Energy efficiency promoting schedule learning algorithms for intelligent thermostat

Information

  • Patent Grant
  • 11334034
  • Patent Number
    11,334,034
  • Date Filed
    Monday, February 22, 2016
    8 years ago
  • Date Issued
    Tuesday, May 17, 2022
    2 years ago
  • CPC
  • Field of Search
    • CPC
    • F24F11/006
    • F24F11/001
    • F24F11/0076
    • F24F11/0012
    • F24F2011/0057
    • F24F2011/0063
    • G05B13/0265
    • G05D23/1904
  • International Classifications
    • G05B13/02
    • F24F11/62
    • F24F11/30
    • F24F11/70
    • G05D23/19
    • F24F110/10
    • F24F11/65
    • F24F11/52
    • F24F120/20
    • F24F11/61
    • F24F110/00
    • F24F11/64
    • F24F11/56
    • Term Extension
      729
Abstract
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.
Description
FIELD

This invention relates generally to the monitoring and control of HVAC systems and/or for other systems for controlling household utilities, and/or resources. More particularly, embodiments of this invention relate to systems, methods and related computer program products for facilitating user-friendly installation and/or operation of a monitoring and control device such as a thermostat.


BACKGROUND

While substantial effort and attention continues toward the development of newer and more sustainable energy supplies, the conservation of energy by increased energy efficiency remains crucial to the world's energy future. According to an October 2010 report from the U.S. Department of Energy, heating and cooling account for 56% of the energy use in a typical U.S. home, making it the largest energy expense for most homes. Along with improvements in the physical plant associated with home heating and cooling (e.g., improved insulation, higher efficiency furnaces), substantial increases in energy efficiency can be achieved by better control and regulation of home heating and cooling equipment. By activating heating, ventilation, and air conditioning (HVAC) equipment for judiciously selected time intervals and carefully chosen operating levels, substantial energy can be saved while at the same time keeping the living space suitably comfortable for its occupants.


Historically, however, most known HVAC thermostatic control systems have tended to fall into one of two opposing categories, neither of which is believed be optimal in most practical home environments. In a first category are many simple, non-programmable home thermostats, each typically consisting of a single mechanical or electrical dial for setting a desired temperature and a single HEAT-FAN-OFF-AC switch. While being easy to use for even the most unsophisticated occupant, any energy-saving control activity, such as adjusting the nighttime temperature or turning off all heating/cooling just before departing the home, must be performed manually by the user. As such, substantial energy-saving opportunities are often missed for all but the most vigilant users. Moreover, more advanced energy-saving settings are not provided, such as the ability to specify a custom temperature swing, i.e., the difference between the desired set temperature and actual current temperature (such as 1 to 3 degrees) required to trigger turn-on of the heating/cooling unit.


In a second category, on the other hand, are many programmable thermostats, which have become more prevalent in recent years in view of Energy Star (US) and TCO (Europe) standards, and which have progressed considerably in the number of different settings for an HVAC system that can be individually manipulated. Unfortunately, however, users are often intimidated by a dizzying array of switches and controls laid out in various configurations on the face of the thermostat or behind a panel door on the thermostat, and seldom adjust the manufacturer defaults to optimize their own energy usage. Thus, even though the installed programmable thermostats in a large number of homes are technologically capable of operating the HVAC equipment with energy-saving profiles, it is often the case that only the one-size-fits-all manufacturer default profiles are ever implemented in a large number of homes. Indeed, in an unfortunately large number of cases, a home user may permanently operate the unit in a “temporary” or “hold” mode, manually manipulating the displayed set temperature as if the unit were a simple, non-programmable thermostat. Thus, there is a need for a thermostat having an improved user interface that is simple, intuitive and easy to use such that the typical user is able to access many of the features such as programming energy-saving profiles.


At a more general level, because of the fact that human beings must inevitably be involved, there is a tension that arises between (i) the amount of energy-saving sophistication that can be offered by an HVAC control system, and (ii) the extent to which that energy-saving sophistication can be put to practical, everyday use in a large number of homes. Similar issues arise in the context of multi-unit apartment buildings, hotels, retail stores, office buildings, industrial buildings, and more generally any living space or work space having one or more HVAC systems.


Some attempts have been made to make programing of programmable thermostat more appealing to greater numbers of users. For example, U.S. Pat. Nos. 7,181,317 and 7,634,504 discuss methods for programming configuration information for thermostats wherein a series of interview questions are asked to a user. The user responses to the questions are stored and one or more schedule parameters can be modified based on the user responses. It is believed, however, that such approaches rely heavily or entirely on the user's answers, and as a result will be either wasteful of energy and/or unnecessarily subject the occupants to uncomfortable temperatures when people make mistakes when enter their responses to the questions.


U.S. Pat. No. 7,784,704 discusses a self-programmable thermostat that initially appears to function as an ordinary manual thermostat. The thermostat privately observes and learns a user's manual temperature setting habits and eventually programs itself accordingly. The thermostat looks for patterns, such as three similar manual overrides on consecutive days. Manual set point changes override current programmed set point temperatures. It is believed, however, that further improvement can be made in discussed method's ability to generate energy efficient program schedules.


SUMMARY

According to some embodiments a thermostat is described that includes: a housing; a ring-shaped user-interface component configured to track a rotational input motion from a user; a processing system disposed within the housing and coupled to the ring-shaped user interface component, the processing system being configured to be in operative communication with one or more temperature sensors for receiving ambient air temperature, the processing system further being configured to be in operative communication with an HVAC system control the HVAC system based at least in part on a comparison of the measured ambient temperature and a setpoint temperature, the processing system further being configured to identify a user's desire to immediately control the setpoint temperature value based on the tracked rotational input, the processing system still further being configured to automatically reset the setpoint temperature to a less energy-consuming temperature upon an ending of a predetermined time interval and to generate, a schedule for the thermostat based at least in part on repeated identifications of the user's desire to immediately control the setpoint temperature; and an electronic display coupled to the processing system and configured to display information representative of the identified setpoint temperature value.


According to some embodiments, the electronic display is disposed along a front face of the thermostat housing, the ring-shaped user interface component comprises a mechanically rotatable ring that substantially surrounds the electronic display and is further configured to be inwardly pressable by the user along a direction of an axis of rotation of the rotational input motion, and the mechanically rotatable ring and the housing are mutually configured such that said mechanically rotatable ring moves inwardly along said direction of said axis of rotation when inwardly pressed. According to some embodiments the thermostat housing is generally disk-like in shape with the front face thereof being circular, and wherein the mechanically rotatable ring is generally coincident with an outer lateral periphery of said disk-like shape.


According to some embodiments, the electronic display is further configured to display to a user a notification relating to the generating of the schedule. According to some embodiments in cases where two or more immediate control setpoint temperature changes are identified within a short time interval of less than 90 minutes, the generating of the schedule is based on a latest of the two or more identifications. According to some embodiments, the automatic resetting of the setpoint temperature is to a base setpoint temperature of lower than 68 degrees Fahrenheit at times when the HVAC system uses heating and to a base setpoint temperature of greater than 78 degrees Fahrenheit at time when the HVAC system uses cooling. According to some embodiments the generated schedule is automatically adopted as an active schedule for the programmable thermostat.


According to some embodiments, a method is described for generating a schedule for a programmable thermostat used for control of an HVAC system, the thermostat comprising a housing, a ring-shaped user interface component, a processing system, and an electronic display. The described method includes: accessing an ambient air temperature measured by one or more temperature sensors; detecting and tracking rotational movements of the ring-shaped user-interface component to track at least one rotational input motion of a user; identifying a first setpoint temperature value based on the tracked rotational input motion at a first point in time; controlling the HVAC system based at least in part on a comparison of the measured ambient air temperature and the first setpoint temperature value for a predetermined time interval; automatically resetting the first setpoint temperature upon the ending of the predetermined time interval; identifying a second setpoint temperature value based on the tracked rotational input motion at a second point in time; controlling the HVAC system based at least in part on a comparison of the measured ambient air temperature and the second setpoint temperature value for the predetermined time interval; automatically resetting the second set point temperature upon the ending of the predetermined time interval; generating with the processing system, a schedule for the programmable thermostat based at least in part on the first and second setpoints and the first and second points in time; and displaying information representative of the first and second identified setpoint temperature values on the electronic display.


According to some embodiments, the generated schedule is automatically adopted as an active schedule for the programmable thermostat. According to other embodiments the user is notified of the generated schedule; and user input is received as to whether or not to adopt the generated schedule as an active schedule.


According to some embodiments a thermostat is described that includes: a disk-like housing including a circular front face; an electronic display centrally disposed on the front face; an annular ring member disposed around the centrally disposed electronic display, said annular ring member and said housing being mutually configured such that (i) said annular ring member is rotatable around a front-to-back axis of the thermostat, and (ii) said annular ring member is inwardly pressable along a direction of the front-to back axis; a processing system disposed within the housing and coupled to the annular ring member; the processing system being configured and programmed to dynamically alter a setpoint temperature value based on a user rotation of the annular ring member; the processing system being further configured to be in operative communication with one or more temperature sensors for receiving an ambient air temperature, said processing system being still further configured to be in operative communication with an HVAC system to control the HVAC system based at least in part on a comparison of the measured ambient temperature and the setpoint temperature value; the processing system being still further configured to identify from the annular ring member user input relating to the user's preference regarding automatically generating a schedule and to determine therefrom whether or not to automatically adopt an automatically generated schedule. According to some embodiments, an audio output device is includes that is coupled to said processing system, the thermostat being configured to output synthesized audible ticks through said audio output device in correspondence with user rotation of said mechanically rotatable ring.


As used herein the term “HVAC” includes systems providing both heating and cooling, heating only, cooling only, as well as systems that provide other occupant comfort and/or conditioning functionality such as humidification, dehumidification and ventilation.


As used herein the term “residential” when referring to an HVAC system means a type of HVAC system that is suitable to heat, cool and/or otherwise condition the interior of a building that is primarily used as a single family dwelling. An example of a cooling system that would be considered residential would have a cooling capacity of less than about 5 tons of refrigeration (1 ton of refrigeration=12,000 Btu/h).


As used herein the term “light commercial” when referring to an HVAC system means a type of HVAC system that is suitable to heat, cool and/or otherwise condition the interior of a building that is primarily used for commercial purposes, but is of a size and construction that a residential HVAC system is considered suitable. An example of a cooling system that would be considered residential would have a cooling capacity of less than about 5 tons of refrigeration.


As used herein the term “thermostat” means a device or system for regulating parameters such as temperature and/or humidity within at least a part of an enclosure. The term “thermostat” may include a control unit for a heating and/or cooling system or a component part of a heater or air conditioner.


As used herein the term “immediate-control input” to a setpoint temperature refers to input from a user to immediately alter the currently active setpoint temperature. Thus an immediate-control input to a thermostat, also sometimes referred to as a “real time” setpoint entry, indicates a user's desire to make an immediate change in the currently setpoint temperature in an HVAC system being controlled by the thermostat. Immediate-control inputs can be made by users either by directly manually interfacing with the thermostat, or by using a remote user interface such as by using a mobile phone, tablet computer and/or web interface on a computer.


As used herein the term “schedule-change input” refers to input from a user or other source to modify a programmed schedule for setpoint changes. Thus a user's schedule-change input to a thermostat, also sometime referred to as a “non-real-time” setpoint entry or change, indicates the user's desire to make changes to one or more of the thermostat's programmed setpoints. In contrast to an immediate control input, where the user desires to immediately effect the currently active setpoint, a schedule-change input indicates a user's desire to make a change (for example temperature or time) to a setpoint that will become active in the future. As in the case of immediate-control inputs, users can make schedule-change inputs either by directly manually interfacing with the thermostat, or by using a remote user interface such as by using a mobile phone, tablet computer and/or web interface on a computer.


