Ex Parte Paul et al

Patent Trial and Appeal Board

Oct 29, 2018

13451938 (P.T.A.B. Oct. 29, 2018)

UNITED STA TES p A TENT AND TRADEMARK OFFICE
APPLICATION NO. FILING DATE FIRST NAMED INVENTOR
13/451,938 04/20/2012 Peter Paul
144569 7590 10/31/2018
MH2 TECHNOLOGY LAW GROUP, LLP (w/CONDUENT)
TIMOTHY M. HSIEH
1951 KIDWELL DRIVE
SUITE 310
TYSONS CORNER, VA 22182
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
ATTORNEY DOCKET NO. CONFIRMATION NO.
2011 l 101US01/0290.0346 8944
EXAMINER
NGUYEN, NGA B
ART UNIT PAPER NUMBER
3683
NOTIFICATION DATE DELIVERY MODE
10/31/2018 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):
conduent. PatentDocketing@conduent.com
doreen@mh2law.com
docketing@mh2law.com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
BEFORE THE PATENT TRIAL AND APPEAL BOARD
Ex parte PETER PAUL, AARON MICHAEL BURRY, and
JOEL EAGLE
Appeal2017-008696
Application 13/451,938
Technology Center 3600
Before CARL W. WHITEHEAD JR., JEREMY J. CURCURI, and
MICHAEL J. ENGLE, Administrative Patent Judges.
CURCURI, Administrative Patent Judge.
DECISION ON APPEAL
Appellants appeal under 35 U.S.C. § 134(a) from the Examiner's
rejection of claim 17. Final Act. 1. We have jurisdiction under 35 U.S.C.
§ 6(b).
Claim 17 is rejected under 35 U.S.C. § 101 as being directed to a
judicial exception without significantly more. Final Act. 2-5.
Claim 17 is rejected under pre-AIA 35 U.S.C. § 103(a) as obvious
over Fitzpatrick (US 2006/0218057 Al; Sept. 28, 2006), Agrawal (US
2009/0309974 Al; Dec. 17, 2009), and Newman (US 2012/0116252; May
10, 2012). Final Act. 6-17.
We affirm.
Appeal2017-008696
Application 13/451,938
STATEMENT OF THE CASE
Appellants' invention relates to
platforms and techniques for estimating the number of occupants
in a vehicle entering a fast food restaurant or other retail site, and
using that number as an input to a production management
engine for the retail site to adjust the food preparation or other
production of the retail site to more closely match the
instantaneous demand of the actual number of onsite customers.
Spec. ,r 1. Claim 1 7 is illustrative and reproduced below:
1 7. A production management system for a retail site using
multiple sensor types, comprising:
at least one acoustic sensor positioned to monitor an access area of the
retail site, the at least one acoustic sensor configured to operate in realtime;
at least one thermal sensor positioned to monitor an access area of the
retail site, the at least one thermal sensor configured to operate in realtime;
at least one optical sensor positioned to monitor an access area of the
retail site, the at least one optical sensor configured to operate in realtime;
an interface to the at least one acoustic sensor, the at least one thermal
sensor, and the at least one optical sensor to detect occupants of a vehicle in
realtime; and
a processor, communicating with the set of sensors via the interface,
the processor being configured to-
monitor an access area to an ordering point of the retail site via
the at least one acoustic sensor, the at least one thermal sensor, and the at
least one optical sensor, wherein the retail site comprises a restaurant,
wherein the access area comprises at least one of an access roadway or a
parking area,
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identify the presence of a vehicle entering the access area of the
retail site,
detect a number of occupants of the vehicle using optical
imaging, thermal imaging using the at least one thermal sensor, and acoustic
detection of voices using the at least one acoustic sensor, wherein the optical
imaging comprises applying a seat detection algorithm to an optical image
detected using the at least one optical sensor, and wherein the optical
imaging further comprises applying a face recognition algorithm to the
detected optical image, wherein the optical imaging further comprises the
use of an infrared strobe,
receive the detected number of occupants,
receive order information from at least one occupant of the
vehicle at the ordering point,
access a model of the retail site to operate the production
management engine, wherein the model is based on historical customer
order data,
generate a set of dynamically generated production instructions,
to manage a production process of the retail site based on the detected
number of occupants, wherein the set of dynamically generated production
instructions comprises a specification of a quantity of at least one food item,
wherein the set of dynamically generated production instructions comprises
a specification of a start time for the processing of at least one food item,
wherein the processor is further configured to generate an estimated queue
delay for an order received from at least one occupant of the vehicle,
wherein the processor is further configured to generate an estimated
freshness rating for the at least one food item,
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Application 13/451,938
update in realtime the quantity of at least one food item to
reflect the order information, and
update the model based on the order information.
