Trials@uspto.gov
`571-272-7822
`
`|
`
`Paper No. 11
`Entered: December 21, 2015
`
`UNITED STATES PATENT AND TRADEMARK OFFICE
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`
`GOOGLEINC., NEST LABS, INC., and
`DROPCAM,INC.,
`Petitioners,
`
`v.
`
`e.DIGITAL CORPORATION,
`Patent Owner.
`
`Case IPR2015-01474
`Patent 8,311,524 Bl
`
`Before KEVIN F. TURNER, HYUN J. JUNG, and BARBARA A.PARVIS,
`Administrative Patent Judges.
`
`JUNG,Administrative Patent Judge.
`
`—
`
`DECISION
`Institution of Inter Partes Review
`37 CFR. § 42.108
`
`
`571-272-7822
`
`|
`
`Paper No. 11
`Entered: December 21, 2015
`
`UNITED STATES PATENT AND TRADEMARK OFFICE
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`
`GOOGLEINC., NEST LABS, INC., and
`DROPCAM,INC.,
`Petitioners,
`
`v.
`
`e.DIGITAL CORPORATION,
`Patent Owner.
`
`Case IPR2015-01474
`Patent 8,311,524 Bl
`
`Before KEVIN F. TURNER, HYUN J. JUNG, and BARBARA A.PARVIS,
`Administrative Patent Judges.
`
`JUNG,Administrative Patent Judge.
`
`—
`
`DECISION
`Institution of Inter Partes Review
`37 CFR. § 42.108
`
`
`
`IPR2015-01474
`Patent 8,311,524 Bl
`
`I.
`
`INTRODUCTION
`
`Google Inc., Nest Labs, Inc., and Dropcam,Inc. (“Petitioners”’) filed a
`Petition (Paper2, “Pet.”), requestinginstitution of an interpartes review of
`claims 1, 3-5, 7, and 9 (“the challenged claims”) of U.S. Patent No.
`
`8,311,524 Bi (Ex. 1001, “the ’524 patent”). e.Digital Corporation (‘Patent
`
`Owner”) timely filed a Preliminary Response (Paper8, “Prelim. Resp.”).
`
`Wehavejurisdiction under 35 U.S.C. § 314, which providesthat an inter
`
`partes review maynotbeinstituted “unless .
`
`.
`
`. there is a reasonable
`
`likelihood that the petitioner would prevail with respect to at least 1 of the
`
`claims challengedin the petition.”
`
`Upon consideration of the Petition and Preliminary Response,and for
`
`the reasons explained below, we determinethat Petitioners have shownthat
`
`there is a reasonable likelihood that they would prevail with respectto at
`
`least one ofthe challenged claims, and weinstitute an inter partes review of
`claims 1, 3-5, 7, and 9 of the °524 patent.
`
`A. Related Proceedings
`
`The parties indicate that the °524 patent is involvedin e. Digital Corp.
`
`v. Dropcam, Inc., Case No. 3:14-cv-04922-JST (N.D. Cal.), e. Digital Corp.
`
`v. Dropcam, Inc., Case No. 3:14-cv-01579 (S.D. Cal.), e.Digital Corp. v.
`
`ShenZhen Gospell Smarthome Electronic Co., Ltd., Case No. 3:15-cv-
`00691-JST (N.D. Cal.), and e. Digital Corp. v. ArcSoft, Inc., Case No. 3:15-
`
`cv-00056-BEN-DHB (S.D. Cal.). Pet. 59; Paper 6, 2 (labeled “Paper No.
`
`4”),
`
`
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`IPR2015-01474
`Patent 8,311,524 Bl
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`B. The ’524 Patent (Ex. 1001)
`T
`
`the classification of a person’s current
`
`actions such that selected callers can automatically or manually gauge the
`ot
`
`intrusiveness of a communication request.” Ex. 1001, 1:17—20. Figure 1 of
`
`the ’524 patent is reproduced below.
