UNITED STATES PATENT AND TRADEMARK OFFICE
`__________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`__________
`
`ECOBEE TECHNOLOGIES ULC
`Petitioner
`v.
`ECOFACTOR, INC.
`Patent Owner
`__________
`
`Case No. IPR2022-00983
`Patent No. 8,596,550
`__________
`
`REPLY TO PATENT OWNER RESPONSE
`
`
`
`
`
`
`__________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`__________
`
`ECOBEE TECHNOLOGIES ULC
`Petitioner
`v.
`ECOFACTOR, INC.
`Patent Owner
`__________
`
`Case No. IPR2022-00983
`Patent No. 8,596,550
`__________
`
`REPLY TO PATENT OWNER RESPONSE
`
`
`
`
`
`
`
`TABLE OF CONTENTS
`
`3.
`
`4.
`
`Page
`Exhibit List ................................................................................................................ ii
`I.
`Introduction ...................................................................................................... 1
`II.
`Level of Ordinary Skill .................................................................................... 2
`III. Argument ......................................................................................................... 3
`A.
`Combination of Ehlers and Wruck ........................................................ 3
`1.
`Thermal Gain .............................................................................. 3
`2.
`Claim Elements [1c] and [9c] - Predict a Rate of
`Change of Temperatures Inside the Structure in
`Response to Changes in Outside Temperatures ........................ 12
`Claim Elements [1d] and [9d] - Calculating
`Scheduled Programming Based on the Predicted
`Rate of Change, the Scheduled Programming
`Comprising at Least a First Automated Setpoint at
`a First Time ............................................................................... 13
`Claim Elements [1e] - Generating a Difference
`Value Based on Comparing an Actual Setpoint to
`the First Automated Setpoint and Detecting a
`Manual Change to the First Automated Setpoint
`Based on the Difference Value – and [9e] –
`Comparing the Actual Setpoint to the First
`Automated Setpoint and Detecting a Manual
`Change to the First Automated Setpoint by
`Determining Whether the Actual Setpoint and First
`Automated Setpoint are the Same or Different ......................... 16
`5. Wruck ........................................................................................ 17
`Combination of Ehlers, Wruck and Harter ......................................... 19
`B.
`IV. Secondary Considerations ............................................................................. 20
`
`
`
`
`
`
`
`i
`
`
`
`Exhibit List
`
`Exhibit No.
`
`Description
`
`1001
`
`1002
`
`1003
`
`1004
`
`1005
`
`1006
`
`1007
`
`1008
`
`1009
`
`1010
`
`1011
`
`1012
`
`1013
`
`1014
`
`1015
`
`U.S. Patent No. 8,596,550 (“the ’550 patent”).
`
`Declaration of David M. Auslander.
`
`C.V. of David M. Auslander.
`
`U.S. Patent App. Pub. 2004/0117330 (“Ehlers ’330”).
`
`U.S. Patent App. Pub. 2005/0040250 A1 (“Wruck”).
`
`Exhibit number not used.
`
`Exhibit number not used.
`
`File History of Application No. 12/778,052.
`
`U.S. Patent App. Pub. 2005/0171645 (“Oswald”).
`
`U.S. Patent No. 5,934,554 (“Charles”).
`
`U.S. Patent No. 6,029,092 (“Stein”).
`
`ITC Inv. No. 337-TA-1258, Order No. 18, Construing the
`Terms of the Asserted Claims of the Patents at Issue (Sept.
`1, 2021).
`
`ecobee, Inc. v. EcoFactor, Inc., 1-21-cv-00323 (D. Del.),
`Answer (May 5, 2021).
`
`ecobee, Inc. v. EcoFactor, Inc., 1-21-cv-00323 (D. Del.),
`Scheduling Order (October 14, 2021).
`
`Horan, T, Control Systems and Applications for
`HVAC/R, Prentice-Hall, Inc., 1997.
`
`ii
`
`
`
`
`
`
`
`1016
`
`1017
`
`1018
`
`1019
`
`1020
`
`1021
`
`1022
`
`1023
`
`Levenhagen, J, HVAC Control and Systems, McGraw-Hill,
`Inc., 1993.
`
`U.S. Patent No. 8,751,186 B2 (“the ’186 patent”).
`
`Excerpt from McDaniel, G, IBM Dictionary of Computing,
`McGraw-Hill, Inc., 1993, p. 165.
`
`U.S. Patent No. 7,784,704 (“Harter”).