It will be appreciated that these systems and methods are novel, as are applications thereof and many of the components, systems, methods and algorithms employed and included therein. It should be appreciated that embodiments of the presently described inventive body of work can be implemented in numerous ways, including as processes, apparatuses, systems, devices, methods, computer readable media, computational algorithms, embedded or distributed software and/or as a combination thereof. Several illustrative embodiments are described below.





BRIEF DESCRIPTION OF THE DRAWINGS

The inventive body of work will be readily understood by referring to the following detailed description in conjunction with the accompanying drawings, in which:



FIG. 1 is a diagram of an enclosure in which environmental conditions are controlled, according to some embodiments;



FIG. 2 is a diagram of an HVAC system, according to some embodiments;



FIGS. 3A-B illustrate a thermostat having a user-friendly interface, according to some embodiments;



FIGS. 4A-C show aspects of a user interface for a thermostat having learning and self-programming capabilities, according to some embodiments;



FIGS. 5A-B show aspects of a user interface for generating a program, according to some embodiments;



FIGS. 6A-C show examples of basic schedules generated based on answers to basic questions, such as those shown in FIG. 5B, according to some embodiments;



FIGS. 7A-E show aspects of a user interface for a thermostat that generates potential schedule adjustments and suggests them to a user for review and acceptance, according to some embodiments;



FIG. 8 shows an example of a web-based user interface for a thermostat that generates potential schedule adjustments and suggests them to a user for review and acceptance, according to some embodiments;



FIGS. 9A-D show aspects of a user interface for a thermostat adapted to learn and generate a schedule based on immediate-control inputs made by the occupants, according to some embodiments;



FIGS. 10A-D show examples of automatically generating a schedule using a “flat line” starting point and learning from immediate-control inputs, according to some embodiments; and



FIGS. 11A-C show examples of automatically generating a schedule using a “flat line” starting point and learning from immediate-control inputs, according to some embodiments.





DETAILED DESCRIPTION

A detailed description of the inventive body of work is provided below. While several embodiments are described, it should be understood that the inventive body of work is not limited to any one embodiment, but instead encompasses numerous alternatives, modifications, and equivalents. In addition, while numerous specific details are set forth in the following description in order to provide a thorough understanding of the inventive body of work, some embodiments can be practiced without some or all of these details. Moreover, for the purpose of clarity, certain technical material that is known in the related art has not been described in detail in order to avoid unnecessarily obscuring the inventive body of work.



FIG. 1 is a diagram of an enclosure in which environmental conditions are controlled, according to some embodiments. Enclosure 100, in this example is a single-family dwelling. According to other embodiments, the enclosure can be, for example, a duplex, an apartment within an apartment building, a light commercial structure such as an office or retail store, or a structure or enclosure that is a combination of the above. Thermostat 110 controls HVAC system 120 as will be described in further detail below. According to some embodiments, the HVAC system 120 is has a cooling capacity less than about 5 tons. According to some embodiments, a remote device 112 wirelessly communicates with the thermostat 110 and can be used to display information to a user and to receive user input from the remote location of the device 112. Although many of the embodiments are described herein as being carried out by a thermostat such as thermostat 110, according to some embodiments, the same or similar techniques are employed using a remote device such as device 112.



FIG. 2 is a diagram of an HVAC system, according to some embodiments. HVAC system 120 provides heating, cooling, ventilation, and/or air handling for the enclosure, such as a single-family home 100 depicted in FIG. 1. The system 120 depicts a forced air type heating system, although according to other embodiments, other types of systems could be used. In heating, heating coils or elements 242 within air handler 240 provide a source of heat using electricity or gas via line 236. Cool air is drawn from the enclosure via return air duct 246 through filter 270, using fan 238 and is heated heating coils or elements 242. The heated air flows back into the enclosure at one or more locations via supply air duct system 252 and supply air grills such as grill 250. In cooling, an outside compressor 230 passes gas such a Freon through a set of heat exchanger coils to cool the gas. The gas then goes to the cooling coils 234 in the air handlers 240 where it expands, cools and cools the air being circulated through the enclosure via fan 238. According to some embodiments a humidifier 254 is also provided. Although not shown in FIG. 2, according to some embodiments the HVAC system has other known functionality such as venting air to and from the outside, and one or more dampers to control airflow within the duct systems. The system is controlled by algorithms implemented via control electronics 212 that communicate with a thermostat 110. Thermostat 110 controls the HVAC system 120 through a number of control circuits. Thermostat 110 also includes a processing system 260 such as a microprocessor that is adapted and programmed to controlling the HVAC system and to carry out the techniques described in detail herein.



FIGS. 3A-B illustrate a thermostat having a user-friendly interface, according to some embodiments. Unlike so many prior art thermostats, thermostat 300 preferably has a sleek, simple, uncluttered and elegant design that does not detract from home decoration, and indeed can serve as a visually pleasing centerpiece for the immediate location in which it is installed. Moreover user interaction with thermostat 300 is facilitated and greatly enhanced over conventional designs by the design of thermostat 300. The thermostat 300 includes control circuitry and is electrically connected to an HVAC system, such as is shown with thermostat 110 in FIGS. 1 and 2. Thermostat 300 is wall mounted and has circular in shape and has an outer rotatable ring 312 for receiving user input. Thermostat 300 has a large frontal display area 314. According to some embodiments, thermostat 300 is approximately 80 mm in diameter. The outer rotating ring 312 allows the user to make adjustments, such as selecting a new target temperature. For example, by rotating the outer ring 312 clockwise, the target temperature can be increased, and by rotating the outer ring 312 counter-clockwise, the target temperature can be decreased. Within the outer ring 312 is a clear cover 314 which according to some embodiments is polycarbonate. Also within the rotating ring 312 is a metallic portion 324, preferably having a number of windows as shown. According to some embodiments, the surface of cover 314 and metallic portion 324 form a curved spherical shape gently arcing outward that matches a portion of the surface of rotating ring 312.


According to some embodiments, the cover 314 is painted or smoked around the outer portion, but leaving a central display 316 clear so as to facilitate display of information to users. According to some embodiments, the curved cover 314 acts as a lens which tends to magnify the information being displayed in display 316 to users. According to some embodiments central display 316 is a dot-matrix layout (individually addressable) such that arbitrary shapes can be generated, rather than being a segmented layout. According to some embodiments, a combination of dot-matrix layout and segmented layout is employed. According to some embodiments, central display 316 is a backlit color liquid crystal display (LCD). An example of information is shown in FIG. 3A, which are central numerals 320. According to some embodiments, metallic portion 324 has number of openings so as to allow the use of a passive infrared proximity sensor 330 mounted beneath the portion 324. The proximity sensor as well as other techniques can be use used to detect and/or predict occupancy, as is described further in co-pending patent application U.S. Ser. No. 12/881,430, which is incorporated by reference herein. According to some embodiments, occupancy information is used in generating an effective and efficient scheduled program.


According to some embodiments, for the combined purposes of inspiring user confidence and further promoting visual and functional elegance, the thermostat 300 is controlled by only two types of user input, the first being a rotation of the outer ring 312 as shown in FIG. 3A (referenced hereafter as a “rotate ring” input), and the second being an inward push on the upper cap 308 (FIG. 3B) until an audible and/or tactile “click” occurs (referenced hereafter as an “inward click” input). For further details of suitable user-interfaces and related designs which are employed, according to some embodiments, see co-pending U.S. patent application Ser. Nos. 13/033,573 and 29/386,021, both filed Feb. 23, 2011, and are incorporated herein by reference. The subject matter of the instant patent specification is further related to that of the following commonly assigned applications, each of which is incorporated by reference herein: U.S. Ser. No. 13/279,151 filed Oct. 21, 2011; U.S. Prov. Ser. No. 61/627,996 filed Oct. 21, 2011; U.S. Prov. Ser. No. 61/550,343 filed Oct. 21, 2011; and U.S. Prov. Ser. No. 61/550,346 filed Oct. 21, 2011.


According to some embodiments, the thermostat 300 includes a processing system 360, display driver 364 and a wireless communications system 366. The processing system 360 is adapted to cause the display driver 364 and display area 316 to display information to the user, and to receiver user input via the rotating ring 312. The processing system 360, according to some embodiments, is capable of maintaining and updating a thermodynamic model for the enclosure in which the HVAC system is installed. For further detail on the thermodynamic modeling, see U.S. patent Ser. No. 12/881,463 filed, which is incorporated by reference herein. According to some embodiments, the wireless communications system 366 is used to communicate with devices such as personal computers and/or other thermostats or HVAC system components.



FIGS. 4A-C show aspects of a user interface for a thermostat having learning and self-programming capabilities, according to some embodiments. FIG. 4A shows an example of a display 316 of thermostat 300 described with respect to FIGS. 3A-B. The display 316 indicates that the user is making settings with respect to the thermostat's learning functionality. The colored disk 410 indicates that the learning setting that will be entered, if selected using an inward click, relates to whether the user will be asked about changes made to the program schedule. FIG. 4B shows the display 316 following a user selection using an inward click. In FIG. 4B, the user is asked to if the thermostat should adjust the schedule automatically. Using the rotating ring the and inward click the user selects “yes” or “no.” If the user selects “yes,” then in step 420 the thermostat automatically generates one or more programs, such as described more fully herein. If the user selects “no,” the thermostat, according to some embodiments, the thermostat nevertheless records some or all of the user's adjustments in set temperature and generates suggested schedule changes according to certain criteria (for example, energy or cost savings to the user). According to some embodiments, if the user answers “no” to the question about automatically adjusting the schedule, the thermostat asks the user, as shown in display 316 of FIG. 4C, if the thermostat should suggest changes to the user each week. If the user answers “yes,” then in step 422, the thermostat generates a schedule based on learning from the user's immediate-control inputs in combination with other information, and periodically suggests changes to the user according to certain criteria (for example, energy saving or costs savings). If the user answers “no,” then in step 424 the thermostat does not generate any program and instead always follows the program set by the user.



FIGS. 5A-B show aspects of a user interface for generating a program, according to some embodiments. In FIG. 5A, the user can select entering set-up questions relating to the schedule settings as indicated by the colored disk 510, using an inward click input while the thermostat is displays the screen as shown in display 316. FIG. 5B is a flow chart showing questions that can be asked of the user in order to generate a basic schedule, according to some embodiments. As can be seen from the flow chart 512 of FIG. 5B, the user is initially asked if the thermostat is installed in a home or business. Then some basic questions are asked to generate a basic schedule, such as whether the home is usually occupied at noon, is someone usually up after 11 pm, and whether or not there is more than one thermostat in the home. Similar questions are asked is the thermostat is installed in a business. According to some embodiments, a basic schedule is generated based on the answers to the questions in FIG. 5B.