`
`FIG. 1
`
`—_
`
`ic
`
`Electronic Device
`
`Location
`Sensor
`
`Inertial
`Sensor
`
`Optical
`Sensor
`
`Acoustic
`Sensor
`
`
`
`Location
`Processor
`
`Transceiver
`
`Pe
`
`CROROY
`
`Gpucal
`Pincessa
`
`ALOU SIC
`FTCCRSSr
`
`Caiculating
`Logic
`
`Memory
`
`Social
`Templates
`
`Social
`Training
`
`170
`
`Figure 1 is a block diagram of an electronic device. Id. at 8:66—67.
`Mobile device 100 includes location sensor 110, inertial sensor 120, optical
`
`sensor 130, and acoustic sensor 140.
`
`/d. at 9:22—27, 35-46, 11:22-26.
`
`Mobile device 100 monitors location, acceleration, orientation, audio, and
`
`optical samples using sensors 110, 120, 130, 140.
`
`/d. at 9:19-21. For
`
`example, acoustic sensor 140 can generate acoustic measurement data, and
`
`optical sensor 130 can generate simple light level measurement data. Jd. at
`
`11:52-54, 62-64.
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`Location sensor 110 is coupled to location processor 115; inertial
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`seiisor 120 is coupied to motion processor 125; acoustic sensor 140is
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`coupled to acoustic processor 145; and optical sensor 130 is coupled to
`
`optical processor 135. Jd. at 13:33-34, 42-43, 14:3-5, 9-10. Calculating
`
`logic 150 receives data from processors 115, 125, 135, 145 and uses the data
`
`to classify a user’s activity from predefined, identifiable useractivities. Jd.
`
`at 14:31-35, 55-58. Calculating logic 150 can identify the user’s social
`
`activity “by monitoring for different social signatures, and applies a
`
`corresponding social template to determine howto treat an incoming
`
`communication request.” Jd. at 14:58-62. The social signature can be a
`
`combination of sensors, with each sensor detecting a certain value range.
`
`/d.
`
`at 15:56-66 (Table 1). “Each social signature is indicative of a different
`
`type of activity.” Jd. at 15:38-39. When enoughevents indicative of a
`
`particular user social activity are detected, calculating logic 150 identifies
`
`/d. at 14:63-66.
`the activity as being performed by the user.
`|
`Calculating logic 150 compares the processed data from sensors 110,
`120, 130, 140 with social templates 165 stored in memory 160. Jd. at 14:31-
`
`37. From the identified social signature, calculating logic 150 selects a
`
`social template that determines how much information is providedto others.
`
`Id. at 15:45—49. For example, the social template may allow specific friends
`
`to know that the useris drinking coffee, may allow co-workers to know that
`
`the user is in a personal meeting, and may allow others to know that the user
`
`is busy and not to be disturbed.
`
`/d. at 15:24-28.
`
`Calculating logic 150 can provide information to a requesting caller
`
`according to a hierarchicalsocial classification. Jd. at 14:39-41. “Examples
`
`of hierarchical social classification that can be identified include high level
`
`
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`available, busy, do not disturb,” and each classification can have further,
`
`inore accurate classifications that can be made available to more select social
`groups. Id. at 14:44-48. “Eachset of hierarchical social classifications is
`
`stored in a separate social template.” Jd. at 14:53-54.
`
`To set up a social template, social training program 167 in memory
`
`160 is activated, and a social signature is associated with a particular social
`
`template.
`
`/d. at 17:31-35. Specifically, data sensed by sensors 110, 120,
`
`130, 140 are correlated with a newsocial template, and the user enters how
`
`muchinformation is to be provided to different categories of potential
`
`callers. Id. at 17:35-41.
`
`C. Illustrative Claim
`The °524 patent has 18 claims. Ofthe challenged claims, claim 1 is
`
`independent and claims 3—5, 7, and 9 depend from claim 1. Claim 1 is
`
`reproduced below:
`
`A method of automatically providing differing
`1.