`
`Excerpt from Dictionary of Scientific and Technical Terms,
`5th ed., McGraw-Hill, Inc., 1994, p. 62.
`
`Excerpt from The Industrial Electronics Handbook, Irwin,
`J.D. ed. CRC Press and IEEE Press, 1997, pp. 59-60.
`
`Deposition transcript of John A. Palmer, Ph.D., April 11,
`2023.
`
`Reply Declaration of David M. Auslander.
`
`
`
`
`
`
`iii
`
`
`
`I.
`
`Introduction
`In an attempt to rebut clear unpatentability, EcoFactor offers fanciful
`
`arguments that contradict the record. For example, with respect to the claimed use
`
`of data “to predict a rate of change of temperatures inside the structure in response
`
`to changes in outside temperatures,” as recited in independent claims 1 and 9,
`
`Ehlers’s Fig. 3D shows the tracking of changes in inside temperatures over time in
`
`response to different outside temperatures. While not disputing this fact, EcoFactor
`
`argues that the terminology Ehlers’ uses to describe what is shown—“thermal
`
`gain”—should be understood to mean something different than what is depicted.
`
`EcoFactor then asks the Board to ignore what is actually shown due to the disputed
`
`terminology. Remarkably, EcoFactor’s expert believes the terminology in the ’550
`
`patent—“thermal mass”—is also wrong, but urges reliance on context to solve the
`
`issue, despite refusing to do so for Ehlers. Such contradictory positions are
`
`untenable.
`
`Also, while Ehlers describes the calculation of a new setpoint that is “offset”
`
`from what a user sets, EcoFactor disputes that the calculated setpoint is
`
`“automated,” as claimed. Specifically, Ehlers’ system may operate within
`
`boundaries limiting how far from the original setpoint the automatically calculated
`
`setpoint may deviate. Due to the boundaries, EcoFactor concludes the new setpoint
`
`cannot count as automated. That position is illogical and EcoFactor’s own expert
`
`
`
`1
`
`
`
`agrees that Ehlers’ system calculates the new setpoint “without the user needing to
`
`do anything else.” Ex. 1022, 68:7-22.
`
`II. Level of Ordinary Skill
`EcoFactor offers a different definition of a POSITA, relative to the Petition,
`
`based on a related ITC proceeding. POR, 5-7. However, that different level for the
`
`POSITA does not affect the outcome. Specifically, EcoFactor alleges that the field
`
`proposed by ecobee—building energy management systems—is “complex” and
`
`that, in “contrast, the subject matter of the ’550 patent is focused on residential and
`
`similar smaller-scale structures that do not require the sophistication” of ecobee’s
`
`stated field. Id., 7. EcoFactor’s proposal also assumes fewer years of experience
`
`(2-3 years as opposed to 5 years). Thus, EcoFactor proposes fewer years of
`
`experience in a less complex field. Ex. 2006, ¶¶26-28; Ex. 1022, 14:14-16:7 (“less
`
`complicated to understand, for sure, and arguably, less complicated to design as
`
`well”).
`
`Dr. Auslander confirms that his opinions do not change under either
`
`definition. Ex. 1023, ¶¶6-7. Indeed, assuming less experience while simultaneously
`
`acknowledging a system “less complicated to understand” balances out. Id., ¶6.
`
`
`
`2
`
`
`
`III.
` Argument
`A. Combination of Ehlers and Wruck
`1.
`Thermal Gain
`Ehlers1 describes determining the “rate of thermal gain.” Ex. 1004, Fig. 3E,
`
`¶[0253]. EcoFactor argues that “[t]hermal gain is the addition of thermal heat, not
`
`the increase of an inside temperature.” POR, 1, 12. However, that assertion directly
`
`contradicts Ehlers and leads to a result that EcoFactor’s expert agrees would be
`
`nonsensical. Ex. 1023, ¶10; Ex. 1022, 107:16-108:7.