FIGS. 6A-B show examples of basic schedules generated based on answers to basic questions, such as those shown in FIG. 5B, according to some embodiments. In FIG. 6A, curve 610 shows a basic schedule for setpoints from 6 am Tuesday to 6 am Wednesday, which corresponds to a home that the user indicated is occupied during noon and the user indicated that someone is not usually up at 11 pm. As can be seen, the setpoint temperature changes at 7 am from 62 degrees to 72 degrees and then stays at 72 degrees until 10 pm when it changes back to 62 degrees. In FIG. 6B, curve 612 shows a basic schedule that corresponds to a home that the user indicated is not occupied during noon and that someone is not usually up at 11 pm. As can be seen, the set point temperature changes at 7 am from 62 degrees to 72 degrees. Then, at 9 am, the temperature is set back to 62 degrees until 5 pm, when the set point is changed to 72 degrees. The set back from 9 am to 5 pm is due to the user's indication that no one is usually home at noon. In FIG. 6C, curve 614 corresponds to a user's indication that no one is usually home at noon, and some one is usually up at 11 pm. In this case the evening set back time is set to midnight. As can be seen a basic schedule is limited by the simple questions that it is based upon, and as a results the occupants may either be uncomfortable, or energy use and costs may be higher than necessary. For example, the occupants may get up before 7 am, or they may be perfectly comfortable at 68 degrees instead of 72 degrees. According to some embodiments, further questions are asked of the user, such as whether someone is usually up at 6:30 am, or if the occupants are comfortable at 68 degrees. However, each additional question detracts from the simple user interface experience, as well as introduces potential errors based on wrong answers and/or misunderstood questions.


According to some embodiments, after generating the basic schedule based on a few simple questions such as shown in FIGS. 6A-C, the thermostat learns from the user's immediate-control inputs and periodically suggests, or automatically implements schedule changes that meet certain criteria.



FIGS. 7A-E show aspects of a user interface for a thermostat that generates potential schedule adjustments and suggests them to a user for review and acceptance, according to some embodiments. FIG. 7A show the thermostat 300 with display 316. A message bubble 710 is overlaid on the display 316 to obtain the user's attention. According to some embodiments, one or more proximity sensors (not shown) are used to detect when an occupant is approaching the thermostat 300. Upon sensing an approaching occupant, the message bubble 710 is displayed in order to obtain the user's attention. If the user wishes further information an inward click input leads to the display 316 shown in FIG. 7B. In FIG. 7B, the thermostat indicates to the user that a new schedule has been calculated that is estimated would have saved about 10% of energy costs in the past week. The user has the choice to view the new schedule or reject it. If the user indicates a desire to see the new schedule, then an animation is displayed which alternates between FIG. 7C showing the current schedule, and FIG. 7D showing the proposed new schedule. In FIG. 7C, the current set point temperature 722 is shown and the applicable time 724 is shown below. In FIG. 7D, the new set point temperature 722 is shown and the new time 724 is shown below. If there are further changes to the schedule then those can be accessed by rotating the ring to the right or left. When the user is finished reviewing the new schedule, the user, in FIG. 7E is given the choice to updated the schedule or not.



FIG. 8 shows an example of a web-based user interface for a thermostat that generates potential schedule adjustments and suggests them to a user for review and acceptance, according to some embodiments. A computer monitor 810 is used to display to a user of the thermostat suggested schedule changes. The user can use a pointing device such as mouse 820 to move a pointer 822 to provide input. In the window 812, the user is asked in bubble 814 whether the displayed schedule change should be adopted. According to some embodiments, further information, such as the estimated amount of energy savings associated with the proposed change can be displayed to aid the user in making a decision. The current schedule is shown in solid circles and the proposed changes are shown in dotted circles. For example, the set back time to 62 degrees in the morning is suggested to be changed from 9 am (shown by solid circle 830) to about 9:30 am (shown by dotted circle 832), and the evening set back to 62 degrees is suggested to be changed from midnight (shown by the solid circle 840) to about 10:15 pm (shown by the dotted circle 842). According to some embodiments, a “snap” button or similar can be provided to the user for the user to easily adopt all the suggested schedule changes. According to some embodiments, the user can also use the interface as shown in FIG. 8 to make their own adjustments and/or accept or reject particular suggested changes by clicking and dragging the circles along the time line, and/or by changing the temperature value within one or more of the circles. According to some embodiments, the interface screen such as shown in FIG. 8 can be displayed at the request of the user, or it can be shown at the request of a central server, such as is common in push technology. According to some embodiments, the decision on when to “push” a notification of a suggested schedule change can be based at least in part on an estimation of energy and/or cost savings being above a predetermined threshold or percentage value.


While simply observing and recording a user's immediate-control inputs can be useful in generating a schedule and/or adjustments to an existing scheduled program, it has been found, unexpectedly, that the thermostat can more effectively learn and generate a scheduled program that makes the user more comfortable while saving energy and cost when the user is periodically urged to input settings to maintain or improve the user's comfort. Bothering the user by periodically urging manual input may at first appear to run counter to a user-friendly experience, but it has been found that this technique very quickly allows the thermostat to generate a schedule that improves user comfort while saving costs, and thus turns out to be very user-friendly overall.


According to some preferred embodiments, therefore, a user's set point change automatically expires after a predetermined amount of time. By automatically resetting or setting back a user's set point adjustment after a predetermined amount of time, the user is urged to repeatedly make set point changes to maintain or improve comfort. As a result, the thermostat is able to learn and generate a much more effective schedule in terms of both comfort for the occupants as well as energy efficiency and cost savings. In this way, the thermostat can learn both the set point temperature, the occupants regard as providing comfort, as well as the times of the day when the user benefits from set point changes, as well as times of the day, such as during periods when the conditioned zone is unoccupied, when the set point temperature can be set back in order to save cost and energy while having a little or no impact on occupant comfort.



FIGS. 9A-D show aspects of a user interface for a thermostat adapted to learn and generate a schedule based on immediate-control changes made by the occupants, according to some embodiments. In FIG. 9A, the thermostat 300 uses display 316 to inform the user using message bubble 920 that the thermostat is in the process of learning in order to generate a schedule that is suitable for the occupants. The user is asked to adjust the thermostat frequently to make the user comfortable. As shown in FIG. 9A, the current set point temperature is set to 62 degrees F. as indicated by the set point tick 910. In FIG. 9B, a user adjusts the set point temperature, or makes an immediate-control input, to improve comfort by rotating the outer ring 312. The current temperature is 62 degrees F., as indicated by the current temperature tick 912, and the set point has been adjusted to 75, as indicated by the set point tick 910 and by the large central numerals. Additionally, the user is reminded that the thermostat is learning by a flashing “learning” message 922. FIG. 9C shows display 316 following an immediate-control input such as described with respect to FIG. 9B. According to some embodiments, as described above, immediate-control input expires after a predetermined amount of time so as to enhance the ability of the thermostat 300 to learn and generate effective and efficient schedules. The current temperature of 75 degrees F. is displayed in the large central numerals. The set point temperature, which was manually entered as an immediate-control input, is shown by the set point tick 910. The user is informed that the immediate-control input will automatically expire at 6:35 pm in message 930. According to an alternate embodiment, a the message 930 displays a countdown timer showing how many minutes remain until the user's immediate-control input expires. FIG. 9D shows a message bubble 932 that informs the user that a comfortable nighttime temperature should be manually entered just prior to going to bed. According to some embodiments, the message such as shown in FIG. 9D is automatically displayed after a certain time of day (such as 9 pm) when one or more proximity sensors detect when an occupant is approaching the thermostat 300.


It has been found, quite unexpectedly, that in many circumstances the thermostat can more quickly and effectively generate a schedule that balances user comfort with cost and energy savings, when the starting point for gathering the user's input is a “flat-line” or constant temperature that may be quite uncomfortable to many users, but saves significant energy. For example the starting point or initial setting for the thermostat in geographic locations and times of the year when heating is predominantly called for (rather than cooling) is a constant low temperature such as 62 degrees F. In geographic locations and times of year when cooling is predominantly called for the starting “flat line” is, for example, 85 degrees F. This “flat-line” starting point, when combined with automatic re-setting or expiring of the user's immediate-control inputs after a predetermined amount of time has been found to be more effective in many situations than starting with a basic schedule based on a number of basic questions, such as showing in FIG. 5B.



FIGS. 10A-D show examples of automatically generating a schedule using a “flat line” starting point and learning from immediate-control inputs, according to some embodiments. FIG. 10A shows the starting point schedule 1010 which is a “flat line” of 62 degrees throughout the day. According to some embodiments, the starting point temperature is selected using a number of criteria. Firstly, a determination should be made as to whether heating or cooling is likely to be called for. In cases where the HVAC system being controlled by the thermostat has both heating and cooling functionality, then the determination of which to use can in many or most cases be made using a combination of geographic location (e.g. using postal or ZIP code) which is known or gathered from basic set up information, and the time of year (from the date). In some locations and times of the year, however, it may be unclear whether the user will want to predominantly use heating or cooling. According to some embodiments, the user's first immediate-control input is used in such cases. For example, if the user makes an immediate-control input to set the temperature greater than the ambient temperature, then it is assumed heating is wanted. According to other embodiments, the user is asked using a message bubble or the like, in such cases. Secondly, a determination should be made as to what temperature should be used as the base “flat line.” According to some embodiments, a temperature is selected at which many or most occupants would consider at least somewhat uncomfortable such that an occupant would likely wish to make an immediate-control input to improve comfort. The base temperature should not be too uncomfortable, however, since doing so would unnecessarily subject to occupants to discomfort. It has been found that when heating is called for, a base value of between 60 and 64 degrees is suitable for many geographic locations.


According to some embodiments, the user is notified that the thermostat is trying to learn and generate a schedule, such as using a message bubble as shown in FIG. 9A. In FIG. 10B, the curve 1012 shows the user's immediate-control inputs throughout the day and curve 1014 shows the indoor temperature sensed by the thermostat. A time 1020, about 7:15 am, the user makes an immediate-control input to change the set point temperature from 62 degrees to 72 degrees. According to some embodiments, the set point temperature automatically is set to expire after a predetermined amount of time, which in this example is two hours. Thus, at about 9:15 am, the set point is automatically set back to the base line value of 62 degrees. In this example the user has gone out of the house for the day, and so does not make any immediate-control inputs until the user returns home. At time 1022, about 5:20 pm, the user makes an immediate-control input to adjust the set point to 68 degrees. In this example the predetermined expiry period is two hours, so the set point is automatically set back to 62 degrees at about 7:20 pm. According to some embodiments, the user is informed of the expiry time using a message such as shown in FIG. 9C. Still referring to FIG. 10B, the user at time 1024, about 7:45 pm, the user makes an immediate-control input to adjust the set point temperature to 69 degrees. The set point is automatically set back to 62 degrees after two hours, at about 9:45 pm. In this example, the occupants have gone to bed before or not long after 9:45, so no further immediate-control inputs are made that day.



FIG. 10C shows a schedule curve 1016 that has been generated based on the user's immediate-control inputs on the previous day (as shown in FIG. 10B). The temperature is set in the morning at 7:15 am to 72 degrees until it is set back at 9:15 am to 62 degrees. At 5:20, the temperature is set to 69 degrees until it is set back at 9:45 pm to 62 degrees. Note that both the times of day and set point temperatures have been used in generating the schedule shown in FIG. 10C. Additionally, according to some embodiments, the short gap from 7:20, when the temperature was automatically set back, and 7:45 when the user made an immediate-control input, is ignored. Also, the setpoint temperatures in the evening of 68 and 69 degrees where not identical and either an average or the later set temperature was used, in this case 69 degrees.


