Google Inc.

Nest Labs, Inc.

Steven Alexander Hales

Yoky Matsuoka

Mark D Stefanski

Rangoli Sharan

Eric A Lee

Anthony Michael Fadell

David Hendler Sloo

Benjamin Jerming Chang

Taylor Keith Umphreys

Siddhant Bhargava

Brian Keith Hales

Craig Thomas Rohe

Thomas Joseph Gurka

Matthew Lee Rogers

Matthey L Rogers

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for presence determination. Systems can include one or more user devices and terminal devices. A current location may be determined of a user that is associated with a particular space of a plurality of different spaces. A plurality of location results may be calculated, wherein each location result is computed using a distinct process of a plurality of processes; and evaluating the plurality of location results to determine a current space of the user; wherein the determining is performed by one or more of, a particular user device, a terminal device, or a server system.

User presence determination

A method of using a server to update stored control schedules for environmental controllers includes communicating with an environmental controller that controls, during a monitoring period, an environmental system in an enclosure according to a stored control schedule; receiving a first immediate-control input provided through the environmental controller during the monitoring period; receiving a first control-schedule change provided through the environmental controller during the monitoring period; receiving a second immediate-control input provided through a user device during the monitoring period; receiving a second control-schedule change provided through the user device during the monitoring period; processing at least the first immediate-control input, the first control-schedule change, the second immediate-control input, and the second control-schedule change together to generate an updated control schedule; and causing the environmental controller to control the environmental system according to the updated control schedule.

Automated control-schedule acquisition within an intelligent controller

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for presence determination. One of the methods includes for one or more user devices having one or more associated users, determining a current location of a user, wherein the current location is associated with a particular space of a plurality of different spaces, wherein the determining includes: computing a plurality of location results, wherein each location result is computed using a distinct process of a plurality of processes; and evaluating the plurality of location results to determine a current space of the user; wherein the determining is performed by one or more of, a particular user device, a terminal device, or a server system.

The current application is directed to an intelligent control system that includes intelligent thermostats and remote servers that spread call-home events over time to avoid large peak computational and communications loads on intelligent-control-system servers. The spreading of call-home vents over time is effected by use of call-home splay values pseudorandomly generated for intelligent thermostats.

Distribution of call-home events over time to ameliorate high communications and computation peaks in intelligent control system

HVAC schedules may be programmed for a thermostat using a combination of pre-existing schedules or templates and automated schedule learning. For example, a pre-existing schedule may be initiated on the thermostat and the automated schedule learning may be used to update the pre-existing schedule based on users' interactions with the thermostat. The preexisting HVAC schedules may be stored on a device or received from a social networking service or another online service that includes shared HVAC schedules.

HVAC schedule establishment in an intelligent, network-connected thermostat

The current application is directed to intelligent controllers that initially aggressively learn, and then continue, in a steady-state mode, to monitor, learn, and modify one or more control schedules that specify a desired operational behavior of a device, machine, system, or organization controlled by the intelligent controller. An intelligent controller generally acquires one or more initial control schedules through schedule-creation and schedule-modification interfaces or by accessing a default control schedule stored locally or remotely in a memory or mass-storage device. The intelligent controller then proceeds to learn, over time, a desired operational behavior for the device, machine, system, or organization controlled by the intelligent controller based on immediate-control inputs, schedule-modification inputs, and previous and current control schedules, encoding the desired operational behavior in one or more control schedules and/or sub-schedules.

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Palo Alto, CA, United States of America

Steven Alexander Hales