`
`For context, Ehlers uses “thermal gain” where the ’550 patent uses “thermal
`
`mass.” Ex. 1001, 5:26-29; Ex. 1004, ¶[0253]. While these terms were not used
`
`uniformly in the art Ehlers uses its term to refer to the rise in internal temperature
`
`due to, e.g., outside temperature. Ex. 1023, ¶¶10, 16. While EcoFactor’s expert—
`
`Dr. Palmer—initially testified that “thermal mass” refers to “the speed with which
`
`the temperature inside the structure will change in response to changes in outside
`
`temperatures” (Ex. 1022, 27:19-28:15, 115:1-13), he ultimately conceded that
`
`“thermal mass,” as used in the field, actually refers to “an amount of energy that …
`
`a structure or system would absorb to result in a … particular change in
`
`
`1 EcoFactor states that another Ehlers patent document with the same disclosure is
`of record in the ’550 patent. POR, 12-13. EcoFactor does not dispute that the
`examiner did not address that other Ehlers document. Id. Both experts agree that
`the document being of record does not change what a POSITA would understand
`from Ehlers. Ex. 1022, 14:3-13; Ex. 1023, ¶8 n.1.
`3
`
`
`
`
`
`temperature.” Ex. 1022, 35:7-37:5 (“it’s not time based”; “could be BTUs per
`
`degree Fahrenheit”). Thus, Dr. Palmer’s position is that the ’550 patent is using
`
`“thermal mass” differently from the conventional meaning, but that the
`
`specification suggests a rate of change in inside temperatures. Id., 27:19-29:10; Ex.
`
`1023, ¶¶8-9.
`
`Ehlers uses “rate of thermal gain” to refer to the rate of change in the inside
`
`temperature in response to outside temperatures—namely, degrees F. per hour. Ex.
`
`1023, ¶10; Ex. 1004, ¶[0255] (“the rate of thermal gain per hour would be set at 3
`
`degrees F. per hour”). Even Dr. Palmer could not dispute that Ehlers’ language
`
`describes a rate of inside temperature change. Ex. 1022, 50:2-53:11. Ehlers also
`
`makes clear that the measured increase of inside temperature is in response to
`
`different outside temperatures. Ex. 1004, ¶¶[0253]-[0255]; Ex. 1023, ¶10. Thus, as
`
`used in Ehlers, the rate of thermal gain refers to the rate of increase in temperature
`
`within a structure as a result of outside influences.
`
`Ultimately, regardless of differences in terminology, a POSITA would
`
`understand that Elhers describes a rate of change of inside temperatures in
`
`response to changes in outside temperatures. Ex. 1004, ¶¶[0253]-[0255]; Ex. 1023,
`
`¶10.
`
`
`
`4
`
`
`
`a.
`Ehlers’ Fig. 3D
`EcoFactor argues, implausibly, that Fig. 3D of Ehlers should not be
`
`understood to refer to a rate of change of inside temperatures in response to
`
`changes in outside temperatures based on the mention of “thermal gain.” POR, 12-
`
`14. In addition to reasons stated above, the argument fails based on a simple
`
`review of the figure, which plots inside temperatures over time in response to
`
`different outside temperatures.
`
`
`
`Ex. 1004, Fig. 3D.
`
`Trend lines 3.12A-C all have a starting internal temperature of 72° F., but
`
`differ in outside temperatures (99, 90, and 77° F., respectively). Ex. 1004, ¶[0253].
`
`Trend lines 3.14A-C correspond to the same respective outside temperatures, but
`
`all start from an internal setting of 76° F. Id. The X-axis is time. Thus, the trend
`
`
`
`5
`
`
`
`lines show inside temperature increases over time in response to different outdoor
`
`temperatures. Ex. 1023, ¶11. Oddly, EcoFactor argues that “[t]he lines appear to
`
`reflect temperatures rather than rates of energy increase, and no axis or label
`
`quantifies the ‘thermal gain.’” POR, 13. In other words, EcoFactor (i) argues that
`
`its definition of “thermal gain” is not depicted in Fig. 3D and (ii) admits that Fig.
`
`3D actually plots temperatures over time (i.e., a rate of change of internal
`
`temperatures). Yet, EcoFactor insists that “thermal gain” must be understood to be
`
`energy absorption (not shown) and not inside temperature change (which is
`
`shown). Such strained logic exposes the weakness of EcoFactor’s position.
`
`For context, Ehlers’s system collects interval data. Ex. 1004, ¶[0084]
`
`(“records actual interval data … for each device”). The interval data (e.g., from
`
`inside and outside temperature sensors) is tracked for learning purposes related to
`
`making future adjustments. Id., ¶¶[0253]-[0254] (“to learn the operational run
`
`characteristics of the HVAC system as a function of the thermal gain. Since the
`
`outside temperature varies continuously during a typical day, the rate of thermal
`
`gain and the HVAC run times also vary in accordance with these changes”),
`
`[0230]-[0231], [0239]; Ex. 1023, ¶12; Ex. 1022, 33:5-10.