`levels of information according to a predetermined social
`hierarchy, the method comprising:
`receiving sensor data transmitted from a sensor set
`producing the sensor data,
`the sensor data including a first
`detected sensor value comprising optical information from an
`optical sensor of the sensor set which detects an amountoflight
`of an environment of the communication device and a second
`detected sensor value comprising acoustic information from an
`acoustic sensor of the sensor set which detects a soundlevel of
`the environmentof the communication device;
`constructing a social signature using the received sensor
`
`data;
`
`determining which one of a plurality of stored social
`templates has a social signature with a greatest correspondence
`with the constructed social signature through comparison ofthe
`first and second detected sensor values and first and second
`sensor value ranges of each social template, each stored social
`
`
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`template corresponding to a unique social signature comprising
`corresponding first and second sensor value ranges and each
`social template being selectable to provide, for each level of the
`predetermined social hierarchy, a corresponding differing
`amount of information to each member of the predetermined
`social hierarchy; and
`retrieving from a memory the determined one social
`template having the greatest correspondence and having the
`detected amountof light within the first sensor value range and
`the detected sound level within the second sensor value range,
`wherein at
`least one member of the predetermined social
`hierarchy is provided only as much information as allowed
`based on the retrieved social template.
`
`D. Challenges
`
`Petitioners challenge, under 35 U.S.C. § 103:
`
`(1) claims 1, 3-5, 7, and 9 as unpatentable over U.S. Patent
`Application Publication No. 2009/0300525 Al to Jolliff, published Dec.3,
`2009 (Ex. 1005, “Jolliff’) and U.S. Patent Application Publication No.
`2009/0094179 Al to Jager, published Apr. 9, 2009 (Ex. 1006, “Jager”); and
`(2) claims 1, 3-5, 7, and 9 as unpatentable over International
`
`Publication No. WO 2009/043020 A2 to Miluzzo, published Apr. 2, 2009
`
`(Ex. 1007, “Miluzzo’’) and U.S. Patent Application Publication No.
`
`2006/0004680 A1 to Robarts, published Jan. 5, 2006 (Ex. 1008, “Robarts”).
`
`Pet. 3, 10-58.
`
`Il.
`
`ANALYSIS
`
`A. Claim Construction
`
`In an inter partes review,claim terms in an unexpired patentare
`interpreted according to their broadest reasonable construction in light of the
`
`specification of the patent in which they appear. 37 C.F.R. § 42.100(b);
`
`
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`IPR2015-01474
`Patent 8,311,524 Bl
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`Office Patent Trial Practice Guide, 77 Fed. Reg. 48,756, 48,766; Jn re
`Cuozzo Speed Techs., LLC, 793 F.3d i268, 1275-79 (Fed. Cir. 2015). Only
`those terms in controversy need to be construed, and only to the extent
`
`necessary to resolve the controversy. Vivid Techs., Inc. v. Am. Sci. & Eng’g,
`
`Inc., 200 F.3d 795, 803 (Fed. Cir. 1999). ~.
`
`Petitioners propose interpreting “social template,
`
`99 66
`
`social hierarchy,”
`
`and “level of [a] social hierarchy.” Pet. 6-9. Patent Owner respondsthat
`
`claim constructionis “irrelevant at this stage.” Prelim. Resp. 7.
`
`For the purposes of this Decision, we determine an express
`
`construction of any term is not necessary.
`
`B. Obviousness of Claims 1, 3-5, 7, and 9 over Miluzzo and Robarts
`
`Petitioners contend that claims 1, 3-5, 7, and 9 are rendered obvious
`
`by Miluzzo and Robarts with citations to the disclosures in these references
`and a Declaration of David Hilliard Williams (Ex. 1003, “the Williams
`Declaration’). Pet. 34-58.
`
`1. Miluzzo (Ex. 1007)
`
`Miluzzo teaches a “method for injecting sensed presence into social
`networking applications.” Ex. 1007, Abstract. In particular, sensor data
`associated with a user are received by a computer, the computer analyzes the
`
`sensor data to infer a presence status of the user, and then the presence status
`
`stores the data in a database and sendsthe presencestatusto a social
`
`networkingserver to update social networking applications based upon the
`
`user’s preferences.
`
`/d. Figure 1 is reproduced below.