According to some embodiments, the shortest time for a scheduled set point segment is set to 60 minutes. If two immediate-control inputs occur within the 60 minutes of each other, the later will generally be use and the earlier setting or settings will be ignored. FIG. 10D illustrates some example scenarios, with curve 1030 showing the set point temperature of the thermostat as manually and automatically adjusted, and curve 1032 shows the current indoor temperature sensed by the thermostat. At time 1040, about 7:15 am, the an immediate-control input is made by the user change the set point to 77 degrees, but about 30 minutes later at time 1044, about 7:45 am, the user makes an immediate-control input changing the set point to 72 degrees. Since the two immediate-control inputs occurred within a short time (in this case 30 minutes), the first setting is assumed to be erroneous and is ignored for purposed of the automatically generated schedule. Similarly, a time 1046 an immediate-control input is made and about 20 minutes later an immediate-control input resets the temperature to the base line level. Since the setting was effectively cancelled, it is assumed to be erroneous and ignored for purposed of the automatically generated schedule. If, on the other hand, the immediate-control input was not reset for 45 minutes or more, then the immediate-control input is not ignored, according to some embodiments, and segment would be created in the generated schedule for 60 minutes duration. Note that following the described rules, the immediate-control inputs as shown in curve 1030 would lead to an automatically generated schedule as shown by curve 1016 in FIG. 10C.



FIGS. 11A-C show examples of automatically generating a schedule using a “flat line” starting point and learning from immediate-control inputs, according to some embodiments. FIG. 11A shows set point curve 1110 that is an example of a “flat line” base value of 80 degrees that is suitable when cooling is believed to be predominantly called for (e.g. based on the geographic location and time of year, as described above). In FIG. 11B, curve 1112 shows the set point settings from immediate-control inputs and automatic resets, and curve 1114 shows the ambient indoor temperature as sensed by the thermostat. In this example, the predetermined expiry time (or reset time) is 1.5 hours. At 7:10 am, the user makes an immediate-control input to 70 degrees. The set point is maintained for 1.5 hours, and at 8:40 am, the set point is automatically set back to 80 degrees. At 5:11 pm the user returns home and makes an immediate-control input to 73 degrees which is maintained for 1.5 hours. At 6:41 pm this set point “expires” and set point is automatically set back to the base value of 80 degrees. At 7:16 pm the user again makes an immediate-control input, but this time to 72 degrees. At 8:46 pm this set point “expires” and the set point is automatically set back to the base value of 80 degrees. At 9:44 pm, the user again makes an immediate-control input to 72 degrees. At 11:14 pm this set point expires, but the user makes no further immediate-control inputs. FIG. 11C shows an example of a schedule 1116 that is automatically generated based on the user input shown in curve 1112 of FIG. 11B. In schedule 1116, a set point of 70 degrees is made between 7:10 am and 8:40 am. During the day, the house is assumed to be unoccupied (since no immediate-control inputs were made on the learning day shown in FIG. 11B), and the temperature is set back to 80 degrees. At 5:11 pm the temperature is set to 73 degrees and then from 7:16 pm to 11:14 pm the temperature is set to 72 degrees.


Note that in the examples shown in FIGS. 10A-D the predetermined expiry time is 2 hours and in the examples shown FIGS. 11A-C the predetermined expiry time is 1.5 hours. It has been found, if the period of time after which the user's immediate-control input is shorter than 30 minutes, this generally cause excessive annoyance to the occupants. On the other hand, if the time is greater than 6 hours, the resulting generated schedule is likely to be wasteful of cost and energy since periods of non-occupancy and/or sleeping are not accurately captured. According to some embodiments the time period is greater than 1 hour and less than or equal to 5 hours.


According to some preferred embodiments, time periods of between 1.5 hours and 3 hours have been found to strike a very good compromise between annoyance to the occupants and energy efficiency of the resulting schedule.


According to some embodiments, the learning process described herein with respect to FIGS. 9-11 can be carried out separately for weekdays versus weekend days. For example, the “flat-line” learning method described can be carried out on a weekday as described which generates a suitable schedule for weekdays. Then, on the first weekend day, a new “flat-line” learning process is started, since it is assumed that for many people the weekday and weekend day schedules are vastly different.


According to some embodiments, the described learning processes continue even after a schedule is activated. For example, following a learning process, a schedule such as shown in FIGS. 10C and/or 11C are generated and activated. The thermostat continues to learn by watching and recording immediate-control inputs. After repeated immediate-control inputs are made, the decision is made as whether and schedule change are automatically implemented or suggested to the user. According to some embodiments, if a user makes similar immediate-control inputs three days in a row (where “similar” is defined, for example, as adjustments within 5 degrees made with 60 minutes of each other), a schedule-change is automatically inputted (and the user notified), or the schedule-change input is suggested to the user. According to some embodiments, estimated energy and/or cost savings is also used as a criterion for implementing or suggesting schedule-change inputs.


According to some embodiments, the continued learning process as described above is used for adjusting, or suggesting improvements to a basic schedule generated from a basic set of questions as shown in and described with respect to FIGS. 5-6. However, it has been found that in many applications, starting with a “flat-line” works to more effectively learn the user's preferences. According to some embodiments, the continued learning process is also carried out in cases where the user has indicated that they wish to manually enter their own scheduled program. In such cases, for example, changes to the schedule can be suggested according to the potential for energy and/or cost savings.


According to some embodiments, occupancy data can also be incorporated in the process of automatically generating a schedule for adoption and/or suggestion to the user. It has been found that occupancy data is particularly useful in cases using automatic set back after a time period, where the time is relatively long-such as three or more hours. In cases where the thermostat is installed in a dwelling that is relatively large, then local-proximity-based occupancy sensing may not be accurate for relatively short periods of time because occupants may simply be in a different part of the dwelling during that time period. However, if there is no occupancy sensed close to the thermostat for greater than two hours, then it is increasingly likely that the dwelling is in fact not occupied.


Although the foregoing has been described in some detail for purposes of clarity, it will be apparent that certain changes and modifications may be made without departing from the principles thereof. It should be noted that there are many alternative ways of implementing both the processes and apparatuses described herein. Accordingly, the present embodiments are to be considered as illustrative and not restrictive, and the inventive body of work is not to be limited to the details given herein, which may be modified within the scope and equivalents of the appended claims.

Claims
  • 1. A method for HVAC control schedule learning, comprising: receiving, over a learning period of time, a population of immediate-control inputs, wherein: each immediate-control input of the population indicates user desire to make an immediate change to a current setpoint temperature being used by a thermostat to control an HVAC system;each immediate-control input of the population is selected from the group consisting of: a user manually interfacing with a user input component of the thermostat; andinteraction with a user interface provided via a remote computerized device;upon receipt of each of said immediate-control input: operating, by the thermostat, the HVAC system according to a temperature defined by that immediate-control input until that immediate-control input expires after a first predetermined time interval during which an additional immediate-control input is not received; andupon the immediate-control input expiring after the first predetermined time interval, performing a setback event in which the thermostat operates the HVAC system at a predetermined lower energy setpoint temperature until such time as a next immediate-control input is received, thereby producing a population of setback events over the learning period; andafter the learning period of time, generating a learned HVAC schedule based on the population of immediate-control inputs and the population of the setback events.
  • 2. The method of claim 1 wherein each setback event is processed to affect the learned HVAC schedule similar to each immediate-control input unless, during the learning period, the setback event was overridden within a defined time period by a subsequent immediate-control input.
  • 3. The method of claim 2, wherein the defined time period is 25 minutes or less.
  • 4. The method of claim 1, wherein the first predetermined time interval is within a range of 1.5 hours to 3 hours.
  • 5. The method of claim 1, wherein the first predetermined time interval is within a range of 30 minutes to 6 hours.
  • 6. The method of claim 1, wherein receiving the population of immediate-control inputs comprises a first immediate-control input and a second immediate-control input being received within a defined time period of each other during the learning period of time; and generating the learned HVAC schedule comprises ignoring the first immediate-control input based on less than the defined time period being present between receiving of the first immediate-control input and the second immediate-control input.
  • 7. The method of claim 6, wherein the defined time period is 30 minutes or less.
  • 8. The method of claim 1, wherein the learning period of time corresponds to one or more weekdays; and the method further comprises: controlling, by the thermostat, the HVAC system in accordance with the learned HVAC schedule on weekdays.
  • 9. The method of claim 8 further comprising: receiving, over a weekend learning period of time, a second population of immediate-control inputs;after the weekend learning period of time, generating a weekend learned HVAC schedule by processing the second population of immediate-control inputs; andcontrolling, by the thermostat, the HVAC system in accordance with the weekend learned HVAC schedule on weekend days.
  • 10. A thermostat that performs HVAC control schedule learning, the thermostat comprising: one or more temperature sensors;a user interface for receiving input from one or more users;control circuitry electrically connected with an HVAC system, wherein the control circuitry allows the thermostat to control operation of the HVAC system;one or more processors that communicate with the one or more temperature sensors, the user interface, and the control circuitry; anda processor-readable medium communicatively coupled with and readable by the one or more processors and having stored therein processor-readable instructions which, when executed by the one or more processors, cause the one or more processors to: receive, over a learning period of time, a population of immediate-control inputs, wherein: each immediate-control input of the population indicates user desire to make an immediate change to a current setpoint temperature being used by the thermostat to control the HVAC system;each immediate-control input of the population is selected from the group consisting of: a user of the one or more users manually interfacing with a user input component of the thermostat; andinteraction with the user interface provided via a remote computerized device;upon receipt of each of said immediate-control input: operate the HVAC system according to a temperature defined by that immediate-control input until that immediate-control input expires after a first predetermined time interval during which an additional immediate-control input is not received; andupon the immediate-control input expiring after the first predetermined time interval, perform a setback event in which the thermostat operates the HVAC system at a predetermined setpoint temperature until such time as a next immediate-control input is received, thereby producing a population of setback events over the learning period; andafter the learning period of time, generate a learned HVAC schedule using the population of immediate-control inputs and the population of the setback events.
  • 11. The thermostat of claim 10 wherein at least a portion of the population of immediate-control inputs are received by the one or more processors from the user interface of the thermostat.
  • 12. The thermostat of claim 10, further comprising a wireless communication system, wherein at least a portion of the population of immediate-control inputs are received by the one or more processors from a remote device via the wireless communication system.
  • 13. The thermostat of claim 10 wherein each setback event is processed by the one or more processors of the thermostat to create the learned HVAC schedule similar to each immediate-control input unless, during the learning period, the setback event was overridden within a defined time period by a subsequent immediate-control input.
  • 14. The thermostat of claim 10, wherein the first predetermined time interval is within a range of 1.5 hours to 3 hours.
  • 15. The thermostat of claim 10, wherein the first predetermined time interval is within a range of 30 minutes to 6 hours.
  • 16. The thermostat of claim 10, wherein: the receiving of the population of immediate-control inputs comprises a first immediate-control input and a second immediate-control input being received by the one or more processors within a defined time period of each other during the learning period of time; andthe generating of the learned HVAC schedule comprises ignoring the first immediate-control input based on less than the defined time period being present between receiving of the first immediate-control input and the second immediate-control input.
  • 17. The thermostat of claim 16, wherein the defined time period is 30 minutes or less.
  • 18. The thermostat of claim 10, wherein the learning period of time corresponds to one or more weekdays; and the processor-readable instructions which, when executed by the one or more processors, further cause the one or more processors to control the HVAC system in accordance with the learned HVAC schedule on weekdays.
  • 19. The thermostat of claim 18 wherein the processor-readable instructions, when executed, further cause the one or more processors to: receive, over a weekend learning period of time, a second population of immediate-control inputs;after the weekend learning period of time, generate a weekend learned HVAC schedule by processing the second population of immediate-control inputs; andcontrol the HVAC system using the control circuitry in accordance with the weekend learned HVAC schedule on weekend days.
  • 20. A non-transitory processor-readable medium for HVAC control schedule learning, comprising processor-readable instructions configured to cause one or more processors to: receive, over a learning period of time, a population of immediate-control inputs, wherein: each immediate-control input of the population indicates user desire to make an immediate change to a current setpoint temperature being used by a thermostat to control an HVAC system;each immediate-control input of the population is selected from the group consisting of: (i) a user manually interfacing with a user input component of the thermostat; and(ii) interaction with a user interface provided via a remote computerized device;upon receipt of each of said immediate-control input: operating the HVAC system according to a temperature defined by that immediate-control input until that immediate-control input expires after a first predetermined time interval; andupon the immediate-control input expiring after the first predetermined time interval, performing a setback event in which the thermostat operates the HVAC system at a predetermined setpoint temperature until such time as a next immediate-control input is received, thereby producing a population of setback events over the learning period; andafter the learning period of time, generate a learned HVAC schedule based on: the population of immediate-control inputs; and the population of the setback events.
Parent Case Info