`
`Ehlers’s Fig. 3D depicts how the system “tracks and learns about the thermal
`
`gain characteristics of the home 2.18” by “track[ing] the thermal gain rate of the
`
`home 2.18 for each set point selected over time by the customer.” Ex. 1004,
`
`
`
`6
`
`
`
`¶[0253]. Specifically, Fig. 3D shows the tracking of inside temperatures as they
`
`approach warmer outside temperatures, when the system cycles off from given
`
`setpoints (i.e., from a particular setpoint, the system switches off and the inside
`
`temperature begins to rise). Ex. 1023, ¶13; Ex. 1004, ¶[0256] (“uses the learned
`
`thermal gain characteristics”). While Fig. 3D’s Y-axis refers to the “INDOOR
`
`SETPOINT,” a POSITA would understand the same is referring to the setpoint at
`
`the start of the measurement. Ex. 1023, ¶14. This is because when an HVAC is
`
`running normally, the temperature stays constant, as Dr. Palmer acknowledges. Ex.
`
`1022, 20:2-22:22, 23:19-22, 25:12-21, 107:16-109:18; Ex. 1004, ¶¶ [0253] (“as the
`
`indoor temperature reaches the outside temperature”), [0255] (“3 degrees F. per
`
`hour”). When the HVAC is off (either because the HVAC is turned off completely
`
`or cycles off during normal operation) the indoor temperature begins to approach
`
`the outdoor temperature.
`
`The use of straight trend lines indicates a simplified, average rate, inasmuch
`
`as, when HVAC first cycles off, the rate of change is high but then plateaus. Ex.
`
`1023, ¶15; Ex. 1004, ¶[0253] (see trend line 3.16; “rapid initial gain when the
`
`differential is large”).
`
`Even Dr. Palmer acknowledged that this a reasonable interpretation of Fig.
`
`3D. Ex. 1022, 54:9-59:15, 73:7-21, 87:15-88:14, 90:22-92:21. Thus, Fig. 3D shows
`
`the tracking of internal temperatures in response to different (i.e., changes in)
`
`
`
`7
`
`
`
`outside temperatures, in order to learn from the data to predict similar patterns in
`
`the future. Ex. 1004, ¶[0254].
`
`Ehlers’ description matches what is described in the ’550 patent. Ex. 1001,
`
`5:17-40 (“FIG. 6b … assumes that the air conditioning is turned off from noon to
`
`7 PM. As expected, the inside temperature 304a rises with increasing
`
`outside temperatures 302 for most of that period, reaching 88 degrees at 7 PM.
`
`Because server 106 logs the temperature readings from inside each house …
`
`database 300 will contain a history of the thermal performance of each house”;
`
`“allow[ing] server 106 to calculate … the speed with the temperature inside a
`
`given building will change in response to changes in outside temperature. Because
`
`the server will also log these inputs against other inputs including time of day…
`
`the server will be able to predict … the rate at which inside temperature should
`
`change for given inside and outside temperatures.”); Ex. 1004, ¶[0295] (“computed
`
`factor is used to more accurately compute the recovery time for thermal gain or
`
`loss when compared with the average normalized thermal gain or loss for the
`
`site”); Ex. 1022, 33:22-4: 21; Ex. 1023, ¶¶16-18.
`
`Therefore, EcoFactor’s attempts to distinguish Ehlers’ Fig. 3D fail.
`
`b.
`Ehlers’ Figs. 3E and 3G
`EcoFactor’s attempt to distinguish Ehlers’ Figs. 3E and 3G is even more
`
`strained. POR, 15-18. EcoFactor argues that the “THERMAL GAIN RATE PER
`
`
`
`8
`
`
`
`HOUR” in those figures cannot be a rate of inside temperature change because
`
`Ehlers acknowledges that the HVAC system maintained a specific setpoint for the
`
`entire day. Id.; Ex. 2006, ¶¶41-44. EcoFactor alleges that if the thermal gain rate
`
`was in degrees per hour, Figs. 3E and 3G would indicate a continuous increase in
`
`inside temperatures over a 24-hour period. A POSITA would not have found that
`
`to be a logical interpretation of those figures. Ex. 1023, ¶19.