`
`
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`114
`
`
` SOCIAL NETWORKING
`SERVER 126
`
` |PRESENCE 1224
`
`
`——_— — — A
`
`
`
`PRESENCE124
`
`FIG. 1
`
`Figure 1 illustrates a system for injecting sensed presence into social
`
`networking applications. Jd. § 8. As shownin Figure 1, user 102 has cell
`
`phone 106, personal digital assistance (PDA) 108, and embeddedsensorunit
`
`NETWORK 120
`
` PRESENCE SERVER
`416
`
`PRESENCE122
`
`
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`110. Jd. § 13. Cell phone 106 includes a camera for sensing images around
`
`user 102 and a giobal positioning sensor (GPS) unit for determining the
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`location of user 102. Jd. PDA 108 includes a temperature sensorfor sensing
`
`the temperature near user 102. Jd. Embedded sensors 110 include one or
`
`more accelerometers for determining activity of user 102. Jd. Embedded
`sensor unit 110 periodically provides sensordata to cell phone 106 via
`wireless link 111, which may transmit using Bluetooth technology. Id. Ff
`17, 26. Additional sensors within devices carried by user 102 include a
`
`microphone,a light sensor, and a humidity sensor. Jd. J{ 16, 81.
`
`Asalso shownin Figure 1, second user 104 has network computer
`
`112 that includes one or more sensors. /d. 414. Sensed data are sent from
`
`notebook computer 112 to presence server 116 via network 120, which may
`be the Internet or other wired or wireless networks. Jd. J 13, 14, 26, 69.
`Presence server 116 analyzes sensordata to infer activity of users 102 and
`
`104. Id. F914, 69. The data may be processed by an analysis component
`
`within server 116, such as inference engine 212 which mayinclude human
`
`activity-inferring algorithms. Jd. J 43, 45. For example, presence server
`
`116 uses sensor data to define presence status 122 of user 102 and presence
`
`status 124 of user 104. Jd. Characteristics of users 102 and 104, such as
`
`presence status 122 and 124, are sent to social network server 126 that
`
`supports one or more social networking applications 119, such as Facebook
`
`or MySpace. Jd. §§ 21, 69. The presence information for the associated
`social networking applications may be updated with presencestatus 122,
`124. Id.
`
`Certain embodiments of system 100 use the “Virtual Walls model
`
`which provides different levels of disclosure based on context, enabling
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`access to the complete sensed/inferred data set, a subset of it, or no accessat
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`all.” Jd. 953.
`
`2. Robarts (Ex. 1008)
`
`Robarts teaches techniques for using user context modeling
`
`techniquesto identify and provide appropriate computer actions based on
`current context. Ex. 1008, Abstract. A body-mounted computer receives
`input and forwardsit to characterization system 100. Jd. { 56.
`
`Characterization system 100 receives sensed user information via user
`sensors 126 and sensed environment information via environment sensors
`
`128. Id. Characterization system 100 processes the information to create a
`current model of theuser context based on multiple attributes. Id. J] 56, 63.
`
`Additionally, a theme is identified that matches the current context.
`
`Id. § 157. A themewill match the current context if specified attributes have
`
`current values that are the sameas the possible values for the theme. Id.
`
`Robarts also teaches that selection of a current theme from multiple
`
`matching themes maybe performedin a variety of ways. Jd. 162. For
`
`example, a theme maybegiven an associated degree of match and then the
`
`theme with the highest degree of matchis selected. Id.
`
`Robarts further teaches a themedata structure that has privacy,
`
`security, and permission information. Jd. § 203. Examplesofdifferent
`privacy valuesincludeprivate, public, work, family, friends, acquaintances,
`
`people in the immediate vicinity, and everyone in mycontact list.
`
`/d.
`
`3. Claim 1
`
`Petitioners argue that Miluzzo teachesthe limitations of claim 1,
`
`except it does not describe explicitly howit infers a user’s status from sensor
`
`data and howit stores, organizes, and retrieves a user’s status and privacy
`
`10
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`settings. Pet. 34-35 (citing Ex. 1007 Abstract, J] 52, 53, 81), 38-40(citing
`
`Ex. 1007 Absiraci, Jfj 16, 21, 53, 56, 69, 81), 42 (citing Ex. 1007 4] 43, 45,
`
`53), 45 (citing Ex. 1007 ¥ 52), 48 (citing Ex. 1007 {J 52, 53, 69).
`
`Petitioners rely on Robarts for teaching themesthat includeattributes,
`
`which can be specified as a range and can be stored in memory,creating a
`
`current model from collected sensor data, identifying a theme based on
`
`matching attributes, and selecting a theme with the highest degree of match.