PRINCIPLES OF LAW
We review the appealed rejections for error based upon the issues
identified by Appellants, and in light of the arguments and evidence
produced thereon. Ex parte Frye, 94 USPQ2d 1072, 1075 (BPAI 2010)
(precedential).
ANALYSIS
THE 35 U.S.C. § 101 REJECTION OF CLAIM 17
Contentions
The Examiner concludes claim 1 7 is directed to an abstract idea
without significantly more. Final Act. 2-5. In particular, the Examiner
concludes the claimed subject matter
can be performed mentally or in a computer and is similar to the
kind of 'organizing human activity' and is an idea of itself. It is
similar to other concepts that have been identified as abstract by
the courts, such as using categories to organize, store and
transmit information in Cyberfone, or computerized meal
planning in Dietgoal Innovations LLC, or scanning and
information processing methodology in Content Extraction and
Transmission LLC.
Final Act. 3; see also Ans. 18-19.
Appellants present the following principal arguments:
1. "[C]laim 1 at issue in Cyberfone merely recites receiving
information, breaking up the information, and transmitting the information."
App. Br. 10. "The Cyberfone claims do not recite interactions with the
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physical world, such as those recited in present claim 17 ." App. Br. 11. "The
Content Extraction claims are directed to receiving, manipulating, and
storing data only." App. Br. 11. "This is markedly different from the present
claims, which provide a technique that includes multiple interactions with
real-world things outside of any computer." App. Br. 11. "[C]laim 17 is not,
in fact, directed to a method of organizing human activity. Rather, claim 17
is directed to improving a production process, which is in the field of
manufacturing." App. Br. 12; see also Reply Br. 3 ("The recitation of
particular sensors in the claims, together with the other claim features,
improves the functionality of a food production management system for a
retail site.").
11. "The claim at issue in Dietgoal is remarkably short and
broad in comparison to the present claims." App. Br. 13. "[T]he only
identified additional elements on the Dietgoal case are software per se."
App. Br. 14.
In sum, none of the Office's examples of generic
computers include thermal, optical, and acoustic sensors, and
none of the Office's examples of generic computer functions
include monitoring a physical access area, identifying the
presence of a vehicle, detecting vehicle occupants, or even
receiving order information, as claimed. In fact, a generic
computer is incapable of capturing the claimed information and
performing the claimed functions, because generic computers are
not equipped with the claimed acoustic, thermal, and optical
sensors configured to monitor access areas, identify the presence
of a vehicle, detect a number of occupants of the vehicle, and
receive order information from at least one occupant of the
vehicle, as claimed.
App. Br. 14.
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Our Review
In Alice Corp. v. CLS Bank Int 'l, 134 S. Ct. 2347 (2014), the Supreme
Court applied the framework as set forth in Mayo Collaborative Servs. v.
Prometheus Labs., Inc., 566 US 66 (2012) for determining whether the
claims are directed to patent-eligible subject matter. Alice, 134 S. Ct. at
2355. The first step in the analysis is to "determine whether the claims at
issue are directed to one of [the judicially-recognized] patent-ineligible
concepts." Id. If the claims are directed to a patent-ineligible concept, then
the second step in the analysis is to consider the elements of the claims
"individually and 'as an ordered combination' to determine whether the
additional elements 'transform the nature of the claim' into a patent-eligible
application." Id. (quoting Mayo, 566 US 66 at 79, 78). However, the Federal
Circuit has articulated that "the first step in the Alice inquiry ... asks
whether the focus of the claims is on the specific asserted improvement in
computer capabilities ... or, instead, on a process that qualifies as an
'abstract idea' for which computers are invoked merely as a tool." Enfish,
LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36 (Fed. Cir. 2016).
Accordingly, the Federal Circuit determined, if "the claims are directed to a
specific implementation of a solution to a problem in the software arts," then
"the claims at issue are not directed to an abstract idea." Id. at 1339. The
Federal Circuit also determined claims directed to "limited rules in a process
specifically designed to achieve an improved technological result in
conventional industry practice" are not directed to an abstract idea. McRO,
Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1316 (Fed. Cir.
2016).
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In the "Background" section, Appellants' Specification discloses the
following:
Moreover, even when restaurant managers or others
attempt to manage the production process of the restaurant by
estimating or manually counting the number of vehicles entering
an ordering lane or parking for occupants to enter the front
counter of the establishment, the number of vehicles serves, at
best, as a rough indicator of the number of potential customers
and therefore, anticipated orders for the restaurant. This can be
due to the fact that the actual number of persons in some vehicles,
including those with a large capacity, can vary widely depending
on how fully that vehicle is loaded. The actual occupancy of the
vehicle may however remain unclear to the manager or others
attempting to get a "head count" of customers based strictly on
the identified number of vehicles approaching the establishment.