`
`It is not disputed that, in normal operation, HVAC systems cycle on and off
`
`to maintain a fairly constant inside temperature. Ex. 1022, 20:2-22:22, 23:19-22;
`
`107:16-109:18; Ex. 1023, ¶20. At a setpoint of 72° F., the HVAC system may
`
`cycle on when the temperature rises to 73° F., stay on until the temperature drops
`
`to 71° F., cycle off, and then repeat that cycle. Ex. 1022, 21:8-22:17.
`
`It is not disputed that, in Ehlers’ Figs. 3E and 3G, the HVAC system used a
`
`fixed setpoint for the entire day. Ex. 1004, ¶[0254]. It is also not disputed that these
`
`figures depict on/off cycling of the HVAC system (“HVAC RUN %”) to maintain
`
`a temperature close to the setpoint. Id., ¶[0254], Fig. 3E; Ex. 1023, ¶21; Ex. 1022,
`
`62:18-63:17 (“dead band”), 93:4-97:10, 100:4-102:21, 113:1-21, 116:11-20; see
`
`Ex. 1001, Fig. 6A. For some outdoor temperatures, the HVAC system may only
`
`need to cycle on for 10% of the time to maintain the inside temperature within that
`
`narrow band around the setpoint. Ex. 1023, ¶21. During the off cycle, the inside
`
`temperature rises at approximately the predicted rate of thermal gain, which, as
`
`
`
`9
`
`
`
`shown in Fig. 3E, varies from about 0.5° F. per hour to about 4° F. per hour. Id.
`
`Thus, the rate of thermal gain indicates the predicted rate of change in inside
`
`temperature when the HVAC system cycles off (which it does throughout the day)
`
`for a given outdoor temperature. Id., ¶¶21-23.
`
`As a further example, the operation associated with Ehlers’ Fig. 3G prevents
`
`the HVAC runtime from exceeding 33% in order to conserve energy. Id., ¶22.
`
`
`
`Ex. 1004, Fig. 3G.
`
`The runtime is minimized by calculating a new, higher setpoint based on
`
`predicted rate of thermal gain under current conditions. Ex. 1004, ¶[0256] (“using
`
`its computed thermal gain rate and the corresponding HVAC cycle run time
`
`projections”). Specifically, Ehlers’ system calculates a new setpoint (offset from
`
`the selected setpoint) that is projected to maintain a runtime of 33%. Id. (“[b]y
`
`
`
`10
`
`
`
`adjusting the effective set point upward, the system 3.08 is able to maintain the
`
`HVAC run time”); Ex. 1023, ¶22.
`
`Thus, in Fig. 3G, the predicted rate of thermal gain (change of inside
`
`temperature per unit time) for the current outdoor temperature is used to calculate a
`
`new setpoint. Ex. 1004, ¶¶[0255] (“the dead band in this example would be raised
`
`to 3 degrees F. and the rate of thermal gain per hour would be set at 3 degrees F.
`
`per hour”); [0256] (“uses the learned thermal gain characteristics of the site 1.04
`
`… to maintain a flat level of demand and consumption”).
`
`Therefore, a POSITA would understand that the thermal gain rate is
`
`“learned” from the tracking depicted in Fig. 3D, which prior tracking predicts what
`
`will happen for a given setpoint and a given outside temperature when the system
`
`cycles off. Id., ¶¶[0253]-[0256]. Thus, the thermal gain rate shown in each of Figs.
`
`3E and 3G is a prediction of the rate of internal temperature change, for current
`
`outdoor conditions, when the system cycles off. Ex. 1023, ¶22.
`
`Despite this description in Ehlers, EcoFactor asserts that Ehlers’ thermal
`
`gain rate indicates a continuous increase in inside temperature, even with the
`
`HVAC operating normally to maintain the setpoint. POR, 22. That is illogical.
`
`Even Dr. Palmer acknowledged that a POSITA would understand that a normally
`
`operating HVAC system maintains the setpoint. Ex. 1022, 101:1-102:5; Ex. 1004,
`
`¶[0254]-[0256]; Ex. 1001, 5:10-12 (when an HVAC system “turns on[] the inside
`
`
`
`11
`
`
`
`temperature stays constant”). Thus, the allegation that Fig. 3E suggests a
`
`continuous rise in indoor temperature over 24 hours, while the system determines a
`
`runtime intended to maintain the inside temperature, is untethered from the record.
`
`Ex. 1023, ¶24. Dr. Palmer even acknowledged that EcoFactor’s interpretation
`
`would make no sense. Ex. 1022, 107:16-108:18 (“Q So that wouldn’t make any
`
`sense … A That’s exactly my point.”).
`
`2.