`
`Pet. 35-36 (citing Ex. 1008 Abstract, J{ 40, 157, 203), 37 (citing Ex. 1008
`
`q 40), 40-49 (citing Ex. 1008 Abstract, J] 40, 56, 63, 92, 157, 162, 203, 213,
`
`224, Fig. 8).
`
`Petitioners assert that a person of ordinary skill would have been
`
`motivated to seek out a reference, such as Robarts, that describes how to
`
`store, organize, and retrieve a user’s privacy settings, which Miluzzo does
`
`not describe explicitly and would have been motivated to seek out
`
`information for implementing an inference engine. Pet. 35-36 (citing Ex.
`1003 4 114), 42 (citing Ex. 1003 { 129).
`
`Petitioners also contend that it would have been obvious to modify
`
`Miluzzosothat its privacy settings can be stored with sensorattributes in the
`
`themedata structures of Robarts, which include privacy settings, and that a
`
`person of ordinary skill would have been motivated to incorporate Robarts
`
`into Miluzzo “to organize andretrieve the user’s ‘group membership
`
`policies’ because Robarts teaches that ‘the themes each includerelated sets
`
`of attributes that reflect the context of the user.’” Jd. at 37 (citing Ex. 1003
`118; Ex. 1007 4 53; Ex. 1008 4¥ 40, 203). Petitioners further argue that the
`themes and user context recognition of Robarts is a substitute for Miluzzo’s
`
`inference engine, and the results would have beenpredictable. Jd.
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`Petitioners further contend that it would have been obvious to modify
`
`Miluzzo’s inference engine to incorporate the theme and user context
`recognition of Robarts because both recognize a user’s context based on
`
`sensor data. Jd. at 43.
`
`Petitioners also assert that a person of ordinary skill would have
`
`understood (1) that, when adapting the themes of Robarts for use in
`
`Miluzzo’s inference engine, the privacy settings would correspondto
`
`Miluzzo’s group memberpolicy or social hierarchy, (2) that the attributes in
`
`each theme of Robarts are unique, (3) that Miluzzo describes providing
`
`differing amounts of information to a social hierarchy, (4) that matching
`
`attributes would involveattributes in ranges, and (5) that the group
`
`membership policy of Miluzzo would be based on social hierarchy groups.
`
`Pet. 42 (citing Ex. 1003 4 128), 44 (citing Ex. 1003 § 132; Ex. 1008 4 157),
`46 (citing Ex. 1003 ¥ 136), 47 (citing Ex. 1003 § 140), 49 (citing Ex. 1003 J
`143). At this stage of the proceeding, Petitioners’ arguments are reasonable
`and supported by record evidence.
`Patent Ownerrespondsthat “Miluzzo provides no description of a
`
`data structure that can be equated with the ‘social template.’” Prelim. Resp.
`
`43. The argumentis not persuasive becausePetitioners argue “Robarts
`
`teaches identifying a theme(i.e., the social template).” Pet. 41.
`
`Patent Owneralso arguesthat Petitioners do not “point to any portion
`
`of Robarts that specifies the collection of ‘attributes’ must be unique to any
`
`particular theme,” and Robarts does not require attributes to be unique.
`
`Prelim. Resp. 43-44 (citing Pet. 38, 43-44; Ex. 1008 § 207). Patent Owner
`
`quotes a portion of paragraph 207 that states “themes can also specify other
`
`types of information, such as whether someorall of the information about
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`the themeis available to other themes.” Jd. The quoted portion, however,
`
`does not directly address the atiributes of a theme. Aiso, Petitioners argue
`that a person of ordinary skill “would have understood that Robarts’
`attributes . .. are unique because Robarts’ system uses comparison of
`
`attributes to select one single appropriate theme.” Pet. 44 (citing Ex. 1003 {
`
`132; Ex. 1008 § 157). Thus, on the current record, we are not persuaded.
`
`Patent Ownerfurther argues that Petitioners rely on the attributes,
`
`which are described in paragraph 92 of Robarts, as part of the “detected
`
`social signature” rather than the recited “social template.” Prelim. Resp. 44—
`
`45 (citing Pet. 41-42). Petitioners, however, cite paragraphs 56 and 63 of
`
`Robarts for teaching the creation of “a current model(i.e., the constructed
`
`social signature) of the user context based on collected sensor data.” Pet. 40.
