Jaan Leemet et al.

Patent Trials and Appeals Board

Sep 2, 2020

2019005972 (P.T.A.B. Sep. 2, 2020)

UNITED STATES PATENT AND TRADEMARK OFFICE
UNITED STATES DEPARTMENT OF COMMERCE
United States Patent and Trademark Office
Address: COMMISSIONER FOR PATENTS
P.O. Box 1450
Alexandria, Virginia 22313-1450
www.uspto.gov
APPLICATION NO. FILING DATE FIRST NAMED INVENTOR ATTORNEY DOCKET NO. CONFIRMATION NO.
14/263,772 04/28/2014 Jaan Leemet 03752-P0081A 1723
24126 7590 09/02/2020
ST. ONGE STEWARD JOHNSTON & REENS, LLC
986 BEDFORD STREET
STAMFORD, CT 06905-5619
EXAMINER
FAN, JOHN
ART UNIT PAPER NUMBER
2454
NOTIFICATION DATE DELIVERY MODE
09/02/2020 ELECTRONIC
Please find below and/or attached an Office communication concerning this application or proceeding.
The time period for reply, if any, is set in the attached communication.
Notice of the Office communication was sent electronically on above-indicated "Notification Date" to the
following e-mail address(es):
patentpto@ssjr.com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
________________

BEFORE THE PATENT TRIAL AND APPEAL BOARD
________________

Ex parte JAAN LEEMET, PAUL SCHMIDT, ALBERT R. SUBBLOIE,
and CHRISTOPHER J. DEBENEDICTIS
________________

Appeal 2019-005972
Application 14/263,772
Technology Center 2400
________________

Before JOHN A. EVANS, JAMES W. DEJMEK, and
RUSSELL E. CASS, Administrative Patent Judges.

CASS, Administrative Patent Judge.

DECISION ON APPEAL
Appellant1 appeals under 35 U.S.C. § 134(a) from the Examiner’s
final rejection of claims 1–9, 11–31, and 33–39 under 35 U.S.C. § 103.
Appeal Br. 1.2 Claims 10 and 32 have been cancelled. Id. We have
jurisdiction under 35 U.S.C. § 6(b).
We reverse.

1 We use the word “Appellant” to refer to “applicant” as defined in 37 C.F.R.
§ 1.42. Appellant lists Tangoe US, Inc. as the real party in interest. Appeal
Brief filed January 4, 2019 (“Appeal Br.”) 2.
2 Rather than repeat the Examiner’s positions and Appellant’s arguments in
their entirety, we refer to the above mentioned Appeal Brief, as well as the
following documents for their respective details: the Final Action mailed
December 20, 2017 (“Final Act.”); the Claims Appendix submitted with the
Response to Non-Complaint Appeal Brief dated February 14, 2019 (“Claims
App.”); the Examiner’s Answer mailed June 6, 2019 (“Ans.”); and the Reply
Brief filed August 6, 2019 (“Reply Br.”).
Appeal 2019-005972
Application 14/263,772
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BACKGROUND
The present invention relates to a system and method that allows
information related to data and communication resource usage to be
gathered and analyzed such that particular data transactions can be classified
based on purpose and/or type. Abstr. The system and method also provide
reporting based on amount and type of usage, so that associated costs can be
calculated and allocated to particular accounts, divisions, groups, or
individuals within and outside of a company or entity. Id.
Appellant’s Specification states that companies face a problem in that,
unlike in a mailroom where each transaction can be monitored and cost
allocated accordingly, data transactions cannot currently be effectively
monitored. Id. ¶ 13. According to Appellant, most of the existing reporting
systems for data use offer metrics limited to simple aggregate amounts of
data used over time, which does not provide detailed usage events with data
transactions for the allocation of costs or the running of reports. Id.
Additionally, the use of applications such as Facebook, Skype, and other
messaging or communication applications, reduce visibility to the user’s
activities as compared to traditional voice services and SMS (Short Message
Service). Id. ¶ 14.
Appellant’s invention seeks to overcome this problem by using
software to collect and analyze how much “data per application,” or “data
per destination,” or “data per application transaction type (i.e. each email
size/avg size/destination etc)” is used, as opposed to the simple total “data
used” format. Id. ¶ 26. This would include, for example, capturing
application-specific units of measure, tweets, posts, likes, and so on. Id.
From this information, costs can be allocated to the particular data
transaction based on the cost system set up by the company. Id. ¶ 27.
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Claim 1 is illustrative of the claims at issue:
1. A system for monitoring data usage of a device and
generating a report relating to the data usage of the device, the
system comprising:
a server connected to a network;
a storage accessible by said server;
software executing on said server for receiving a data
stream relating to data used by the device;
said software extracting a data packet from the data stream;
said software analyzing the data packet to extract a first
address selected from a source address or a destination address
or a Universal Resource Locator (URL) to generate formatted
usage data;
said software matching the formatted usage data to known
data to generate a data transaction, wherein the known data is
related to a pattern of data usage correlated with an active
application running on the device that is associated with the
first address and the data transaction associates data usage with
an activity-based category of usage within the active
application;
said software allocating a cost for the data transaction; and
said software generating a cost report based on the cost for
the data transaction;
said system further comprising software executing on the
device to monitor usage characteristics of a Central Processing
Unit (CPU) of the device and correlating the monitored usage
characteristics with active applications running on the device.
Claims App. 2.