`
`Claim Elements [1c] and [9c] - Predict a Rate of Change of
`Temperatures Inside the Structure in Response to Changes in
`Outside Temperatures
`For the reasons expressed above, a POSITA would have understood that
`
`Ehlers’ Figs. 3D, 3E and 3G (and associated descriptions) indicate an operation
`
`that generates “stored data comprising a plurality of internal temperature
`
`measurements taken within a structure and a plurality of outside temperature
`
`measurements relating to temperatures outside the structure; using the stored data
`
`to predict a rate of change of temperatures inside the structure in response to at
`
`least changes in outside temperatures.” Ex. 1001, claim 1. Specifically, Ehlers’ Fig
`
`3D indicates that tracking and storing of data that is used to learn the rate of
`
`thermal gain inside a structure relative to changes in outside temperature (e.g., 99°
`
`vs. 90° F.). Ex. 1023, ¶12; Ex. 1022, 43:19-44-10 (acknowledging that “changes”
`
`may refer to “two different temperatures at two different days”). These predictive
`
`models are then used in setpoint programming, as discussed below.
`
`
`
`12
`
`
`
`3.
`
`Claim Elements [1d] and [9d] - Calculating Scheduled
`Programming Based on the Predicted Rate of Change, the
`Scheduled Programming Comprising at Least a First Automated
`Setpoint at a First Time
`Ehlers uses its learned predictions pertaining to how quickly an inside
`
`temperature will rise in response to different outside temperatures to create new
`
`setpoint programming. For instance, the thermal gain rate is used to calculate a
`
`new “offset” setpoint. Ex.1004, ¶¶[0253]-[0254], [0256]. As discussed above, the
`
`offset setpoint is selected to reduce the HVAC runtime to conserve energy (i.e., the
`
`new setpoint requires less runtime than the prior setpoint). Ex. 1023, ¶22. In Fig.
`
`3G’s example, the system repeatedly changes the setpoint to prevent the runtime
`
`from exceeding 33% as the outdoor temperature rises. Each new setpoint is
`
`calculated based on the predicted rate of change (e.g., by knowing how quickly the
`
`inside temperature is expected to rise during the off cycle, the system can select a
`
`setpoint that will allow for an off-cycle period that is 67% of the runtime). Ex.
`
`1004, ¶[0256]. Thus, Ehlers calculates scheduled programming for one or more
`
`times based on the predicted rate of change, wherein the programming includes a
`
`first automated setpoint at a first time. See Ex. 1001, claims 1 and 9.
`
`
`
`13
`
`
`
`While those offset setpoints in Ehlers are “automated,” EcoFactor argues
`
`that the offset setpoints should not count as automated because the user can restrict
`
`how far the offset may deviate from the user’s setting. POR, 29-30.2
`
`Ehlers clearly describes calculating a new setpoint that is different from the
`
`one selected by a user. Ex. 1004, ¶¶[0141] (“setpoints are offset”; “original
`
`setpoint (prior to the offset change)”), [0150] (“can change the heating and cooling
`
`setpoint(s) and offset values of the thermostat”), [0255] (“permit the system in this
`
`example to vary the temperature in the home from the normal set point of 72 F by
`
`the 4 degree offset …”), [0256] (“computes the required effective set point offset
`
`…”). These changes to a manual setpoint are automated because the computer
`
`selects the new setting. Ex. 1023, ¶¶25-26; Ex. 1022, 65:6:66-21, 68:7-22, 121:5-
`
`122:17.
`
`A user may influence how far from the manual setpoint the automated
`
`setpoint may stray from the original setpoint, but that does not affect the analysis.
`
`Specifically, in Ehlers, a user may elect various settings from “100% comfort
`
`management … to 100% economic management.” Ex. 1004, ¶[0255]. The settings
`
`are “tied to the number of degrees from the set point that the customer would make
`
`
`2 This and other arguments by EcoFactor appear to diverge from EcoFactor’s
`infringement positions in the related litigation. Therefore, ecobee reserves the right
`to present non-infringement positions in the litigation that are based on the
`arguments presented by EcoFactor in this IPR.
`14
`
`
`
`
`
`available to the system.” Id. In one setting, the system may permit a 4° deviation
`
`(e.g., from 72° to 76°). Id. Regardless of whether a user affects boundaries for the
`
`adjustment does not change the fact that the system determines when to change the
`
`setpoint and what the specific, new setpoint will be. Ex. 1023, ¶27. Therefore, the
`
`offset setpoint is automated. Id. Such automated adjustments may happen
`
`throughout the day as the outside temperature fluctuates. Id.
