Abstract

Smart home features can automate and/or personalize various functions and routines, such as turning on the lights automatically when motion is detected in a dark room, automatically closing the skylights when it starts raining, etc. Smart home devices lack the capability to make dynamic adjustments to user-specified operating parameters or pre-programmed routines. Yet, such adjustments are often necessary to handle variations in the user’s needs and context as captured via real time information. As a result, the potential of a smart home to maximize user comfort and facilitate healthier living for the occupants is not fully realized. This disclosure describes techniques, implemented with user permission, to automatically detect optimal baseline settings for a user’s smart home environment to facilitate healthier and higher quality sleep. Appropriate dynamic adjustments to the baseline settings are made based on real time data obtained from a wearable device or other suitable sensor using a trained model.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

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