`
`Petitioners cite paragraph 92 of Robarts for teaching thatits attributes can be
`
`specified as arange. See Pet. 42, 44. On the current record, we are not
`
`persuaded.
`
`With reference to Figure 13 of Robarts, Patent Owner arguesthat the
`“uncertainty value” of Robarts is not a “sensor value range” and instead,“‘is
`used to determine the accuracy ofa particular attribute contained within a
`theme.” Prelim. Resp. 45-47. Petitioners, however, cite Figure 8, not
`
`Figure 13, for teaching that the attributes of Robarts can include data from
`
`light and sound sensors, and Petitioners cite paragraph 92 of Robarts for
`
`teaching a “sensor value range.” See Pet. 43-44. Paragraph 92 describes
`
`“an uncertainty value that represents a range of values aroundtheattribute
`
`value that the attribute is likely to have.” Because Patent Owner’s
`
`arguments do not address Figure 8 or paragraph 92 of Robarts, we are not
`
`persuaded.
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`Onthe present record, we are persuadedthat Petitioners have a
`
`reasonable likelinood of prevailing in showingthat claim i is unpatentable
`over Miluzzo and Robarts.
`
`4. Dependent Claims 3—5, 7, and 9
`
`For claims 3 and 4, Petitioners argue that Miluzzo and Robarts teach
`
`their limitations. Pet. 49-55 (citing Ex. 1007 {J 45, 60; Ex. 1008 Abstract,
`
`qJ 20, 40, 194, 199, 214, 272, 273, 276-278, Figs. 12A—12H,17).
`
`Petitioners assert Miluzzo and Robarts would be combined for reasons
`
`similar to those asserted for claim 1, would improve Miluzzo’s ability to
`make inferences, and is a known technique. See id. (citing Ex. 1003 ¥ 147,
`149). Petitioners also assert that it would have been obviousto incorporate
`
`detected error by adjusting the uncertainty valueand to create a new theme
`based on current context information and that a person ofordinary skill
`would have recognized that an updated theme would be stored in memory
`
`for future use. Jd. (citing Ex. 1003 FJ 151, 152, 158, 159).
`
`Patent Ownerrespondsthat, for claims 3 and 4, Robarts does not
`
`teach explicitly that the appropriateness verification of Robarts“is triggered
`by a detection of an ‘error between the detected socialsignature and the
`social signature of the determined one social template having the greatest
`
`correspondence,”” as required by these claims. Prelim. Resp. 48-49(citing
`
`Ex. 1008 § 273). However, Petitioners rely on a portion of Robarts that
`
`describes, when a suggested rule is presented to the user for verification, the
`user can respond with “the system should ask the user for confirmation
`
`(because the suggestion was good, just not entirely appropriate).” Pet. 50-
`
`51 (citing Ex. 1008 | 276). Petitioners’ argumentis reasonable and
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`supported by the-record developed thusfar, and therefore, at this stage of the
`
`proceeding, Patent Owner's argument is not persuasive.
`
`Patent Owneralso argues that Petitioners’ motivation to combine
`
`Miluzzo and Robarts is unsupported (discussing Ex. 1003 § 172). Prelim.
`
`Resp. 49. Paragraph 172 of the Williams Declaration cites paragraphs 278—
`
`285 of Robarts, which reasonably supports the contention of paragraph 172.
`Onthe current record, Patent Owner’s argumentis not persuasive.
`Patent Owneralso argues that Robarts does not teach updating a
`
`social signature with the detected error, as required by claims 3 and4.
`
`Prelim. Resp. 49-51. Patent Ownerasserts that examples of feedback
`
`described in Robarts do not adjust the uncertainty value and instead add a
`
`new sensor value.
`
`/d. at 50-51 (citing Ex. 1008 Jf 279-280, 285-309).
`
`Petitioners, however, rely on paragraph 276 of Robarts that describes
`
`“specify[ing}] more information to the system to improve the appropriateness
`
`of the request” and Petitioners assert it would have been obvious.that the
`
`“more information” would involve adjusting a range of an uncertainty value.