`
`As another example, in recovery operations from one mode to another,
`
`Ehlers’ system performs ramping from one temperature to another. Such
`
`operations often involve selecting intermediate setpoints (time and temperature) to
`
`allow the system to reach a desired user setting by a desired time. Id., ¶28; Ex.
`
`1004, ¶¶ [0246], [0255], [0295]; Ex. 1002, ¶¶105-106. At the very least, the
`
`recovery involves selecting a setpoint at a time calculated based on the predicted
`
`rate of change in order to match the user’s programming (e.g., reaching 72° F. by
`
`6pm may require setting the temperature to that temperature by 5pm)). Ex. 1023,
`
`¶28; Ex. 1022, 37:19-39:4, 63:18-64:18. This use of the predicted rate of change
`
`matches the use described in the ’550 patent. Ex. 1001, 5:35-40 (“to determine
`
`when the HVAC system must be turned on in order to reach the desired
`
`temperature at the desired time”). Thus, EcoFactor’s argument against this
`
`disclosure in Ehlers (POR, 31-34) seems to reject the very description in the
`
`specification. Ex. 1001, 4:62-5:40. Notably, while the POR discusses examples the
`
`
`
`15
`
`
`
`’550 patent to give context to some claim features, it is silent as to an example
`
`corresponding to this claim element. See POR, 2-4. This silence is likely due to the
`
`fact that reference to the specification’s description of using predicted rates of
`
`change in setpoint programming would underscore the similarity of Ehlers
`
`recovery time example. Compare Ex. 1004, ¶[0246], with Ex. 1001, 5:35-40.
`
`4.
`
`Claim Elements [1e] - Generating a Difference Value Based on
`Comparing an Actual Setpoint to the First Automated Setpoint
`and Detecting a Manual Change to the First Automated Setpoint
`Based on the Difference Value – and [9e] – Comparing the
`Actual Setpoint to the First Automated Setpoint and Detecting a
`Manual Change to the First Automated Setpoint by Determining
`Whether the Actual Setpoint and First Automated Setpoint are
`the Same or Different
`In addition to implementing automated setpoints, Ehlers’ system learns from
`
`user preferences by detecting manual changes to the setpoint. Ex. 1004, ¶[0242]
`
`(“system 3.08 manages comfort for the customer site 1.04 by learning from the
`
`user’s inputs or adjustments to the system 3.08 to change or modify indoor air
`
`temperature”). This learning is not limited to particular circumstances. A POSITA
`
`would have understood that, regardless of whether the current setpoint was a
`
`setpoint selected by the user or an automated setpoint selected by the system to
`
`conserve energy, the system would learn from the user’s adjustments. Ex. 1023,
`
`¶29; Ex. 1004, ¶¶[0243] (explaining that the programming “would be modified as
`
`needed based on the user’s changes to the set point”), [0308]-[0309]. Specifically,
`
`Ehlers does not state that it learns from user adjustment only when those
`16
`
`
`
`
`
`adjustments are to the user’s own settings. See Ex. 1022, 131:15-132:14, 124:13-
`
`21, 126:6-128:20; Ex. 1004, ¶¶[0308]-[0309]. Instead, Ehlers explains that it tracks
`
`when any changes are made by the user. Ex. 1004, ¶¶ [0308]-[0309]. Ehlers also
`
`explains that the system routinely sets automated setpoints to conserve energy. Id.,
`
`¶[0256], Fig. 3G. Thus, a POSITA would have understood that Ehlers suggests
`
`detecting changes to any setpoints (automated or manual).3
`
`EcoFactor also argues that Ehlers description of learning from user
`
`adjustments is not directly tied to the use of predictive models to minimize HVAC
`
`runtimes. POR, 37. But the same could be said of the ’550 patent. See Ex. 1001,
`
`5:5-66. In both documents, predicting rates of change and learning from user
`
`adjustments are distinct operations. A POSITA would find it obvious that these
`
`two features would be used together in the same thermostat control system. Ex.
`
`1023, ¶29.
`
`5. Wruck
`While Ehlers describes learning from a user’s adjustment to the setpoint, it
`
`does not detail how the comparison of a prior setpoint to a new setpoint would
`
`have been made. Wruck shows a common way for detecting such changes—
`
`
`3 This was generally known in the field. See Ex. 1019, 3:25-39 (“regardless of
`whether the current setpoint temperature was manually entered or was
`automatically activated as a learned setpoint temperature”), 4:42-5:33, 5:45-48.