This application is a continuation of U.S. application Ser. No. 13/656,200 filed Oct. 19, 2012, which claims the benefit of U.S. Prov. Application Ser. No. 61/550,345 filed Oct. 21, 2011. U.S. application Ser. No. 13/656,200 is also a Continuation-in-Part of U.S. application Ser. No. 13/269,501 filed Oct. 7, 2011, now U.S. Pat. No. 8,918,219 issued Dec. 23, 2014, which claims the benefit of U.S. Prov. Application Ser. No. 61/415,771 filed Nov. 19, 2010. U.S. application Ser. No. 13/269,501 also claims the benefit of U.S. Prov. Application Ser. No. 61/429,093 filed Dec. 31, 2010. U.S. application Ser. No. 13/269,501 is also a Continuation-in-Part of U.S. application Ser. No. 13/033,573 filed Feb. 23, 2011, now U.S. Pat. No. 9,223,323 issued Dec. 29, 2015, all of which are incorporated by reference herein.

US Referenced Citations (514)
Number Name Date Kind
2558648 Warner Jun 1951 A
3991357 Kaminski Nov 1976 A
4223831 Szarka Sep 1980 A
4316577 Adams et al. Feb 1982 A
4335847 Levine Jun 1982 A
4408711 Levine Oct 1983 A
4460125 Barker et al. Jul 1984 A
4613139 Robinson, II Sep 1986 A
4615380 Beckey Oct 1986 A
4621336 Brown Nov 1986 A
4669654 Levine et al. Jun 1987 A
4674027 Beckey Jun 1987 A
4685614 Levine Aug 1987 A
4741476 Russo et al. May 1988 A
4751961 Levine et al. Jun 1988 A
4768706 Parfitt Sep 1988 A
4847781 Brown, III et al. Jul 1989 A
4897798 Cler Jan 1990 A
4971136 Mathur et al. Nov 1990 A
4997029 Otsuka et al. Mar 1991 A
5005365 Lynch Apr 1991 A
D321903 Chepaitis Nov 1991 S
5065813 Berkeley et al. Nov 1991 A
5088645 Bell Feb 1992 A
5115967 Wedekind May 1992 A
5211332 Adams May 1993 A
5224648 Simon et al. Jul 1993 A
5224649 Brown et al. Jul 1993 A
5240178 Dewolf et al. Aug 1993 A
5244146 Jefferson et al. Sep 1993 A
D341848 Bigelow et al. Nov 1993 S
5294047 Schwer et al. Mar 1994 A
5303612 Odom et al. Apr 1994 A
5395042 Riley et al. Mar 1995 A
5415346 Bishop May 1995 A
5460327 Hill et al. Oct 1995 A
5462225 Massara et al. Oct 1995 A
5476221 Seymour Dec 1995 A
5482209 Cochran et al. Jan 1996 A
5485954 Guy et al. Jan 1996 A
5499196 Pacheco Mar 1996 A
5544036 Brown, Jr. et al. Aug 1996 A
5555927 Shah Sep 1996 A
5603451 Helander et al. Feb 1997 A
5611484 Uhrich Mar 1997 A
5627531 Posso et al. May 1997 A
5673850 Uptegraph Oct 1997 A
5690277 Flood Nov 1997 A
5761083 Brown, Jr. et al. Jun 1998 A
D396488 Kunkier Jul 1998 S
5779143 Michaud et al. Jul 1998 A
5782296 Mehta Jul 1998 A
5808294 Neumann Sep 1998 A
5808602 Sellers Sep 1998 A
5816491 Berkeley et al. Oct 1998 A
5902183 D'Souza May 1999 A
5909378 De Milleville Jun 1999 A
5918474 Khanpara et al. Jul 1999 A
5924486 Ehlers et al. Jul 1999 A
5931378 Schramm Aug 1999 A
5959621 Nawaz et al. Sep 1999 A
5973662 Singers et al. Oct 1999 A
5977964 Williams et al. Nov 1999 A
6020881 Naughton et al. Feb 2000 A
6032867 Dushane et al. Mar 2000 A
6062482 Gauthier et al. May 2000 A
6066843 Scheremeta May 2000 A
D428399 Kahn et al. Jul 2000 S
6093914 Diekmann et al. Jul 2000 A
6095427 Hoium et al. Aug 2000 A
6098893 Berglund et al. Aug 2000 A
6122603 Budike, Jr. Sep 2000 A
6164374 Rhodes et al. Dec 2000 A
6206295 LaCoste Mar 2001 B1
6211921 Cherian et al. Apr 2001 B1
6213404 Dushane et al. Apr 2001 B1
6216956 Ehlers et al. Apr 2001 B1
6286764 Garvey et al. Sep 2001 B1
6298285 Addink et al. Oct 2001 B1
6311105 Budike, Jr. Oct 2001 B1
D450059 Itou Nov 2001 S
6318639 Toth Nov 2001 B1
6349883 Simmons et al. Feb 2002 B1
6351693 Monie et al. Feb 2002 B1
6356204 Guindi et al. Mar 2002 B1
6370894 Thompson et al. Apr 2002 B1
6415205 Myron et al. Jul 2002 B1
6438241 Silfvast et al. Aug 2002 B1
6453687 Sharood et al. Sep 2002 B2
D464660 Weng et al. Oct 2002 S
6478233 Shah Nov 2002 B1
6502758 Cottrell Jan 2003 B2
6513723 Mueller et al. Feb 2003 B1
6519509 Nierlich et al. Feb 2003 B1
D471825 Peabody Mar 2003 S
6574581 Bohrer et al. Jun 2003 B1
6595430 Shah Jul 2003 B1
6619055 Addy Sep 2003 B1
6622925 Earner et al. Sep 2003 B2
D480401 Kahn et al. Oct 2003 S
6636197 Goldenberg et al. Oct 2003 B1
6641054 Morey Nov 2003 B2
6641055 Tiernan Nov 2003 B1
6643567 Kolk et al. Nov 2003 B2
6644557 Jacobs Nov 2003 B1
6645066 Gutta et al. Nov 2003 B2
D485279 DeCombe Jan 2004 S
6726112 Ho Apr 2004 B1
D491956 Ombao et al. Jun 2004 S
6769482 Wagner et al. Aug 2004 B2
6785630 Kolk et al. Aug 2004 B2
6798341 Eckel et al. Sep 2004 B1
D497617 Decombe et al. Oct 2004 S
6814299 Carey Nov 2004 B1
6824069 Rosen Nov 2004 B2
6851621 Wacker et al. Feb 2005 B1
6864879 Nojima et al. Mar 2005 B2
D503631 Peabody Apr 2005 S
6891838 Petite et al. May 2005 B1
6909921 Bilger Jun 2005 B1
6951306 DeLuca Oct 2005 B2
D511527 Hernandez et al. Nov 2005 S
6975958 Bohrer et al. Dec 2005 B2
6990821 Singh et al. Jan 2006 B2
7000849 Ashworth et al. Feb 2006 B2
7024336 Salsbury et al. Apr 2006 B2
7028912 Rosen Apr 2006 B1
7035805 Miller Apr 2006 B1
7038667 Vassallo et al. May 2006 B1
7055759 Wacker et al. Jun 2006 B2
7083109 Pouchak Aug 2006 B2
7108194 Hankins, II Sep 2006 B1
7109970 Miller Sep 2006 B1
7111788 Reponen Sep 2006 B2
7114554 Bergman et al. Oct 2006 B2
7135965 Chapman, Jr. et al. Nov 2006 B2
7140551 de Pauw et al. Nov 2006 B2
7141748 Tanaka et al. Nov 2006 B2
7142948 Metz Nov 2006 B2
7149729 Kaasten et al. Dec 2006 B2
7152806 Rosen Dec 2006 B1
7156318 Rosen Jan 2007 B1
7159789 Schwendinger et al. Jan 2007 B2
7159790 Schwendinger et al. Jan 2007 B2
7181317 Amundson et al. Feb 2007 B2
7188482 Sadegh et al. Mar 2007 B2
7222494 Peterson et al. May 2007 B2
7222800 Wruck May 2007 B2
7225054 Amundson et al. May 2007 B2
7225057 Froman et al. May 2007 B2
D544877 Sasser Jun 2007 S
7258280 Wolfson Aug 2007 B2
D550691 Hally et al. Sep 2007 S
7264175 Schwendinger et al. Sep 2007 B2
7274972 Amundson et al. Sep 2007 B2
7287709 Proffitt et al. Oct 2007 B2
7289887 Rodgers Oct 2007 B2
7299996 Garrett et al. Nov 2007 B2
7302642 Smith et al. Nov 2007 B2
7333880 Brewster et al. Feb 2008 B2
7346467 Bohrer et al. Mar 2008 B2
D566587 Rosen Apr 2008 S
7379791 Tamarkin et al. May 2008 B2
RE40437 Rosen Jul 2008 E
7418663 Pettinati et al. Aug 2008 B2
7427926 Sinclair et al. Sep 2008 B2
7434742 Mueller et al. Oct 2008 B2
7451937 Flood et al. Nov 2008 B2
7455240 Chapman, Jr. et al. Nov 2008 B2
7460690 Cohen et al. Dec 2008 B2
7469550 Chapman, Jr. et al. Dec 2008 B2
D588152 Okada Mar 2009 S
7509753 Nicosia et al. Mar 2009 B2
D589792 Clabough et al. Apr 2009 S
D590412 Saft et al. Apr 2009 S
D593120 Bouchard et al. May 2009 S
7537171 Mueller et al. May 2009 B2
D594015 Singh et al. Jun 2009 S
D595309 Saski et al. Jun 2009 S
7555364 Poth et al. Jun 2009 B2
D596194 Vu et al. Jul 2009 S
D597101 Chaudhri et al. Jul 2009 S
7558648 Hoglund et al. Jul 2009 B2
D598463 Hirsch et al. Aug 2009 S
7571014 Lambourne et al. Aug 2009 B1
7571865 Nicodem et al. Aug 2009 B2
7575179 Morrow et al. Aug 2009 B2
D599810 Scalisi et al. Sep 2009 S
7584899 de Pauw et al. Sep 2009 B2
7600694 Helt et al. Oct 2009 B2
D603277 Clausen et al. Nov 2009 S
D603421 Ebeling et al. Nov 2009 S
D604740 Matheny et al. Nov 2009 S
7614567 Chapman et al. Nov 2009 B2
7620996 Torres et al. Nov 2009 B2
D607001 Ording Dec 2009 S
7624931 Chapman, Jr. et al. Dec 2009 B2
7634504 Amundson Dec 2009 B2
7641126 Schultz et al. Jan 2010 B2
7644869 Hoglund et al. Jan 2010 B2
7667163 Ashworth et al. Feb 2010 B2
D613301 Lee et al. Apr 2010 S
D614194 Guntaur et al. Apr 2010 S
D614196 Guntaur et al. Apr 2010 S
7693582 Bergman et al. Apr 2010 B2
7702424 Cannon et al. Apr 2010 B2
7703694 Mueller et al. Apr 2010 B2
D614976 Skafdrup et al. May 2010 S
D615546 Lundy et al. May 2010 S
D616460 Pearson et al. May 2010 S
7721209 Tilton May 2010 B2
7726581 Naujok et al. Jun 2010 B2
D619613 Dunn Jul 2010 S
7761189 Froman et al. Jul 2010 B2
7784704 Harter Aug 2010 B2
7802618 Simon et al. Sep 2010 B2
D625325 Vu et al. Oct 2010 S
D625734 Kurozumi et al. Oct 2010 S
D626133 Murphy et al. Oct 2010 S
7823076 Borovsky et al. Oct 2010 B2
RE41922 Gough et al. Nov 2010 E
7845576 Siddaramanna et al. Dec 2010 B2
7848900 Steinberg et al. Dec 2010 B2
7854389 Ahmed Dec 2010 B2
7861179 Reed Dec 2010 B2
D630649 Tokunaga et al. Jan 2011 S
7890195 Bergman et al. Feb 2011 B2
7900849 Barton et al. Mar 2011 B2
7904209 Podgorny et al. Mar 2011 B2
7904830 Hoglund et al. Mar 2011 B2
7908116 Steinberg et al. Mar 2011 B2
7908117 Steinberg et al. Mar 2011 B2
7913925 Ashworth Mar 2011 B2
D638835 Akana et al. May 2011 S
D640269 Chen Jun 2011 S
D640273 Arnold et al. Jun 2011 S
D640278 Woo Jun 2011 S
D640285 Woo Jun 2011 S
