DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Application
The following is a Final Office Action. In response to Examiner's communication on 05/01/2025, Applicant on 07/30/2025, amended Claim 1-3, 5-6, 10-11, 13, 16-18, and 20. Claims 1-20 are now pending in this application and have been rejected below.
Response to Amendment
Applicants’ amendments are insufficient to overcome the 35 USC 101 rejections set forth in the previous action. The rejections are maintained below.
Applicants’ amendments render moot the 35 USC 103 rejections set forth in the previous action in view of new and updated grounds for rejection necessitated by Applicants’ amendments. Therefore, these rejections are withdrawn in view of the new grounds for rejection necessitated by Applicants’ amendments, as set forth below.
Response to Arguments – 35 USC § 101
Applicant's arguments with respect to the 35 USC 101 rejections have been fully considered but they are not persuasive.
Applicant firstly argues that the recited operations cannot be said to be wholly performable in the scope of the human mind, specifically pointing to “analyzing the photographed image” as something that inherently requires computer-implemented image analysis. Examiner respectfully disagrees.
Both the language of the claims and the relevant parts of Applicant’s specification, citing Page 5 Lines 11-26, fail to recite “analyzing the photographed image” in a manner that cannot be performed by a human mentally. There is no mention of interacting with image metadata or other forms of analysis that would necessitate a computer system – while not specified in Applicant’s claims or specification, it is implied that the computer system maintains these times by regularly reviewing photographed images to maintain a timeline of different events; analogously, a human could mentally keep a record of different action events by reviewing photographed images at regular time intervals, and perform a mental judgement to coordinate actions on the basis of the timeline.
Applicant subsequently argues that additional elements serve to provide “significantly more” by providing a clear improvement. Examiner respectfully disagrees. Note that per MPEP 2106.05(a), "an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology." While there may be a benefit to Applicant’s method, what is improved is not the underlying technology – modelling events with machine learning is a well-established, generic technique, similar to the generic usage of photographs to monitor times. Merely applying such generic techniques in a specific context is insufficient to meet the bar for an improvement to technology.
Response to Arguments – 35 USC § 102 and 35 USC § 103
Applicant' s arguments with respect to the rejections under 35 USC 103 have been considered but are moot in light of new grounds of rejections necessitated by applicant’s amendments.
Regarding Applicant’s arguments a)-c), these limitations are taught by the introduced Suzuki reference. Examiner respectfully points to the updated rejections below.
Regarding d) No motivation exists to combine the references to achieve the claimed disclosure. Applicant argues under B. The Proposed Combination Does Not Render the Claimed Invention Obvious that there is no apparent reason to combine references from distinct fields. Examiner respectfully disagrees and notes MPEP 2141.01(a), Analogous and Nonanalogous art, “A reference is analogous art to the claimed invention if: (1) the reference is from the same field of endeavor as the claimed invention (even if it addresses a different problem); or (2) the reference is reasonably pertinent to the problem faced by the inventor (even if it is not in the same field of endeavor as the claimed invention)”. That the fields be disparate need not preclude the combination of the references as cited, as we are able to use the second standard of “reasonable pertinence”. As stated in the original Non-Final Rejection, the shared problem of food storage renders Baca and Watanabe analogous art, with the benefit of the sensor-based analytics of Baca being prevention of food spoilage through granular sensor input. Suzuki’s problem is directly relevant to Watanabe combined with Baca owing to their shared task of managing the display of fried food, with the benefit being intelligently developed cooking schedules.
In response to applicant’s argument that the examiner’s conclusion of obviousness is based upon improper hindsight reasoning, it must be
recognized that any judgment on obviousness is in a sense necessarily a
reconstruction based upon hindsight reasoning. But so long as it takes into account only knowledge which was within the level of ordinary skill at the
time the claimed invention was made, and does not include knowledge
gleaned only from the applicant’s disclosure, such a reconstruction is
proper. See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA
1971).
Claim Rejections - 35 USC § 112(d)
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim 3 is rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. Note that Claim 1 now functionally contains the limitation "estimate the number of products to be cooked for each time zone to include a time zone in which cooking is not performed".. Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
101 Analysis – Step 1
The claims are directed to a method and apparatus. Therefore, the claims are directed to at least one of the four statutory categories.