`17
`
`
`
`
`
`determining the difference between the scheduled setting and the actual setting.
`
`Petition, 17-19.
`
`EcoFactor argues that Wruck does not compare different setpoints or detail
`
`what is meant by a “Delta value.” Ex. 2006, ¶55. However, Wruck describes that,
`
`when a user overrides a scheduled setpoint, the system detects the change so that it
`
`can update the displayed setpoint. Ex. 1002, ¶¶59-60, 126-129; Ex. 1005, ¶¶[0005],
`
`[0015], [0125], [0150], [0231], [0198], Fig. 20b. To detect the change, Wruck’s
`
`system determines the “Delta value” between the actual setpoint and the scheduled
`
`setpoint. If the “Delta value” is greater than zero, Wruck determines that a change
`
`has been made. Ex. 1002, ¶¶60-61; Ex. 1005, ¶¶[0005], [0015], [0104], [0150],
`
`Tables 28 and 36. This description would have been more than sufficient for a
`
`POSITA to understand that Wruck indicates analyzing a “difference value” that is
`
`the difference between the scheduled and actual setpoints. Ex. 1023, ¶30. In fact,
`
`Dr. Palmer admits that “Delta” is known to mean “a change.” Ex. 1022, 134:1-20,
`
`139.
`
`Also, EcoFactor argues that Wruck does not teach an automated setpoint.
`
`POR, 41. However, this feature is already taught by Ehlers, making the argument
`
`mere misdirection. Thus, EcoFactor’s strained argument against Wruck fails.
`
`
`
`18
`
`
`
`B. Combination of Ehlers, Wruck and Harter
`For this ground, EcoFactor relies primarily on the arguments made with
`
`respect to the combination of Ehlers and Wruck. POR, 45-47. Those arguments fail
`
`for the reasons discussed above.
`
`EcoFactor also alleges that the Petition does not contain an explanation as to
`
`the manner of combining Harter. However, the Petition makes clear that Harter
`
`adds more detail on how a thermostatic controller learns from a user’s manual
`
`inputs. Petition, 59-60, 63-65. The Petition explains that the system learns from
`
`manual adjustments by, for instance, tracking similar manual adjustments on three
`
`consecutive days and, on the next day, automatically enters that adjustment in
`
`advance of when the user had made the adjustment on previous days (i.e.,
`
`anticipating that the user will want to make the same change again). Petition, 65-
`
`66; Ex.1019, 4:14-29, 1:39-50. This learning of user preferences and associated
`
`adjustments are continually updated, such that the system “can begin operating as a
`
`programmed thermostat.” Ex. 1019, 3:25-27. In fact, the system learns from user
`
`adjustment “regardless of whether the current setpoint temperature was manually
`
`entered or was automatically activated as a learned setpoint temperature.” Id. 3:28-
`
`39, 4:42-5:33, 5:45-48 (“activate learned weekly setpoints at learned times, and
`
`keep them active until the activated setpoint is overridden by the next learned
`
`setpoint or interrupted by a manually entered setpoint.”).
`
`
`
`19
`
`
`
`Thus, while EcoFactor alleges that Harter does nothing to address the
`
`deficiencies it alleges with respect to Ehlers and Wruck, Harter makes even more
`
`clear that it was known to detect manual changes to “automated” setpoints in order
`
`to learn user behavior. As established in the Petition, this further informs how the
`
`learning algorithms in Ehlers would operate to continually monitor manual
`
`adjustments regardless of whether the changes were to a setpoint previously set by
`
`a user or the system. Petition, 60. Harter makes clear that this is true of first and
`
`second automated setpoints, as the intention of these types of learning algorithms
`
`(in Harter and Ehlers) was to continuously learn from and adapt to user
`
`adjustments.
`
`IV. Secondary Considerations
`
`EcoFactor argues that prior information sharing between Dr. Auslander and
`
`the named inventors, as well as the publication of related data, establishes that the
`
`claimed subject matter was “beneficial” and “met a long-felt need.” POR, 47-48.
`
`First, Dr. Auslander participated in the mutual sharing of information due, in large
`
`part, to his role as a professor at a public university and the same did not imply any
`
`benefit with respect to what is claimed. Ex. 1023, ¶31. Further, EcoFactor’s
`
`argument is woefully deficient in that
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