D641373 Gardner et al. Jul 2011 S
7984384 Chaudhri et al. Jul 2011 B2
D643045 Woo Aug 2011 S
8010237 Cheung et al. Aug 2011 B2
8019567 Steinberg et al. Sep 2011 B2
8037022 Rahman et al. Oct 2011 B2
D648735 Arnold et al. Nov 2011 S
D651529 Mongell et al. Jan 2012 S
8090477 Steinberg Jan 2012 B1
8091375 Crawford Jan 2012 B2
8091794 Siddaramanna et al. Jan 2012 B2
8131207 Hwang et al. Mar 2012 B2
8131497 Steinberg et al. Mar 2012 B2
8131506 Steinberg et al. Mar 2012 B2
8136052 Shin et al. Mar 2012 B2
D656950 Shallcross et al. Apr 2012 S
D656952 Weir et al. Apr 2012 S
8156060 Borzestowski et al. Apr 2012 B2
8166395 Omi et al. Apr 2012 B2
D658674 Shallcross et al. May 2012 S
D660732 Bould et al. May 2012 S
8174381 Imes et al. May 2012 B2
8180492 Steinberg May 2012 B2
8185164 Kim May 2012 B2
8195313 Fadell et al. Jun 2012 B1
D663743 Tanghe et al. Jul 2012 S
D663744 Tanghe et al. Jul 2012 S
D664559 Ismail et al. Jul 2012 S
8219249 Harrod et al. Jul 2012 B2
8223134 Forstall et al. Jul 2012 B1
8234581 Kake Jul 2012 B2
D664978 Tanghe et al. Aug 2012 S
D665397 Naranjo et al. Aug 2012 S
8243017 Brodersen et al. Aug 2012 B2
8253704 Jang Aug 2012 B2
8253747 Niles et al. Aug 2012 B2
8265798 Imes Sep 2012 B2
8280536 Fadell et al. Oct 2012 B1
8281244 Neuman et al. Oct 2012 B2
8292494 Rosa et al. Oct 2012 B2
D671136 Barnett et al. Nov 2012 S
8316022 Matsuda et al. Nov 2012 B2
D673171 Peters et al. Dec 2012 S
D673172 Peters et al. Dec 2012 S
8341557 Pisula et al. Dec 2012 B2
D677180 Plitkins et al. Mar 2013 S
8406816 Marui et al. Mar 2013 B2
8442695 Imes et al. May 2013 B2
8442752 Wijaya et al. May 2013 B2
8446381 Molard et al. May 2013 B2
8489243 Fadell et al. Jul 2013 B2
8510255 Fadell et al. Aug 2013 B2
8606374 Fadell et al. Dec 2013 B2
8689572 Evans et al. Apr 2014 B2
8706270 Fadell et al. Apr 2014 B2
8918219 Sloo et al. Dec 2014 B2
8950686 Matsuoka et al. Feb 2015 B2
9223323 Matas et al. Dec 2015 B2
9298196 Matsuoka et al. Mar 2016 B2
20010052052 Peng Dec 2001 A1
20020005435 Cottrell Jan 2002 A1
20020022991 Sharood et al. Feb 2002 A1
20030034898 Shamoon et al. Feb 2003 A1
20030042320 Decker Mar 2003 A1
20030112262 Adatia et al. Jun 2003 A1
20030231001 Bruning Dec 2003 A1
20040015504 Ahad et al. Jan 2004 A1
20040034484 Solomita, Jr. et al. Feb 2004 A1
20040055446 Robbin et al. Mar 2004 A1
20040067731 Brinkerhoff et al. Apr 2004 A1
20040074978 Rosen Apr 2004 A1
20040095237 Chen et al. May 2004 A1
20040164238 Xu et al. Aug 2004 A1
20040249479 Shorrock Dec 2004 A1
20040256472 DeLuca Dec 2004 A1
20040260427 Wimsatt Dec 2004 A1
20040262410 Hull Dec 2004 A1
20050040250 Wruck Feb 2005 A1
20050043907 Eckel et al. Feb 2005 A1
20050055432 Rodgers Mar 2005 A1
20050071780 Muller et al. Mar 2005 A1
20050090915 Geiwitz Apr 2005 A1
20050103875 Ashworth et al. May 2005 A1
20050119766 Amundson et al. Jun 2005 A1
20050119771 Amundson Jun 2005 A1
20050119793 Amundson et al. Jun 2005 A1
20050120181 Arunagirinathan et al. Jun 2005 A1
20050128067 Zakrewski Jun 2005 A1
20050144963 Peterson Jul 2005 A1
20050150968 Shearer Jul 2005 A1
20050159847 Shah et al. Jul 2005 A1
20050189429 Breeden Sep 2005 A1
20050192915 Ahmed et al. Sep 2005 A1
20050194456 Tessier et al. Sep 2005 A1
20050195757 Kidder et al. Sep 2005 A1
20050199737 de Pauw et al. Sep 2005 A1
20050204997 Fournier Sep 2005 A1
20050279840 Schwendinger et al. Dec 2005 A1
20050279841 Schwendinger et al. Dec 2005 A1
20050280421 Yomoda et al. Dec 2005 A1
20050287424 Schwendinger et al. Dec 2005 A1
20060000919 Schwendinger et al. Jan 2006 A1
20060184284 Froman et al. Aug 2006 A1
20060186214 Simon et al. Aug 2006 A1
20060196953 Simon et al. Sep 2006 A1
20060206220 Amundson Sep 2006 A1
20060208099 Chapman, Jr. Sep 2006 A1
20070001830 Dagci et al. Jan 2007 A1
20070045430 Chapman et al. Mar 2007 A1
20070045433 Chapman et al. Mar 2007 A1
20070045444 Gray et al. Mar 2007 A1
20070050732 Chapman et al. Mar 2007 A1
20070057079 Stark et al. Mar 2007 A1
20070084941 De Pauw et al. Apr 2007 A1
20070114295 Jenkins May 2007 A1
20070115902 Shamoon et al. May 2007 A1
20070132503 Nordin Jun 2007 A1
20070157639 Harrod Jul 2007 A1
20070158442 Chapman et al. Jul 2007 A1
20070158444 Naujok et al. Jul 2007 A1
20070173978 Fein et al. Jul 2007 A1
20070177857 Troost et al. Aug 2007 A1
20070220907 Ehlers Sep 2007 A1
20070221741 Wagner et al. Sep 2007 A1
20070225867 Moorer et al. Sep 2007 A1
20070227721 Springer et al. Oct 2007 A1
20070228183 Kennedy et al. Oct 2007 A1
20070241203 Wagner et al. Oct 2007 A1
20070246553 Morrow et al. Oct 2007 A1
20070257120 Chapman et al. Nov 2007 A1
20070278320 Lunacek et al. Dec 2007 A1
20070296280 Sorg et al. Dec 2007 A1
20080006709 Ashworth et al. Jan 2008 A1
20080015740 Osann Jan 2008 A1
20080015742 Kulyk et al. Jan 2008 A1
20080048046 Wagner et al. Feb 2008 A1
20080054082 Evans et al. Mar 2008 A1
20080054084 Olson Mar 2008 A1
20080099568 Nicodem et al. May 2008 A1
20080155915 Howe et al. Jul 2008 A1
20080183337 Szabados Jul 2008 A1
20080191045 Harter Aug 2008 A1
20080215240 Howard et al. Sep 2008 A1
20080221737 Josephson et al. Sep 2008 A1
20080245480 Knight et al. Oct 2008 A1
20080256475 Amundson et al. Oct 2008 A1
20080273754 Hick et al. Nov 2008 A1
20080290183 Laberge et al. Nov 2008 A1
20080317292 Baker et al. Dec 2008 A1
20090001180 Siddaramanna et al. Jan 2009 A1
20090001181 Siddaramanna et al. Jan 2009 A1
20090024927 Schrock et al. Jan 2009 A1
20090099699 Steinberg et al. Apr 2009 A1
20090125151 Steinberg et al. May 2009 A1
20090127078 Hostmann et al. May 2009 A1
20090140056 Leen Jun 2009 A1
20090140057 Leen Jun 2009 A1
20090140060 Stoner et al. Jun 2009 A1
20090140062 Amundson et al. Jun 2009 A1
20090140064 Schultz et al. Jun 2009 A1
20090143916 Boll et al. Jun 2009 A1
20090143918 Amundson et al. Jun 2009 A1
20090158188 Bray et al. Jun 2009 A1
20090171862 Harrod et al. Jul 2009 A1
20090194601 Flohr Aug 2009 A1
20090195349 Frader-Thompson et al. Aug 2009 A1
20090215534 Wilson et al. Aug 2009 A1
20090254225 Boucher et al. Oct 2009 A1
20090259713 Blumrich et al. Oct 2009 A1
20090261174 Butler et al. Oct 2009 A1
20090263773 Kotlyar et al. Oct 2009 A1
20090273610 Busch et al. Nov 2009 A1
20090283603 Peterson et al. Nov 2009 A1
20090297901 Kilian et al. Dec 2009 A1
20090327354 Resnick et al. Dec 2009 A1
20100000417 Tetreault et al. Jan 2010 A1
20100019051 Rosen Jan 2010 A1
20100025483 Hoeynck et al. Feb 2010 A1
20100050004 Hamilton, II et al. Feb 2010 A1
20100053464 Otsuka Mar 2010 A1
20100070084 Steinberg et al. Mar 2010 A1
20100070085 Harrod et al. Mar 2010 A1
20100070086 Harrod et al. Mar 2010 A1
20100070089 Harrod et al. Mar 2010 A1
20100070093 Harrod et al. Mar 2010 A1
20100070234 Steinberg et al. Mar 2010 A1
20100070907 Harrod et al. Mar 2010 A1
20100076605 Harrod et al. Mar 2010 A1
20100076835 Silverman Mar 2010 A1
20100084482 Kennedy et al. Apr 2010 A1
20100106305 Pavlak et al. Apr 2010 A1
20100106322 Grohman Apr 2010 A1
20100107070 Devineni et al. Apr 2010 A1
20100107076 Grohman et al. Apr 2010 A1
20100107103 Wallaert et al. Apr 2010 A1
20100131112 Amundson May 2010 A1
20100163633 Barrett et al. Jul 2010 A1
20100167783 Alameh et al. Jul 2010 A1
20100168924 Tessier et al. Jul 2010 A1
20100179704 Ozog Jul 2010 A1
20100198425 Donovan Aug 2010 A1
20100211224 Keeling et al. Aug 2010 A1
20100262298 Johnson et al. Oct 2010 A1
20100262299 Cheung et al. Oct 2010 A1
20100280667 Steinberg Nov 2010 A1
20100282857 Steinberg Nov 2010 A1
20100289643 Trundle et al. Nov 2010 A1
20100308119 Steinberg et al. Dec 2010 A1
20100318227 Steinberg Dec 2010 A1
20110001812 Kang et al. Jan 2011 A1
20110015797 Gilstrap Jan 2011 A1
20110015798 Golden et al. Jan 2011 A1
20110015802 Imes Jan 2011 A1
20110016017 Carlin et al. Jan 2011 A1
20110022242 Bukhin et al. Jan 2011 A1
20110029488 Fuerst et al. Feb 2011 A1
20110046756 Park Feb 2011 A1
20110046792 Imes et al. Feb 2011 A1
20110046805 Bedros et al. Feb 2011 A1
20110046806 Nagel et al. Feb 2011 A1
20110054710 Imes et al. Mar 2011 A1
20110077758 Tran et al. Mar 2011 A1
20110077896 Steinberg et al. Mar 2011 A1
20110082594 Dage et al. Apr 2011 A1
20110106328 Zhou et al. May 2011 A1
20110151837 Winbush, III Jun 2011 A1
20110160913 Parker et al. Jun 2011 A1
20110166828 Steinberg et al. Jul 2011 A1
20110167369 van Os Jul 2011 A1
20110181412 Alexander Jul 2011 A1
20110185895 Freen Aug 2011 A1
20110202193 Craig Aug 2011 A1
20110282937 Deshpande et al. Nov 2011 A1
20110290893 Steinberg Dec 2011 A1
20110307103 Cheung et al. Dec 2011 A1