101 Analysis – Step 2A
Regarding Prong 1 of the Step 2A analysis in the MPEP, the claims are to be analyzed to determine whether they recite subject matter that is directed to a judicial expectation, namely a law of nature, a natural phenomenon, or one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
Independent Claim 1 includes limitations that recite an abstract idea and will henceforth be used as a representative claim for the 101 rejection until otherwise noted. Claim 1 recites:
A product management device comprising: a memory storing instructions; and one or more processors configured to execute the instructions to: acquire a discard time of a product based on a photographed image obtained by photographing the product displayed on a furniture and an expiration date of the product, wherein acquiring the discard time comprises analyzing the photographed image to determine a display time of the product and calculating the discard time based on the display time and the expiration date; predict a sales quantity for each time zone based on a prediction model created using past sales quantity information of the product, wherein the prediction model is a machine learning model generated by learning a correlation between sales quantity and at least one explanatory variable comprising a parameter that affects sales quantity; estimate a number of products to be cooked for each time zone based on the discard time and the sales quantity of the product, wherein the number of products to be cooked is estimated for each time zone in a way that includes a time zone in which cooking is not performed; and output the number of products to be cooked to an output device as an alert.
The examiner submits that the foregoing bolded limitation(s) constitute an abstract idea because under its broadest reasonable interpretation, the claim covers a mental process and certain methods of organizing human activity.
“acquire a discard time of a product…”, “predict a sales quantity…”, “analyzing…to determine a display time of the product and calculating…”, “estimate a number of products…”, “output the number of products to be cooked…” recite abstract ideas - namely, mental processes that could be
performed by a human with a pen and paper, per the MPEP, merely
adapting them into the context of a technological environment with computing parts does not preclude them from being abstract. Further, as the limitations are directed to deciding how many products to cook in accordance with demand projections, they also recite a certain method of organizing human activity, namely under the category of commercial or legal interactions.
Accordingly, the claim recites at least one abstract idea.
Independent Claims 9, 10 recite abstract ideas by virtue of presenting substantially similar limitations.
Claims 2-8 recite abstract ideas by virtue of their dependency on independent Claim 1.
101 Analysis – Step 2A, Prong II
Regarding Prong II of the Step 2A analysis in the MPEP, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into practical application. As noted in the MPEP, it must be determined whether any additional elements in the claim beyond the judicial exception integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements, such as merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”):
A product management device comprising: a memory storing instructions; and one or more processors configured to execute the instructions to: acquire a discard time of a product based on a photographed image obtained by photographing the product displayed on a furniture and an expiration date of the product, wherein acquiring the discard time comprises analyzing the photographed image to determine a display time of the product and calculating the discard time based on the display time and the expiration date; predict a sales quantity for each time zone based on a prediction model created using past sales quantity information of the product, wherein the prediction model is a machine learning model generated by learning a correlation between sales quantity and at least one explanatory variable comprising a parameter that affects sales quantity; estimate a number of products to be cooked for each time zone based on the discard time and the sales quantity of the product, wherein the number of products to be cooked is estimated for each time zone in a way that includes a time zone in which cooking is not performed; and output the number of products to be cooked to an output device as an alert.
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
As it pertains to Claim 1, the additional elements in the claims include “A product management device comprising: a memory storing instructions; and one or more processors configured to execute the instructions to:”, “based on a photographed image obtained by photographing the product displayed on a furniture and an expiration date of the product…”, “wherein the prediction model is a machine learning model…”, “output…to an output device as an alert”. When considered in view of the claim as a whole, the additional elements do not integrate the abstract idea into a practical application because the additional elements are generic computing components that are merely used as a tool to perform the recited abstract idea and/or do no more than generally link the use of the recited abstract idea to a particular technological environment or field of use under Step 2A Prong Two.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitation(s) does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing an abstract idea.
Claim 9 does not integrate the abstract idea into a practical application by virtue of presenting substantially similar limitations as Claim 1.
Claim 10 recites “A non-transitory computer-readable recording medium”, “a program for causing a computer to execute”.
These do not integrate the abstract idea into a practical application by analogous reasoning as above.
Claims 2-8 do not recite additional elements that would serve to integrate the abstract idea into a practical application beyond those found in limitations upon which they are dependent.
101 Analysis – Step 2B
Regarding Step 2B of the MPEP, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to generic computing components that are merely used
as a tool to perform the recited abstract idea and/or do no more than
generally link the use of the recited abstract idea to a particular
technological environment or field of use. Further, looking at the additional
elements as an ordered combination adds nothing that is not already
present when considering the additional elements individually.
Claim 9 is ineligible as presenting substantially similar limitations as Claim 1.
Claim 10 recites “A non-transitory computer-readable recording medium”, “a program for causing a computer to execute”.
These do not integrate the abstract idea into a practical application or amount to significantly more by analogous reasoning as above, and are therefore ineligible.