Spec ,r 4 ( emphasis added).
In the "Description of Embodiments" section, Appellants'
Specification discloses the following:
Embodiments of the present teachings relate to systems
and methods for realtime occupancy detection of vehicles
approaching a retail site for predictive ordering. More
particularly, embodiments relate to platforms and techniques for
monitoring vehicle traffic approaching a restaurant and/or other
retail site, and generating an estimate of the number of occupants
of the vehicle. That estimated number of occupants can be
transmitted to an operational model of the retail site, such as a
model generated or accessed by a production management
engine which generates operating instructions such as the type of
food items to prepare, the quantity of those items to prepare,
when to begin the cooking or other preparation of those items,
and other production details. Because in part the retail site can
tie up-to-the-minute production instructions or details to a fairly
accurate or granular estimate of the number of vehicle
occupants, the efficiency of the retail operation can be improved.
In the case for instance of a fast-food restaurant, food can be
delivered to a customer in a drive-through line or other access
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area which is fresher, and delivered on time to the customer as
they arrive at the dispensing window or other pickup point,
enhancing the customers' experience while reducing waste for
the retail operator. Other advantages can also be achieved.
Spec. ,r 12 (emphasis added).
We agree with Appellants that claim 17 is directed to an improved
production process, and we conclude the claims focus on a specific
improvement in computer-related technology and are analogous to McRO. In
McRO, the court found that a claim reciting a system of automated facial
animation through the use of rules, rather than by artists setting weights, to
automate tasks that humans perform is directed to patent-eligible subject
matter. McRO, 837 F.3d at 1313. The court found that the process performed
by human animators is not the same as the rules-based process recited in the
claimed automation, as the human process is driven by subjective
determinations. McRO, 837 F.3d at 1314. Thus, the court in McRO held that
it was the incorporation of the specific features of the particular rules as
claim limitations that improved the technological process, and by
incorporating the specific rules, the claim is limited to a specific process for
animation that is not an abstract idea. McRO, 837 F.3d at 1315-16.
We conclude the instant claim limitations are similar to the claim
limitations at issue in McRO. The claims do not merely attempt to get a
"head count" of customers based strictly on the identified number of
vehicles approaching the establishment; rather, the claim limitations recite a
specific technique that detects a number of occupants of the vehicle and
improves the efficiency of the retail operation. Spec. ,r,r 4, 12; Claim 17. As
such, the claim limitations are directed to improving a technological process.
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Accordingly, we do not sustain the Examiner's rejection of independent
claim 17.
THE OBVIOUSNESS REJECTION OF CLAIM 17
Contentions
The Examiner finds Fitzpatrick, Agrawal, and Newman teach all
limitations of claim 17. Final Act. 6-17.
In particular, the Examiner finds Fitzpatrick teaches "the set of
dynamically generated production instructions comprises a specification of a
start time for the processing of at least one food item" as recited in claim 1 7.
Final Act. 12 (citing Fitzpatrick ,r 87); see also Ans. 19--20 (citing
Fitzpatrick ,r,r 199, 207).
In particular, the Examiner finds Fitzpatrick teaches to "update in
realtime the quantity of at least one food item to reflect the order
information" as recited in claim 17. Final Act. 13 ( citing Fitzpatrick ,r 228);
see also Ans. 20-22 ( citing Fitzpatrick ,r,r 202, 204 ).
In particular, the Examiner finds Agrawal teaches to "detect a number
of occupants of the vehicle using optical imaging" as recited in claim 1 7,
and further teaches "wherein the optical imaging comprises applying a seat
detection algorithm to an optical image detected using the at least one
optical sensor" as recited in claim 17. Final Act. 13-14. The Examiner
reasons
it would have been obvious to one with ordinary skill in the art
at the time the invention was made to modify the Fitzpatrick
[ system and method] to incorporate the teaching of Agrawal, for
the purpose of detecting the number of occupants of the vehicle,
wherein the detecting comprises detecting the number of
occupants using optical imaging, and wherein the optical
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imaging comprises applying a seat detection algorithm to a
detected optical image, in order to provide more accuracy in
detecting the number of occupants within the vehicle. Because
Fitzpatrick discloses detecting number of customers using a
plurality of different sensors (paragraphs [0065]-[0068],
Customer arrival measurement may be performed with any of a
number of sensors 22 including mechanical, electrical, and
chemical sensors), Agrawal discloses using optical sensor to
detect number of occupants of the vehicle by applying a seat
detection algorithm to an optical image, therefore, one of
ordinary skill in the art would have recognized that the
combination of Fitzpatrick and A[gr ]awal [ would] yield
predictable results for detecting the occupants of the vehicle.