Appeal 2019-005972
Application 14/263,772
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THE EXAMINER’S REJECTIONS
The prior art relied upon by the Examiner is set forth in the following
table:
Name Reference Date
Talley US 2007/0081471 A1 Apr. 12, 2007
Raleigh2 US 2012/0087319 A1 Apr. 12, 2012
Raleigh1 US 2012/0215911 A1 Aug. 23, 2012
Final Act. 4–28.
In the Final Office Action, the Examiner rejected claims 1–9, 11–28,
37, and 38 under 35 U.S.C. § 103 as being unpatentable over Raleigh1 in
view of Raleigh2 and Talley. Final Act. 4–22. The Examiner also rejected
claims 29–31, 33–36, and 39 under 35 U.S.C. § 103 as being unpatentable
over Raleigh1 in view of Raleigh2. Id. at 22–28.
The Examiner determined, inter alia, that Raleigh1 teaches,
said software matching the formatted usage data to known data
to generate a data transaction, wherein the known data is related
to a pattern of data usage correlated with an active application
running on the device that is associated with the first address
and the data transaction associates data usage with an activity-
based category of usage within the active application.
Final Act. 5–6; Ans. 6–13. Appellant disputes the obviousness rejections,
arguing that Raleigh1 only discloses the ability to determine network usage
by application, but not an activity based-category of usage within a
particular active application. Appeal Br. 6–12; Reply Br. 2–8.

