Google Inc.

Nest Labs, Inc.

Mark D Stefanski

Yoky Matsuoka

Rangoli Sharan

David Hendler Sloo

Anthony Michael Fadell

Mark Rajan Malhotra

Matthew Lee Rogers

Evan Jarman Fisher

Eric A Lee

Joseph Adam Ruff

Steven Alexander Hales

Frank Emmanuel Astier

Hugo Fiennes

Andrea Mucignat

Edwin H Satterthwaite, Jr

Allen Joseph Minich

Michael James Matas

Michael Plitkins

Anurag Gupta

Isabel I Guenette

Marcus Albonico

Giancarlo Giustina

John Stefanski

Vivek Goyal

Steven A Hales, Iv

Marie Pellat

Orville Buenaventura

Alexander Schoenen

David Saltzman

Isabel Thornton

Matthey L Rogers

Allen J Minich

A control system includes an energy management system in operation with intelligent, network-connected thermostats located in structures. The thermostats are operable to control heating, ventilation, and air conditioning (HVAC) systems. Control during a demand response (DR) event period may be performed based on an optimal setpoint schedule of the HVAC system. Candidate setpoint schedules may be simulated to identify an optimal schedule.

Controlling an HVAC system during a demand-response event with display of effective setpoints

A control system includes an energy management system in operation with intelligent, network-connected thermostats located in structures. The thermostats are operable to control heating, ventilation, and air conditioning (HVAC) systems. Control during a demand response (DR) event period may be performed based on an optimal control trajectory of the HVAC system, where the control trajectory is optimal in that it minimizes a cost function.

Controlling an HVAC system using an optimal setpoint schedule during a demand-response event

Various arrangements are presented for monitoring a resident of a residence. A confidence assessment may be performed based on a plurality of smart home devices in the residence. The residence may be identified as eligible for monitoring of the resident based on the confidence assessment. A learning process may be performed to create an ordinary behavior model. Data that is received from the plurality of smart home devices may be monitored to identify data indicative of behavior considered unusual based on the ordinary behavior model.

Thoughtful elderly monitoring in a smart home environment

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

The current application is directed to intelligent controllers that use sensor output and electronically stored information 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/or modify control schedules with respect to the presence and absence of the one or more entities. The intelligent controllers selectively carry out scheduled control operations during periods of time when one or more types of entities are determined not to be in a controlled environment.

Selective carrying out of scheduled control operations by an intelligent controller

Controlling an HVAC system in association with a demand-response event

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

This patent specification relates to methods and systems that can detect over cycling conditions that exist in an HVAC system. The over cycling condition can be caused by overheating of a forced air heating system or furnace of the HVAC system control. When the furnace overheats, a thermally actuated limit switch within the furnace may cut off power to a heat generation apparatus. The limit switch can reconnect the power to the heat generation apparatus after it has cooled down, at which point the thermostat control system may issue another heating call to continue heating the enclosure so that it reaches the desired temperature. If the overheat condition persist, then the thermally actuated switch will cut power, resulting in repeated power cycling. The detection system and methods can monitor these power loss events and use them as data points for determining whether an alert condition exists within the HVAC system.

Intelligent HVAC control including automatic furnace shutdown event processing

Various arrangements are presented for monitoring a resident of a residence. A confidence assessment may be performed based on a plurality of smart home devices in the residence. The residence may be identified as eligible for monitoring of the resident based on the confidence assessment. A learning process may be performed to create an ordinary behavior model. Data that is received from the plurality of smart home devices may be monitored to identify data indicative of behavior considered unusual based on the ordinary behavior model. An alert may be created that identifies the behavior and identifies how the behavior contrasts with the ordinary behavior model.

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

A thermostat may include a plurality of heat-generating components; a plurality of first temperature sensors, each of the plurality of first temperature sensors being disposed next to a corresponding one of the plurality of heat-generating components; a second temperature sensor that is disposed away from the plurality of heat-generating components; and a memory device storing a coefficient matrix. The thermostat may also include one or more processors that combine a plurality of inputs to calculate an ambient temperature for an enclosure in which the thermostat is installed, the plurality of inputs including readings from the plurality of first temperature sensors, readings from the second temperature sensor, and the coefficient matrix.

Smart thermostat robust against adverse effects from internal heat-generating components

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

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.

Growing community of inventors

Palo Alto, CA, United States of America

Mark D Stefanski