Abstract: Aspects of the subject technology provide noise mitigation for electronic devices. Noise mitigation can mitigate the effect of a sound-generating component of an electronic device that generates sound as a byproduct of a primary function of the sound-generating component. The noise mitigation can include geometrically distributing another sound in a geometric distribution that mitigates the perceived effect of the sound of the sound-generating component on a user of the electronic device.

Abstract: 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 th

Abstract: 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.

Abstract: Systems and methods are provided for efficiently controlling energy-consuming systems, such as heating, ventilation, or air conditioning (HVAC) systems. For example, an electronic device used to control an HVAC system may encourage a user to select energy-efficient temperature setpoints. Based on the selected temperature setpoints, the electronic device may generate or modify a schedule of temperature setpoints to control the HVAC system.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Devices and methods are provided for generating and/or displaying a graphical user interface used to control an energy-consuming system, such as a heating, ventilation, or air conditioning (HVAC) system. Such an electronic device may include, for example, a processor that generates the graphical user interface and an electronic display that displays the graphical user interface. The graphical user interface may include a menu formed from discrete display elements that, owing to the way in which the discrete display elements are shifted into and out of view on the screen, appear to be spatially related to one another.

Abstract: 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.

Abstract: Systems and methods are provided for efficiently controlling energy-consuming systems, such as heating, ventilation, or air conditioning (HVAC) systems. For example, an electronic device used to control an HVAC system may encourage a user to select energy-efficient temperature setpoints. Based on the selected temperature setpoints, the electronic device may generate or modify a schedule of temperature setpoints to control the HVAC system.

Abstract: Systems and methods are provided for efficiently controlling energy-consuming systems, such as heating, ventilation, or air conditioning (HVAC) systems. For example, an electronic device used to control an HVAC system may encourage a user to select energy-efficient temperature setpoints. Based on the selected temperature setpoints, the electronic device may generate or modify a schedule of temperature setpoints to control the HVAC system.

Abstract: 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.

Abstract: 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.

Abstract: Provided according to one or more embodiments is a method of processing rotational inputs to a control device having a an electronic display and user interface, such as a programmable thermostat. Methods and systems include displaying on the electronic display associated with the control device at least a portion of an initial display element selected from a sequence of display elements. In response to seeing such information, the user applies a rotational input applied to a rotational input device, such as a rotatable ring around the electronic display. A variable scroll assist engine receives this information and determines an angular movement as provided by the user through the rotational input device. In order to reduce the rotational input required by the user, the variable assist scroll engine applies one or more heuristics to variably assist with a scrolling movement of a sequence of display elements on the electronic display.

Abstract: Devices and methods are provided for generating and/or displaying a graphical user interface used to control an energy-consuming system, such as a heating, ventilation, or air conditioning (HVAC) system. Such an electronic device may include, for example, a processor that generates the graphical user interface and an electronic display that displays the graphical user interface. The graphical user interface may include a menu formed from discrete display elements that, owing to the way in which the discrete display elements are shifted into and out of view on the screen, appear to be spatially related to one another.

Abstract: 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.

Abstract: Devices and methods are provided for generating and/or displaying a graphical user interface used to control an energy-consuming system, such as a heating, ventilation, or air conditioning (HVAC) system. Such an electronic device may include, for example, a processor that generates the graphical user interface and an electronic display that displays the graphical user interface. The graphical user interface may include a menu formed from discrete display elements that, owing to the way in which the discrete display elements are shifted into and out of view on the screen, appear to be spatially related to one another.

Abstract: 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.

Abstract: 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.

Abstract: 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.