ANALYSIS
The central issue on this appeal is whether the cited prior art teaches,
inter alia,
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said software matching the formatted usage data to known data
to generate a data transaction, wherein the known data is related
to a pattern of data usage correlated with an active application
running on the device that is associated with the first address
and the data transaction associates data usage with an activity-
based category of usage within the active application,
as required by claim 1 (emphasis added).
The Examiner relies on Raleigh1 for this limitation, pointing
specifically to paragraphs 77, 80, 82, 176, 201, 211, 258, 289, 290, 339, and
Figure 23. First, the Examiner states that “categories of usage” are disclosed
in the portions of paragraphs 211 and 258 reproduced below:
[T]he service processor determines application/service usage
activity demand with or without granular application service
usage activity (e.g., depending on various user/service
plan/service provider/network/legal and/or other privacy
restrictions and/or any other related requirements or settings).
[¶ 211]
[V]arious applications, OS functions, and/or other utilities/tools
installed/loaded onto and/or launched executing/active on a
communications device (e.g., device 100) are classified as
network capacity controlled services for protecting network
capacity. [¶ 258]
Ans. 7–8. Based on the above, the Examiner finds that Raleigh1 provides an
“indication that the ‘network services activities’ are a category of usage
within the application.” Id. at 8.
The Examiner further relies on Figure 23 of Raleigh1, reproduced
below, as teaching the ability to determine particular categories of usage
within an application, such as Facebook, Outlook, or Skype. Id. at 8–10.
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Figure 23 of Raleigh1 shows priority levels assigned to various network
capacity controlled services (including Outlook, Skype, FaceBook, etc.)
based on the network busy state (NBS) level, which indicates what
percentage of the network capacity is being utilized. Raleigh1, Fig. 23,
¶¶ 258–259.
Next, the Examiner points to the following portions of paragraphs
176, 201, and 339 of Raleigh1 to disclose an activity based category of
usage within the active application:
[D]evices 100 can communicate via the central provider access
and core networks 220 to the Internet 120 for access to various
Internet sites/services 240 (e.g., Google sites/service, Yahoo
sites/service, Blackberry services, Apple iTunes and Apple
Store, Amazon.com, FaceBook and/or any other Internet
service or other network facilitated service). [¶ 176]
[C]lassifying or categorizing service usage activities to
associate various monitored activities (e.g., by URL, by
network domain, by website, by network traffic type, by
application or application type, and/or any other service usage
activity categorization classification) . . . are provided. [¶ 201]
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Classification rules can include, for example, examining if one
or more of the following has taken place within a specified
period of time: user has interacted with the service usage
activity, user has picked up the device, service usage activity UI
content is in the foreground of the device UI, audio or video
information is being played by the service usage activity, a
certain amount of data has been communicated by the service
usage activity. [¶ 339]
Ans. 9–10, 10–11.
Finally, the Examiner relies on the following portions of paragraphs
289 and 290 of Raleigh1 to disclose the ability to determine particular
categories of usage within the active application:
[C]lassifying the network service usage activity further includes
classifying the network service usage activity . . . into one or
more of a plurality of classification categories for differential
network access control for protecting network capacity. [289]
[C]lassifying the network service usage activity based on one
or more of the following: application or widget (e.g., Outlook,
Skype, iTunes, Android email, weather channel weather widget,
iCal, Firefox Browser, etc.). [290]
Id. at 10, 12–13.
Appellant argues, inter alia, that Raleigh1 teaches the use of “service
usage monitors” that act as an agent “which is installed on the device to
identify which applications are using the network service” and “merely map
network usage to the application.” Reply Br. 2 (citing Raleigh1 ¶¶ 215,
250). According to Appellant, this does not involve “said software matching
the formatted usage data to known data to generate a data transaction,
wherein the known data is related to a pattern of data usage correlated with
an active application running on the device,” or “associat[ing] data usage
with an activity-based category of usage within the active application,” as
claimed. Id. Instead, Appellant asserts, “Raleigh’s ‘agent’ or ‘usage
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monitor’ simply knows usage that relates to the application by virtue of
which application data is flowing to in a given instance,” without “the ability
to go to the next step and determine what the user is actually doing with the
active application with that data usage.” Id. at 2–3; Appeal Br. 8–10.
“Thus,” Appellant argues, “[w]hile Raleigh 1 may disclose mapping usage
to applications which initiated usage, there is no indication that Raleigh can
associate a ‘category of usage within the active application’ with a data
transaction.” Appeal Br. 11.
We agree with Appellant that Raleigh1 does not disclose “matching
the formatted usage data to known data to generate a data transaction,
wherein the known data is related to a pattern of data usage correlated with
an active application” and that “the data transaction associates data usage
with an activity-based category of usage within the active application.”
Although the Examiner has pointed to portions of Raleigh1 showing that
Raleigh can map usage to particular applications, the Examiner has not
sufficiently shown that Raleigh1 associates that usage with an “activity-
based category of usage” within an application.
More specifically, paragraphs 211 and 258 of Raleigh1, relied on by
the Examiner, disclose that the service processer determines “service usage
activity demand with or without granular application/service usage activity”
and that “various applications . . . are classified as network capacity
controlled services for protecting network capacity,” but the Examiner fails
to sufficiently show these disclosures teach associating data usage with “an
activity based category of usage within the active application.” Raleigh1
¶¶ 211, 258. Figure 23, also relied upon by the Examiner, shows that the
system can determine that data is being used by particular applications (such
as Outlook, Skype, Facebook, etc.), but the Examiner again fails to show
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how these paragraphs disclose associating data usage with “activity-based
categories of usage” within these applications. Id. Fig. 23. As to Raleigh1
paragraphs 176, 201, and 339, the Examiner similarly fails to show how they
teach associating data usage with an “activity-based category of usage,”
because the Examiner fails to show how the system can determine what the
user is doing on an application being used, such as Facebook, or iTunes. Id.
¶¶ 176, 201, 339. Paragraphs 289 and 290 also describe usage by
application, and the Examiner again does not show how they determine and
distinguish between different activity-based categories of usage within a
particular application. Id. ¶¶ 289, 290.
Thus, we find that the Examiner has failed to show that Raleigh1
discloses
said software matching the formatted usage data to known data
to generate a data transaction, wherein the known data is related
to a pattern of data usage correlated with an active application
running on the device that is associated with the first address
and the data transaction associates data usage with an activity-
based category of usage within the active application.
The Examiner also does not rely on any other prior art for this limitation.
Accordingly, we reverse the Section 103 rejection of claim 1, as well as the
rejection of independent claims 20 and 29, which include similar limitations.
We also reverse the rejection of claims 2–9, 11–19, 21–28, 30–31, and 33–
39, which are dependent on claims 1, 20, or 29.
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Application 14/263,772
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CONCLUSION
We reverse the Examiner’s rejection of claims 1–9, 11–31, and 33–39.
In summary:

Claims
Rejected
35 U.S.C.
§
Reference(s)/Basis Affirmed Reversed
1–9, 11–28,
37, 38
103 Raleigh1,
Raleigh2, Talley
1–9, 11–28,
37, 38
29–31, 33–
36, 39
103 Raleigh1, Raleigh2 29–31, 33–
36, 39
Overall
Outcome
1–9, 11–31,
33–39

REVERSED