine a mood of the user based at least in part on the sensor input; and

determine a contextually relevant time to deliver the advice based at least in part on the determined mood.

15 . The system of claim 14 , wherein the plurality of sensors includes at least one inertial sensor configured to detect head movement and head orientation.

16 . The system of claim 14 , wherein the processor is further configured to:

distinguish between idle, walking, running, cycling, swimming, sleeping, or other activities based on the sensor input.

17 . The system of claim 14 , wherein the plurality of sensors includes at least one biometric sensor configured to measure physiological parameters.

18 . The system of claim 14 , wherein the processor is further configured to:

track user responses to previously provided advice; and

modify future delivery of advice based on the tracked user responses.

19 . The system of claim 14 , wherein the artificial intelligence framework includes at least one of:

a machine learning model, a convolutional neural network, a hidden Markov model, natural language processing, or a deep neural network.

20 . The system of claim 14 , wherein the processor is further configured to:

receive data from at least one external sensor not disposed within the earpiece housing; and

modify the determination of the contextually relevant time based on the received data.