Final Act. 14--15; see also Ans. 22-23 ("Agrawal is relied on only for the
teaching of the way [for] counting the occupants of the vehicle which
Fitzpatrick already discloses the number of people by counting 'emerging
from the cars' (paragraph [0090]). By adopting the teaching of the counting
the occupants of the vehicle as disclosed by Agrawal, the advantage will be
for counting people of a vehicle using drive through.").
In particular, the Examiner finds
Fitzpatrick does not disclose wherein the model is based on
historical customer order data. However, Fitzpatrick discloses
that the related prior arts applying the model based on historical
customer order data (paragraph [0008], The restaurant
industry's state-of.-the art solutions are based on data-mining
historical sales information to predict future ordering patterns.
Each restaurant typically saves a multi-week history of its sales
volumes for each product. For example, sales data of the past 70
days may be stored and analyzed).
Final Act. 16. The Examiner reasons
it would have been obvious to one with ordinary skill in the art
at the time the invention was made to modify the Fitzpatrick
[ system and method] to incorporate the teaching of the related
prior arts disclosed by Fitzpatrick, for the purpose of applying
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Fitzpatrick's model based on historical customer order data, in
order to provide more efficiency in predicting future ordering
patterns to improve performance of the restaurant.
Final Act. 16 (citing Fitzpatrick ,r 83); see also Ans. 23-25 (finding
Fitzpatrick does not teach away from using historical order data).
Appellants present the following principal arguments:
1. Fitzpatrick does not teach "the set of dynamically generated
production instructions comprises a specification of a start time for the
processing of at least one food item" as recited in claim 1 7 because
"Fitzpatrick at most discloses that sensors detecting a car ( or person) at a
particular location is a trigger for the kitchen to take action before the
customer places the order." App. Br. 15; see also Reply Br. 3--4 ("[T]his
disclosure has nothing to do with any 'dynamically generated production
instructions' generated by a programmed processor.").
11. Fitzpatrick does not teach "update in realtime the quantity of at
least one food item to reflect the order information" as recited in claim 1 7.
See App. Br. 15-18. For example, Appellants argue
The Office's interpretation of "quantity" as a database
representation of a number of food items in Fitzpatrick's physical
food buffers is not a proper reading of this term. This is because
the quantity of food items in Fitzpatrick's food buffers is not the
same as the quantity of food items specified in production
instructions, which is required by the antecedent basis for the
term "quantity" in claim 17. Specifically, Fitzpatrick's buffer
state database represents food items present in Fitzpatrick's
physical buffers (see Fitzpatrick, paragraph 58) as reported by
Fitzpatrick's kitchen employees (see Fitzpatrick, paragraph 228).
A "quantity of at least one food item" as specified in production
instructions according to claim 17 does not properly read on
Fitzpatrick's database representation of food items in its physical
food storage buffer. Thus, the Office's interpretation of "the
quantity" is improper even under a broadest-reasonable-
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interpretation standard, and the rejection should be therefore
reversed.
App. Br. 17; see also Reply Br. 4--5 ("A bound on a quantity does not meet
claim language that requires updating the quantity.").
111. Agrawal is not analogous art because "[ o ]ne of ordinary skill in
the art of restaurant production management would not look to a law
enforcement technique." App. Br. 18.
1v. Agrawal teaches away from the facial recognition disclosed by
Fitzpatrick because "Agrawal cautions against using facial recognition
techniques." App. Br. 19 (citing Agrawal ,r 18).
v. Fitzpatrick teaches away from using historical order data. App.
Br. 19--21. "Fitzpatrick teaches that using historic information reduces speed
and quality because it does not allow restaurant managers to know with
confidence the demand that the restaurant will be in the near future." App.
Br. 19 ( citing Fitzpatrick ,r 11 ). "Fitzpatrick again differentiates and
distinguishes its 'buffer manager' technique from techniques such as the
claimed technique that use historical customer order data." App. Br. 20.
"Fitzpatrick distinguishes and disparages techniques that use historical
customer order data from Fitzpatrick's own technique." App. Br. 20; see
also Reply Br. 5-6
Our Review
We do not see any error in the contested findings of the Examiner. We
concur with the Examiner's conclusion of obviousness.