`See Pet. 52 (also citing Ex. 1003 4 151; Ex. 1008 § 214). At this stage ofthe
`
`proceeding, Patent Owner’s argumentis not persuasive.
`
`For claim 5, Petitioners argue that Robarts teachesits limitations and
`
`the combination of Miluzzo and Robarts renders the claim obvious. Pet. 55—
`
`57 (citing Ex. 1003 J 164; Ex. 1007 9 52, 53; Ex. 1008 Abstract [¥ 199,
`
`203, 299, Fig. 17). For claims 7 and 9, Petitioners contend that Miluzzo
`
`teachestheir limitations, and thus, Miluzzo and Robarts render obvious these
`
`claims. Pet. 57-58 (citing Ex. 1003 ¢ 170; Ex. 1007 4 21, 53, 69). At this
`
`stage of the proceeding, Petitioners’ contentions regarding these claims are
`
`
`
`IPR2015-01474
`Patent 8,311,524 Bl
`
`reasonable and supported by record evidence. The Preliminary Response
`does not present any specific argumenis for dependentciaims5, 7, and 9.
`
`Thus, the present record indicates that Petitioners have a reasonable
`
`likelihood of prevailing in the challenge of claims 3—5, 7, and 9 as
`
`unpatentable over Miluzzo and Robarts.
`
`C. Challenge based on Jolliffand Jager
`Petitioners also contend that claims 1, 3—5, 7, and 9 are unpatentable
`
`over Jolliff and Jager. Pet. 10-34. Under 35 U.S.C. § 314, the Director
`
`“may not” institute review unless certain circumstances are met, and thus,
`
`institution of inter partes review is discretionary. The Director has
`delegated the decision to institute inter partes review to the Board. See
`37 C.F.R. § 42.4 (“[t]he Board institutes the trial on behalf of the Director.”).
`
`Thus, the Board,at its discretion, may determine whetherto institute an inter
`
`partes review. Furthermore, in determining whetherto institute an inter
`
`partes review,“the Board may authorize the review to proceed... on all or
`
`some of the grounds of unpatentability asserted for each claim.” 37 C.F.R.
`
`§ 42.108. Accordingly, we exercise our discretion to decline institution on
`
`this additional ground of unpatentability.
`
`III.
`
`CONCLUSION
`
`For the foregoing reasons, we determine that Petitioners have
`
`demonstrated that the information presented in the Petition in view of the
`Preliminary Response showsthat there is a reasonable likelihood that
`Petitioners would prevail in proving the unpatentability of claims 1, 3-5, 7,
`
`and 9 of the °524 patent as unpatentable over Miluzzo and Robarts.
`
`16
`
`
`
`IPR2015-01474
`Patent 8,311,524 Bl
`
`At this stage of the proceeding, the Board has not madea final
`
`determination as to the patentability of any chaiienged ciaim or any
`
`underlying factual and legal issues.
`
`IV. ORDER
`
`Accordingly,it is:
`ORDEREDthat, pursuant to 35 U.S.C. § 314(a), an inter partes
`review is hereby instituted as to claims 1, 3-5, 7, and 9 of U.S. Patent No.
`
`8,311,524 B1 based on the groundthat claims 1, 3-5, 7, and 9, under
`
`35 U.S.C. § 103(a), are unpatentable over Miluzzo and Robarts;
`
`FURTHER ORDEREDthatinter partes review commenceson the
`
`entry date ofthis Order, and pursuant to 35 U.S.C. § 314(c) and 37 C.F.R.
`§ 42.4, notice is hereby given of the institution of a trial; and
`FURTHER ORDEREDthatthetrial is limited to the ground of
`
`unpatentability listed above, and no other grounds of unpatentability are
`
`authorized for inter partes review.
`
`PETITIONERS:
`
`Michael V. Messinger
`~ Michelle K. Holoubek
`STERNE, KESSLER, GOLDSTEIN & FOX PLLC
`mikem-PTAB@skgf.com
`mholoubek-PTAB@skgf.com
`
`PATENT OWNER:
`
`Robert E. Purcell
`Jerry Kearns
`THE LAW OFFICE OF ROBERTE. PURCELL, PLLC
`rpurcell@repurcelllaw.com
`
`17
`
`
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