20110307112 Barrilleaux Dec 2011 A1
20120017611 Coffel et al. Jan 2012 A1
20120036250 Vaswani et al. Feb 2012 A1
20120053745 Ng Mar 2012 A1
20120065783 Fadell Mar 2012 A1
20120065935 Steinberg et al. Mar 2012 A1
20120066168 Fadell et al. Mar 2012 A1
20120085831 Kopp Apr 2012 A1
20120086562 Steinberg Apr 2012 A1
20120089523 Hurri et al. Apr 2012 A1
20120101637 Imes et al. Apr 2012 A1
20120125559 Fadell et al. May 2012 A1
20120125592 Fadell et al. May 2012 A1
20120126019 Warren et al. May 2012 A1
20120126020 Filson et al. May 2012 A1
20120126021 Warren et al. May 2012 A1
20120128025 Huppi et al. May 2012 A1
20120130546 Matas et al. May 2012 A1
20120130547 Fadell et al. May 2012 A1
20120130548 Fadell et al. May 2012 A1
20120130679 Fadell et al. May 2012 A1
20120131504 Fadell et al. May 2012 A1
20120158350 Steinberg et al. Jun 2012 A1
20120179300 Warren et al. Jul 2012 A1
20120186774 Matsuoka et al. Jul 2012 A1
20120191257 Corcoran et al. Jul 2012 A1
20120022151 Steinberg Aug 2012 A1
20120199660 Warren et al. Aug 2012 A1
20120203379 Sloo et al. Aug 2012 A1
20120229521 Hales, IV et al. Sep 2012 A1
20120233478 Mucignat et al. Sep 2012 A1
20120239207 Fadell et al. Sep 2012 A1
20120239221 Mighdoll et al. Sep 2012 A1
20120252430 Imes et al. Oct 2012 A1
20120296488 Dharwada et al. Nov 2012 A1
20130024799 Fadell et al. Jan 2013 A1
20130046397 Fadell et al. Feb 2013 A1
20130090767 Bruck et al. Apr 2013 A1
20130099011 Matsuoka et al. Apr 2013 A1
20130014057 Reinpoldt et al. Oct 2013 A1
20140005837 Fadell et al. Jan 2014 A1
Foreign Referenced Citations (59)
Number Date Country
2202008 Feb 2000 CA
106440187 Feb 2017 CN
3217068 Oct 1983 DE
19609390 Sep 1997 DE
207295 Jan 1987 EP
0444308 Apr 1991 EP
434926 Jul 1991 EP
196069 Dec 1991 EP
720077 Jul 1996 EP
802471 Aug 1999 EP
1065079 Jan 2001 EP
1184804 Mar 2002 EP
1731984 Dec 2006 EP
1283396 Mar 2007 EP
2157492 Feb 2010 EP
1703356 Sep 2011 EP
2212317 May 1992 GB
S50-119898 Sep 1975 JP
59106311 Jun 1984 JP
01252850 Oct 1989 JP
09298780 Nov 1997 JP
10023565 Jan 1998 JP
2000257939 Sep 2000 JP
2002087050 Mar 2002 JP
2003-021380 Jan 2003 JP
2003-54290 Feb 2003 JP
2003054290 Feb 2003 JP
2005049062 Feb 2005 JP
2006-501965 Jan 2006 JP
2006-205752 Aug 2006 JP
2007020908 Feb 2007 JP
2007-64555 Mar 2007 JP
2007-165246 Jun 2007 JP
2008-286445 Nov 2008 JP
2008-544447 Dec 2008 JP
2009302004 Dec 2009 JP
2010278539 Dec 2010 JP
2011-038718 Feb 2011 JP
1020070117874 Dec 2007 KR
1024986 Jun 2005 NL
0248851 Jun 2002 WO
2003017304 Feb 2003 WO
2005019740 Mar 2005 WO
2008054938 May 2008 WO
2009073496 Jun 2009 WO
2010033563 Mar 2010 WO
2011128416 Oct 2011 WO
2011149600 Dec 2011 WO
2012024534 Feb 2012 WO
2012068436 May 2012 WO
2012068437 May 2012 WO
2012068453 May 2012 WO
2012068459 May 2012 WO
2012068495 May 2012 WO
2012068503 May 2012 WO
2012068507 May 2012 WO
2012068447 Jan 2013 WO
2013052389 Apr 2013 WO
2013059671 Apr 2013 WO
Non-Patent Literature Citations (108)
Entry
JP Patent Application No. 2014-537314 filed Oct. 19, 2012, Final Office Action dated Mar. 7, 2017, all pages.
Notice of Grounds of Rejection for Japanese Patent Application No. 2014-537314 dated Jul. 5, 2016, 11 pages. English Translation.
Extended European Search Report dated Mar. 7, 2016, for European Application No. 12841459.6, 8 pages.
Chinese Office Action dated Mar. 3, 2016, for Chinese Application No. 201280051345.9, 6 pages, English Translation.
Notice of Publication dated Feb. 25, 2016, for U.S. Appl. No. 14/933,947, 1 page.
Preliminary Report of Issuance of a New Office Action dated Aug. 7, 2018 in related Japanese Patent Application No. 2014-537314, all pages.
Office action dated Aug. 28, 2018 in related Canadian Patent Application No. 2,852,944, all pages.
Office action dated Sep. 5, 2018 in related Chinese Patent Application No. 201610807014.3, all pages.
Notice of Decision to Grant dated Nov. 27, 2018 in Japanese Patent Application No. 2014-537314, all pages.
Aprilaire Electronic Thermostats Model 8355 User's Manual, Research Products Corporation, 2000, 16 pages.
Braeburn 5300 Installer Guide, Braeburn Systems, LLC, 2009, 10 pages.
Braeburn Model 5200, Braeburn Systems, LLC, 2011, 11 pages.
Ecobee Smart Si Thermostat Installation Manual, Ecobee, 2012, 40 pages.
Ecobee Smart Si Thermostat User Manual, Ecobee, 2012, 44 pages.
Ecobee Smart Thermostat Installation Manual, 2011, 20 pages.
Ecobee Smart Thermostat User Manual, 2010, 20 pages.
Electric Heat Lock Out on Heat Pumps, Washington State University Extension Energy Program, Apr. 2010, pp. 1-3.
Energy Joule, Ambient Devices, 2011, [retrieved on Aug. 1, 2012], Retrieved from: http://web.archive.org/web/20110723210421/http://www.ambientdevices.com/products/energyjoule.html, 3 pages.
Honeywell CT2700, An Electronic Round Programmable Thermostat—User's Guide, Honeywell, Inc., 1997, 8 pages.
Honeywell CT8775A,C, The digital Round Non-Programmable Thermostats—Owner's Guide, Honeywell International Inc., 2003, 20 pages.
Honeywell Installation Guide FocusPRO TH6000 Series, Honeywell International, Inc., 2012, 24 pages.
Honeywell Operating Manual FocusPRO TH6000 Series, Honeywell International, Inc., 2011, 80 pages.
Honeywell Prestige IAQ Product Data 2, Honeywell International, Inc., 2012, 126 pages.
Honeywell Prestige THX9321 and TXH9421 Product Data, Honeywell International, Inc., 68-0311, No Date Given, 126 pages.
Honeywell Prestige THX9321-9421 Operating Manual, Honeywell International, Inc., 2011, 120 pages.
Honeywell T8700C, An Electronic Round Programmable Thermostat—Owner's Guide, Honeywell, Inc., 1997, 12 pages.
Honeywell T8775 The Digital Round Thermostat, Honeywell, 2003, 2 pages.
Honeywell T8775AC Digital Round Thermostat Manual No. 69-1679EF-1, www.honeywell.com/yourhome, Jun. 2004, pp. 1-16.
Hunter Internet Thermostat Installation Guide, Hunter Fan Co., 2012, 8 pages.
ICY 3815TT-001 Timer-Thermostat Package Box, ICY BV Product Bar Code No. 8717953007902, 2009, 2 pages.
Introducing the New Smart Si Thermostat, Datasheet [online], Ecobee, No Date Given [retrieved on Feb. 25, 2013], Retrieved from the Internet: <URL: https://www.ecobee.com/solutions/home/smart-si/>, all pages.
Lennox ComfortSense 5000 Owner's Guide, Lennox Industries, Inc., 2007, 32 pages.
Lennox ComfortSense 7000 Owner's Guide, Lennox Industries, Inc., 2009, 15 pages.
Lennox iComfort Manual, Lennox Industries, Inc., 2010, 20 pages.
Lux PSPU732T Manual, LUX Products Corporation, No Date Given, 48 pages.
NetX RP32-WIFI Network Thermostat Consumer Brochure, Network Thermostat, No Date Given, 2 pages.
NetX RP32-WIFI Network Thermostat Specification Sheet, Network Thermostat, 2012, 2 pages.
Robertshaw Product Manual 9620, Maple Chase Company, 2001, 14 pages.
Robertshaw Product Manual 9825i2, Maple Chase Company, 2006, 36 pages.
SYSTXCCUIZ01-V Infinity Control Installation Instructions, Carrier Corp, 2012, 20 pages.
T8611G Chronotherm IV Deluxe Programmable Heat Pump Thermostat Product Data, Honeywell International Inc., 1997, 24 pages.
TB-PAC, TB-PHP, Base Series Programmable Thermostats, Carrier Corp, 2012, 8 pages.
The Clever Thermostat, ICY BV Web Page, http://www.icy.nl/en/consumer/products/clever-thermostat, ICY BV, 2012, 1 page.
The Clever Thermostat User Manual and Installation Guide, ICY BV ICY3815 Timer-Thermostat, 2009, pp. 1-36.
The Perfect Climate Comfort Center PC8900A W8900A-C Product Data Sheet, Honeywell International Inc, 2001, 44 pages.
Trane Communicating Thermostats for Fan Coil, Trane, 2011, 32 pages.
Trane Communicating Thermostats for Heat Pump Control, Trane, 2011, 32 pages.
Trane Install XL600 Installation Manual, Trane, 2006, 16 pages.
Trane XL950 Installation Guide, Trane, 2011, 20 pages.
Venstar T2900 Manual, Venstar, Inc., 2008, 113 pages.
Venstar T5800 Manual, Venstar, Inc., No Date Given, 63 pages.
VisionPRO TH8000 Series Installation Guide, Honeywell International, Inc., 2012, 12 pages.
VisionPRO TH8000 Series Operating Manual, Honeywell International, Inc., 2012, 96 pages.
VisionPRO Wi-Fi Programmable Thermostat, Honeywell International, Inc Operating Manual, 2012, 48 pages.
White Rodgers (Emerson) Model 1F81-261 Installation and Operating Instructions, White Rodgers, No Date Given, 63 pages.
White Rodgers (Emerson) Model IF98EZ-1621 Homeowner's User Guide, White Rodgers, No Date Given, 28 pages.
U.S. Appl. No. 60/512,886, Volkswagen Rotary Knob For Motor Vehicle—English Translation of German Application filed Oct. 20, 2003, all pages.
