Optimal sleep phase selection system

1. A method comprising:

determining a current sleep phase of a user based on sensor data from at least one sensor;

determining an optimal next sleep phase for the user based on at least remote data received via a network, wherein the remote data comprises one or more of: data from home environment controls, data from a home automation system, and data from a remote sensor; and

determining whether the user should be moved to the optimal next sleep phase, and when the user should be moved to the optimal next sleep phase, utilizing an output system to adjust one or more conditions in the user's environment to guide the user to the optimal next sleep phase.

2. The method of claim 1 , wherein the at least one sensor comprises at least one of: an accelerometer, a thermometer, a heart rate monitor, and a brainwave monitor.

3. The method of claim 1 , wherein the at least one sensor comprises at least one of: an environmental sensor, an interface to home environment controls to receive environmental data, and an interface to a home automation system to receive environmental data.

4. The method of claim 1 , wherein the one or more conditions are one or more of: sound, tactile output, light level, visual output, scent, temperature, humidity, and mattress firmness.

5. The method of claim 1 , further comprising:

using data from a sleep tracker, indicating sleep phase data for a current sleep period, to determine the optimal next sleep phase for the user.

6. The method of claim 1 , further comprising:

adjusting one or more conditions to keep the user in the current sleep phase, when the optimal next sleep phase is the same as the current sleep phase.

7. The method of claim 1 , wherein the sensor is implemented in one of: an armband, a mobile telephone, a wristband, a pillow, or a sleep mask.

8. The method of claim 1 , wherein the remote data comprises one or more of: traffic data and weather data.

9. A sleep sensing system comprising:

a sleep sensor to generate real-time information including one or more sensors in one of an armband, a mobile telephone, a wristband, a pillow, or a sleep mask;

a processor to:

determine the user's current sleep phase based on the real-time information, and

select an optimal next sleep phase for the user based on at least remote data received via a network, wherein the remote data comprises one or more of: data from home environment controls, data from a home automation system, and data from a remote sensor; and

an output mechanism to adjust one or more conditions in the user's environment to guide the user from the current sleep phase to the optimal next sleep phase, when needed.

10. The sleep sensing system of claim 9 , wherein the one or more conditions include one or more of: sound, tactile output, light level, visual output, scent, temperature, humidity, and mattress firmness.

11. The sleep sensing system of claim 9 , wherein the optimal next phase of sleep is further determined based on a combination of one or both of: sleep phase data for the current sleep period and an estimated waking time, the estimated waking time based on a calendar entry.

12. The sleep sensing system of claim 9 , wherein the remote data comprises one or more of: traffic data and weather data.

13. A method comprising:

determining a current sleep phase of a user based on sensor data from at least one sensor;

determining an optimal next sleep phase for the user based on at least remote data received via a network from a third party source, wherein the remote data comprises data from a remote sensor; and

determining whether the user should be moved to the optimal next sleep phase, and when the user should be moved to the optimal next sleep, utilizing an output system to adjust one or more conditions in the user's environment to guide the user to the optimal next sleep phase.

14. The method of claim 13 , wherein the remote data received from a third party source comprises traffic data.

15. The method of claim 13 , wherein the remote data received from a third party source comprises weather data.

16. The method of claim 13 , wherein the remote data received from a third party source comprises data from home environment controls.

17. The method of claim 13 , wherein the remote data received from a third party source comprises data from a home automation system.