Abstract: Methods, systems, and devices for predicting a state of a user (e.g., asleep or awake). In some embodiments, the location sharing system accesses historical activity data of the user and extracts historical sleep records from the historical activity data. The system clusters the historical sleep records into a plurality of clusters and extracts a sleep pattern from each one of the plurality of clusters. Then, when the location sharing system receives current activity data of the user, the system can predict whether the user is currently asleep based on the current activity of the user and at least one of the sleep patterns. Some embodiments additionally compute an estimated wake up time of the user. Some embodiments share the predicted physiological state of the user with the user's friends via the map GUI. Some embodiments additionally share the estimated wake up time of the user.

Abstract: Methods, systems, and devices for predicting a state of a user (e.g., asleep or awake). In some embodiments, the location sharing system accesses historical activity data of the user and extracts historical sleep records from the historical activity data. The system clusters the historical sleep records into a plurality of clusters and extracts a sleep pattern from each one of the plurality of clusters. Then, when the location sharing system receives current activity data of the user, the system can predict whether the user is currently asleep based on the current activity of the user and at least one of the sleep patterns. Some embodiments additionally compute an estimated wake up time of the user. Some embodiments share the predicted physiological state of the user with the user's friends via the map GUI. Some embodiments additionally share the estimated wake up time of the user.

Abstract: Methods, systems, and devices for predicting a state of a user (e.g., asleep or awake). In some embodiments, the location sharing system accesses historical activity data of the user and extracts historical sleep records from the historical activity data. The system clusters the historical sleep records into a plurality of clusters and extracts a sleep pattern from each one of the plurality of clusters. Then, when the location sharing system receives current activity data of the user, the system can predict whether the user is currently asleep based on the current activity of the user and at least one of the sleep patterns. Some embodiments additionally compute an estimated wake up time of the user. Some embodiments share the predicted physiological state of the user with the user's friends via the map GUI. Some embodiments additionally share the estimated wake up time of the user.

Abstract: Methods, systems, and devices for predicting a state of a user (e.g., asleep or awake). In some embodiments, the location sharing system accesses historical activity data of the user and extracts historical sleep records from the historical activity data. The system clusters the historical sleep records into a plurality of clusters and extracts a sleep pattern from each one of the plurality of clusters. Then, when the location sharing system receives current activity data of the user, the system can predict whether the user is currently asleep based on the current activity of the user and at least one of the sleep patterns. Some embodiments additionally compute an estimated wake up time of the user. Some embodiments share the predicted physiological state of the user with the user's friends via the map GUI. Some embodiments additionally share the estimated wake up time of the user.

Abstract: Methods, systems, and devices for predicting a state of a user (e.g., asleep or awake). In some embodiments, the location sharing system accesses historical activity data of the user and extracts historical sleep records from the historical activity data. The system clusters the historical sleep records into a plurality of clusters and extracts a sleep pattern from each one of the plurality of clusters. Then, when the location sharing system receives current activity data of the user, the system can predict whether the user is currently asleep based on the current activity of the user and at least one of the sleep patterns. Some embodiments additionally compute an estimated wake up time of the user. Some embodiments share the predicted physiological state of the user with the user's friends via the map GUI. Some embodiments additionally share the estimated wake up time of the user.

Abstract: Methods, systems, and devices for predicting a state of a user (e.g., asleep or awake). In some embodiments, the location sharing system accesses historical activity data of the user and extracts historical sleep records from the historical activity data. The system clusters the historical sleep records into a plurality of clusters and extracts a sleep pattern from each one of the plurality of clusters. Then, when the location sharing system receives current activity data of the user, the system can predict whether the user is currently asleep based on the current activity of the user and at least one of the sleep patterns. Some embodiments additionally compute an estimated wake up time of the user. Some embodiments share the predicted physiological state of the user with the user's friends via the map GUI. Some embodiments additionally share the estimated wake up time of the user.