Allen et al., “Real-Time Earthquake Detection and Hazard Assessment by ElarmS Across California”, Geophysical Research Letters, vol. 36, L00B08, 2009, pp. 1-6.
Arens et al., “Demand Response Electrical Appliance Manager—User Interface Design, Development and Testing”, Poster, Demand Response Enabling Technology Development, University of California Berkeley, Retrieved from dr.berkeley.edu/dream/posters/2005_6GUIposter.pdf, 2005, 1 page.
Arens et al., “Demand Response Enabled Thermostat—Control Strategies and Interface”, Demand Response Enabling Technology Development Poster, University of California Berkeley, Retrieved from dr.berkeley.edu/dream/posters/2004_11CEC_TstatPoster.pdf, 2004, 1 page.
Arens et al., “Demand Response Enabling Technology Development”, Phase I Report: June 2003-Nov. 2005, Jul. 27, P:/DemandRes/UC Papers/DR-Phase1Report-Final DraftApril24-26.doc, University of California Berkeley, pp. 1-108.
Arens et al., “New Thermostat Demand Response Enabling Technology”, Poster, University of California Berkeley, Jun. 10, 2004.
Auslander et al., “UC Berkeley DR Research Energy Management Group”, Power Point Presentation, DR ETD Workshop, State of California Energy Commission, Jun. 11, 2007, pp. 1-35.
Chen et al., “Demand Response-Enabled Residential Thermostat Controls”, Abstract, ACEEE Summer Study on Energy Efficiency in Buildings, Mechanical Engineering Dept. and Architecture Dept., University of California Berkeley, 2008, pp. 1-24 through 1-36.
Deleeuw, “Ecobee WiFi Enabled Smart Thermostat Part 2: The Features Review”, Retrieved from <URL: http://www.homenetworkenabled.com/content.php?136-ecobee-WiFi-enabled-Smart-Thermostat-Part-2-The-Features-review>, Dec. 2, 2011, 5 pages.
Gao et al., “The Self-Programming Thermostat: Optimizing Setback Schedules Based on Home Occupancy Patterns”, In Proceedings of the First ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings, Novembers, 2009, 6 pages.
Green, “Thermo Heat Tech Cool”, Popular Mechanics Electronic Thermostat Guide, Oct. 1985, pp. 155-158.
Loisos et al., “Buildings End-Use Energy Efficiency: Alternatives to Compressor Cooling”, California Energy Commision, Public Interest Energy Research, Jan. 2000, 80 pages.
Lu et al., “The Smart Thermostat: Using Occupancy Sensors to Save Energy in Homes”, In Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems, Nov. 3-5, 2010, pp. 211-224.
Meier et al., “Thermostat Interface Usability: A Survey”, Ernest Orlando Lawrence Berkeley National Laboratory, Environmental Energy Technologies Division, Berkeley California, Sep. 2010, pp. 1-73.
Mozer, “The Neural Network House: An Environmental that Adapts to it's Inhabitants”, AAAI Technical Report SS-98-02, 1998, pp. 110-114.
Peffer et al., “A Tale of Two Houses: The Human Dimension of Demand Response Enabling Technology from a Case Study of Adaptive Wireless Thermostat”, Abstract, ACEEE Summer Study on Energy Efficiency in Buildings, Architecture Dept. and Mechanical Engineering Dept., University of California Berkeley., 2008, pp. 7-242 through 7-253.
Peffer et al., “Smart Comfort at Home: Design of a Residential Thermostat to Achieve Thermal Comfort, and Save Money and Peak Energy”, University of California Berkeley, Mar. 2007, 1 page.
Salus, “S-Series Digital Thermostat Instruction Manual-ST620 Model No. Instruction Manual”, www.salus-tech.com, Version 005, Apr. 29, 2010, 24 pages.
Sanford, “iPod (Click Wheel) (2004)”, www.apple-history.com [retrieved on Apr. 9, 2012], Retrieved from: http://apple-history.com/ipod, Apr. 9, 2012, 2 pages.
Wright et al., “DR ETD—Summary of New Thermostat, TempNode, & New Meter (UC Berkeley Project)”, Power Point Presentation, Public Interest Energy Research, University of California Berkeley. Retrieved from: http://dr.berkeley.edu/dream/presentations/2005_6CEC.pdf, 2005, pp. 1-49.
International Search Report and Written Opinion dated Jan. 23, 2013 in PCT Application No. PCT/US2012/061133, all pages.
International Preliminary Report on Patentability dated Apr. 22, 2014 for International Patent Application PCT/US2012/061133 filed Oct. 19, 2012, 14 pages.
ICY3815TT-001 Timer-Thermostat Package Box, Product Bar Code No. 8717953007902, 2009, 2 pages.
“Advanced Model Owner's Manual”, Bay Web Thermostat, manual [online], [retrieved on Nov. 7, 2012], Retrieved from the Internet: <URL:http://www.bayweb.com/wp-content/uploads/BW-WT4-2DOC.pdf>, Oct. 6, 2011, 31 pages.
“Ambient Devices Energy Joule Web Page”, http://www.ambientdevices.com/products/energyjoule.html, Cambridge Massachusetts, Ambient Devices , 2011, 2 pages.
“SCE Energy$mart Thermostat Study for Southern California Edison—Presentation of Study Results”, Population Research Systems, Project #1010, Nov. 10, 2004, 51 pages.
Bourke, “Server Load Balancing”, O'Reilly & Associates, Inc., Aug. 2001, 182 pages.
De Almeida et al., “Advanced Monitoring Technologies for the Evaluatioin of Demand-Side Management Programs”, Energy, vol. 19, No. 6, 1994, pp. 661-678.
Gevorkian, “Alternative Energy Systems in Building Design”, 2009, pp. 195-200.
Hoffman et al., “Integration of Remote Meter Reading, Load Control and Monitoring of Customers' Installations for Customer Automation with Telephone Line Signalling”, Electricity Distribution, 1989. CIRED 1989. 10th International Conference on, May 8-12, 1989, pp. 421-424.
Levy, “A Vision of Demand Response—2016”, The Electricity Journal, vol. 19, Issue 8, Oct. 2006, pp. 12-23.
Lopes, “Case Studies in Advanced Thermostat Control for Demand Response”, AEIC Load Research Conference, St. Louis, MO, Jul. 2004, 36 pages.
Martinez, “SCE Energy$mart Thermostat Program”, Advanced Load Control Alliance, Oct. 5, 2004, 20 pages.
Matty, “Advanced Energy Management for Home Use”, IEEE Transaction on Consumer Electronics, vol. 35, No. 3, Aug. 1989, pp. 584-588.
Motegi et al., “Introduction to Commercial Building Control Strategies and Techniques for Demand Response”, Demand Response Research Center, May 22, 2007, 35 pages.
White et al., “A Conceptual Model for Simulation Load Balancing”, Proc. 1998 Spring Simulation Interoperability Workshop, 1998, 7 pages.
International Patent Application No. PCT/US2012/030084, International Search Report & Written Opinion, dated Jul. 6, 2012, 7 pages.
International Preliminary Report on Patentability dated Apr. 8, 2014 for International Patent Application No. PCT/US2012/058207 filed Sep. 30, 2012, 8 pages.
Detroitborg, “Nest Learning Thermostat: Unboxing and Review”, [online], Feb. 2012 [retrieved on Aug. 22, 2013], Retrieved from the Internet: <URL: http://www.youtube.com/watch?v=KrgcOL4oLzc>, all pages.
International Patent Application No. PCT/US2011/061470, International Search Report & Written Opinion, dated Apr. 3, 2012, 11 pages.
International Patent Application No. PCT/US2012/058207, International Search Report & Written Opinion, dated Jan. 11, 2013, 10 pages.
TP-PAC, TP-PHP, TP-NAC, TP-NHP Performance Series AC/HP Thermostat Installation Instructions, Carrier Corp, Sep. 2007, 56 pages.
Chinese Office Action dated Mar. 2, 2015 for Chinese Patent Application No. 201280051345.9 filed Oct. 19, 2012, all pages.
Chinese Office Action dated Oct. 12, 2015 for Chinese Patent Application No. 201280051345.9 filed Oct. 19, 2012, all pages.
Notice of Publication dated Jul. 2, 2014 in Chinese Patent Application No. 201280051345.9, 1 page.
Notice of Decision to Grant dated Jun. 22, 2016 in Chinese Patent Application No. 201280051345.9, all pages.
Notice of European Publication No. dated Jul. 30, 2014 in European Patent Application No. 12841459.6, 1 page.
Notice of Decision to Grant dated Nov. 29, 2018 in European Patent Application No. 12841459.6, 1 page.
Office action dated Jul. 5, 2016 in Japanese Patent Application No. 2014-537314, all pages.
Office action dated Aug. 22, 2017 in Japanese Patent Application No. 2014-537314, all pages.
Office action dated Aug. 7, 2018 in Japanese Patent Application No. 2014-537314, all pages.
Notice of Publication dated Mar. 1, 2017 in Chinese Patent Application No. 201610807014.3, all pages.
Related Publications (1)
Number Date Country
20160169547 A1 Jun 2016 US
Provisional Applications (3)
Number Date Country
61550345 Oct 2011 US
61429093 Dec 2010 US
61415771 Nov 2010 US
Continuations (1)
Number Date Country
Parent 13656200 Oct 2012 US
Child 15049921 US
Continuation in Parts (2)
Number Date Country
Parent 13269501 Oct 2011 US
Child 13656200 US
Parent 13033573 Feb 2011 US
Child 13269501 US