Google Inc.

Nest Labs, Inc.

Rangoli Sharan

Yoky Matsuoka

Anthony Michael Fadell

Mark D Stefanski

Matthew Lee Rogers

David Hendler Sloo

Frank Emmanuel Astier

Eric A Lee

Evan Jarman Fisher

Joseph Adam Ruff

Shahar Ben-Menahem

Steven Alexander Hales

Kipp Avery Rogers

Abraham K Ishihara

Mark Rajan Malhotra

Michael Plitkins

Michael James Matas

Matthew S Rogers

Steven A Hales, Iv

Michael Anthony Fadell

Matthey L Rogers

Methods for controlling temperature in a conditioned enclosure such as a dwelling are described that include an 'auto-away' and/or 'auto-arrival' feature for detecting unexpected absences which provide opportunities for significant energy savings through automatic adjustment of the setpoint temperature. According to some preferred embodiments, when no occupancy has been detected for a minimum time interval, an &#x201c;auto-away&#x201d; feature triggers a changes of the state of the enclosure, and the actual operating setpoint temperature is changed to a predetermined energy-saving away-state temperature, regardless of the setpoint temperature indicated by the normal thermostat schedule. The purpose of the &#x201c;auto away&#x201d; feature is to avoid unnecessary heating or cooling when there are no occupants present to actually experience or enjoy the comfort settings of the schedule, thereby saving energy.

Control unit with automatic setback capabtility

A method includes a system that operates according to a control schedule; detects events that indicate occupancy; stores a record of the events that indicate occupancy in one or more memory devices; and enters an auto-away state. A determination to enter the auto-away state may be based at least in part on a length of a time interval during which no events that indicate occupancy were detected and the stored record of the events that indicate occupancy. The system may also detect a pattern of instances where the auto-away state is entered over a plurality of days and adjusts the control schedule based at least in part on the pattern of instances where the auto-away state is entered.

Automated presence detection and presence-related control within an intelligent controller

A user-friendly programmable thermostat is described that includes receiving an immediate-control input to change set point temperature, controlling temperature according to the set point temperature for a predetermined time interval, and then automatically resetting the set point temperature upon the ending of the predetermined time interval such that the user is urged to make further immediate-control inputs. A schedule for the programmable thermostat is automatically generated based on the immediate-control inputs. Methods are also described for receiving user input relating to the user's preference regarding automatically generating a schedule, and determining whether or not to automatically adopt an automatically generated schedule based on the received user input.

Energy efficiency promoting schedule learning algorithms for intelligent thermostat

A system for detecting occupancy of an enclosure may include a sensing system adapted to monitor utility information for the enclosure which tends to indicate a likelihood of occupancy of the enclosure. The utility information may include power line information, Smart Meter information, Wi-Fi information, etc. The system may also include a processing system programmed to estimate occupancy of the enclosure based at least in part on the monitored utility information by the sensing system.

Occupancy pattern detection, estimation and prediction

A method includes operating a controller according to a control schedule; detecting events that indicate occupancy; storing a record of the events that indicate occupancy in one or more memory devices; and causing the controller to enter an auto-away state. A determination that the controller should enter the auto-away state may be based at least in part on a length of a time interval during which no events that indicate occupancy were detected; and the stored record of the events that indicate occupancy. The method also includes detecting a pattern of instances where the controller enters the auto-away state over a plurality of days; and adjusting the control schedule based at least in part on the pattern of instances where the controller enters the auto-away state.

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

A device includes a memory configured to store a preexisting schedule and one or more processors configured to perform operations including controlling a temperature within an enclosure according to a first setpoint, wherein the first setpoint is from the preexisting schedule and represents a temperature for when the enclosure is occupied. The operations also include accessing occupancy data indicating occupancy within the enclosure and automatically changing the first setpoint to a second setpoint upon expiration of a predetermined time interval during which no occupancy has been detected. The second setpoint requires less energy to maintain than the first setpoint, and the predetermined time interval is modified based at least in part on received manual settings that indicate occupancy following the changing to the second setpoint.

Control unit with automatic setback capability

The current application is directed to intelligent controllers that continuously, periodically, or intermittently calculate and display the time remaining until a control task is projected to be completed by the intelligent controller. In general, the intelligent controller employs multiple different models for the time behavior of one or more parameters or characteristics within a region or volume affected by one or more devices, systems, or other entities controlled by the intelligent controller. The intelligent controller collects data, over time, from which the models are constructed and uses the models to predict the time remaining until one or more characteristics or parameters of the region or volume reaches one or more specified values as a result of intelligent controller control of one or more devices, systems, or other entities.

Intelligent controller providing time to target state

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.

Systems and methods for energy-efficient control of an energy-consuming system

A thermostat includes a control unit, a plurality of connection ports, and a user interface operatively coupled to the control unit an having an electronic display. The control unit may be configured and programmed to operate the wire insertion sensing circuits to identify a set of the plurality of connection ports into which corresponding ones of the plurality of HVAC wires have been inserted; cause the electronic display to display a photograph of the plurality of connection ports as they actually appear to a user; and cause the electronic display to visually highlight the set of the plurality of connection ports into which the corresponding ones of the plurality of HVAC wires have been inserted.

Thermostat facilitating user-friendly installation thereof

Modeling the behavior of an enclosure for use by a control system of an HVAC system is described. A model for the enclosure that describes the enclosure's behavior for use by the control system is updated based on weather forecast data. The weather forecast data can include predictions more than 24 hours in the future, and can include predictions on temperature, humidity and/or dew point, solar output, precipitation. The model for the enclosure can also be updated based on additional information and data. The model for the enclosure can be updated based also on an enclosure model stored in a database, and/or enclosure information from a user. The model can be updated based on active testing of the enclosure which can be performed automatically or in response to user input. The testing can include heating and/or cooling the enclosure at times when the enclosure is not likely occupied.

Thermodynamic modeling for enclosures

A thermostat is described for controlling air temperature in a building. The time associated with causing the controlled air temperature to reach a target temperature is estimated and displayed to a user. Input from a user indicating the target temperature can be received and the estimating and displaying can be carried out in real time. The thermostat can be wall-mounted or the user input can be received and estimated time can be displayed using a remote device, for example that communicates wirelessly with other components of the HVAC system.

Temperature controller with model-based time to target calculation and display

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 use sensor output and electronically stored information, including one or more of electronically stored rules, parameters, and instructions, to determine whether or not one or more types of entities are present within an area, volume, or environment monitored by the intelligent controllers. The intelligent controllers select operational modes and modify control schedules with respect to the presence and absence of the one or more entities. The intelligent controllers employ feedback information to continuously adjust the electronically stored parameters and rules in order to minimize the number of incorrect inferences with respect to the presence or absence of the one or more entities and in order to maximize the efficiency by which various types of systems controlled by the intelligent controllers carry out selected operational modes.

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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Sunnyvale, CA, United States of America

Rangoli Sharan