Regarding Appellants' argument (i), Fitzpatrick discloses "[s]ensor
placement is a function of the restaurant's performance-higher
performance restaurants do not require as much warning time to react to
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changes in consumer demand." Fitzpatrick ,r 87. We agree with Appellants
that this disclosure discloses a trigger for the kitchen to take action. But
contrary to Appellants, we find such disclosure teaches "the set of
dynamically generated production instructions comprises a specification of a
start time for the processing of at least one food item" as recited in claim 1 7
because such a trigger specifies the start time as the current time at which
the triggering occurs. See Final Act. 12. In addition, Fitzpatrick discloses
"[t]he computer 20 may use queue simulation to make a series of production
decisions in real time." Fitzpatrick ,r 199. In addition, Fitzpatrick further
discloses "it may be desirable to estimate the remaining time for a bin of
food product components so as to decide when to begin cooking another bin
of food product components." Fitzpatrick ,r 207. These disclosures in
Fitzpatrick further teach "the set of dynamically generated production
instructions comprises a specification of a start time for the processing of at
least one food item" as recited in claim 17 because Fitzpatrick's computer
makes production decisions, and decides when to begin cooking food
product components. See Ans. 19--20 (citing Fitzpatrick ,r,r 199, 207).
Regarding Appellants' argument (ii), Fitzpatrick discloses "the
computer 20 of buffer manager 18 according to the present invention
determines the nominal buffer level using a patty count instead of a bin
count." Fitzpatrick ,r 202. Fitzpatrick further discloses "[e]stimation of
desired nominal component buffer level may bound production by the total
number of unplaced orders on the restaurant property." Fitzpatrick ,r 204.
Contrary to Appellants' arguments, these disclosures teach "update in
realtime the quantity of at least one food item to reflect the order
information" as recited in claim 17 because as orders are placed, the bound
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on the buffer level changes, thereby reflecting the order information,
particularly when the bound is actively restricting the buffer level.
Regarding Appellants' arguments (iii) and (iv), the particular problem
with which Appellants are concerned is "estimating the number of
occupants in a vehicle." Spec. ,r 1. Although the application of Appellants'
invention is in a retail site for predictive ordering, the particular problem
faced is estimating the number of occupants in the vehicle. See Spec. ,r 1.
Agrawal is reasonably pertinent to this problem. See Agrawal Abstract
( emphasis added) ("an automated detection system consisting of a combined
visible and Short Wave Infra-Red (SWIR) camera that identifies vehicle
identification number and the number of occupants in a given vehicle").
Thus, Agrawal is analogous art.
While an alternative may be inferior to or less desirable than another,
that alone is insufficient to teach away from the inferior alternative unless
the disclosure criticizes, discredits, or otherwise discourages that alternative.
In re Fulton, 391 F.3d 1195, 1200--01 (Fed. Cir. 2004). Here, to the extent
Agrawal cautions against using facial recognition due to privacy concerns, a
mere lack of justification for facial recognition does not criticize, discredit,
or otherwise discourage the use of facial recognition. See Agrawal ,r 18
("detailed image recognition is not warranted for privacy concerns.").
Finally, the Examiner provides a reason to combine the references that
is rational on its face and supported by evidence drawn from the record. See
Final Act. 14--15 (citing Fitzpatrick ,r,r 65---68); see also Ans. 22-23 (citing
Fitzpatrick ,r 90). Appellants have not presented any additional
particularized arguments as to why this reasoning is incorrect. Accordingly,
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Appellants' arguments (iii) and (iv) do not show any error in the Examiner's
findings and reasons in support of the conclusion of obviousness.
Regarding Appellants' argument (v), Fitzpatrick discloses "this
method of estimating desired nominal component buffer level according to
the present invention may drive production in proportion to current
demand. Subsequent methods may work to improve the convergence of this
method's demand-curve following performance." Fitzpatrick ,r 204
(emphasis added). To the extent certain portions of Fitzpatrick describe the
invention as an improvement over prior art techniques that use only
historical customer data, Fitzpatrick's own technique suggests considering
current demand, and additionally considering historical order information.
See Fitzpatrick ,r 204. Put another way, by "work[ing] to improve the
convergence," Fitzpatrick suggests that subsequent methods consider
historical as well as current demand. Fitzpatrick ,r 204.
Accordingly, we sustain the Examiner's rejection of independent
claim 17.
ORDER
Because we have sustained one ground of rejection for claim 17, the
Examiner's decision rejecting claim 17 is affirmed.
No time period for taking any subsequent action in connection with
this appeal maybe extended under 37 C.F.R. § 1.136(a)(l)(iv).
AFFIRMED
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