Claims 2-8 do not recite additional elements that would serve to integrate the abstract idea into a practical application or amount to significantly more, beyond those found in limitations upon which they are dependent, and are therefore ineligible.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-10 are rejected under 35 U.S.C. 103 as being unpatentable over Watanabe(WO2022145218) in view of Baca(US 20180053140 A1) in further view of Suzuki(US2022343239A1).
Claims 1, 9, 10
As to Claim 1,
Watanabe teaches:
A product management device comprising: a memory storing instructions; and one or more processors configured to execute the instructions to:
In [0047], "The fried food display management method according to the embodiment of the present invention is included in this management. The server 56 and the terminal 50 include a computing unit (e.g., a CPU, a RAM, and a ROM) connected to each other as basic hardware elements that an information processing device naturally has. ) and nonvolatile storage devices (e.g., HDD and/or SSD). OS and various application programs (including a program that executes a display management method for fried foods) ) is stored in a nonvolatile storage device of either the server 56 or the terminal 50, or distributed across both".
acquire a discard time of a product…an expiration date of the product, wherein acquiring the discard time comprises … to determine a display time of the product and calculating the discard time based on the display time and the expiration date;
Regarding calculation of a discard deadline based on expiration time in [0010], "...a parameter state recognition unit that recognizes a parameter state as the state of a parameter related to the expiration date of each of the fried foods; a removal deadline determination unit that determines the expiration date of each fried food based on the parameter state recognized by the parameter state recognition unit and determines a removal deadline for each fried food from the display section based on the determined expiration date". The display time factors into the discard time in [0057], “Figure 8 shows the relationship between the degree of deterioration d of the frying oil 41 in the oil tank 40 when the fried food 35 is cooked in the fryer 21, and the remaining time u from the time the fried food 35 is first displayed on the hotter 18 until the expiration date and the remaining time v until the removal deadline”.
predict a sales quantity for each time zone based on a prediction model created using past sales quantity information of the product;
In [0088], "Since the POS data includes information on the sales time and number of each type of fried food 35 up to the current time, it is possible to predict the sales number of each type of fried food 35 from the current time to a certain time in the future based on the POS data. Specifically, for example, correlations between the past sales numbers of fried foods based on past POS data and the sales numbers of each type of fried food 35 with past weather, temperature, humidity, and events (festivals and special events) around the store individually or in combination with two or more of these are analyzed from past statistics and created in advance. Next, at the prediction point in time when the predicted sales volume is to be predicted, the sales volume of each type of fried food 35 from a point in time a predetermined time before the prediction point in time to the prediction point in time is checked from the POS data. Then, based on the investigated sales numbers by type and the correlation created in advance, the sales numbers by type of fried food 35 from the time of prediction to the expiration date of fried food 35 (e.g., = investigated sales numbers by type x correlation value of the correlation created in advance) are predicted".
estimate a number of products to be cooked for each time zone based on the discard time and the sales quantity of the product; and output the number of products to be cooked
In [0088], the mechanics for predicting sales quantities is described. In this context, in accordance with the broadest reasonable interpretation of the claim, it is reasonable to understand the number of products to be cooked as equal to the number of products to be sold.
Watanabe does not expressly disclose the remaining limitations.
However, Baca teaches:
based on a photographed image obtained by photographing the product displayed on a furniture … analyzing the photographed image
In [0012], “In embodiments, the apparatus may use sensors such as three-dimensional depth-based cameras and odor sensors along with predictive analytics with real-time learning into an intelligent food consumption platform, for example for a refrigerator and/or a pantry, to know exactly when certain foods will expire, and what foods may need to be replaced and when”.
Baca discloses a system for using sensors to intelligently provide recommendations on stored food. Watanabe discloses a system meant to manage fried food on display. Each reference discloses means to manage stored food. Extending the camera analytics as recorded in Baca to the system of Watanabe is applicable as both are pertained with providing analytical recommendations to the storage of food.
It would have been obvious to one having ordinary skill in the art at the effective filling date of the invention to apply the sensor analysis as taught in Baca and apply that to the system of Watanabe. Motivation to do so comes from the fact that the claim is plainly directed to the predictable result of combining known items in the prior art, with the expected benefit found in [0012], “Advantages of such an apparatus, or of their associated processes may include less food waste, creative menu planning based on most efficient use of on-hand food items based on their condition, less time wasted going to a grocery store to replace food items, and preventing spoiled food from being consumed”.
Watanabe combined with Baca does not expressly disclose the remaining limitations.
However, Suzuki teaches:
wherein the prediction model is a machine learning model generated by learning a correlation between sales quantity and at least one explanatory variable comprising a parameter that affects sales quantity
In [0139], “In the embodiment, the cooking schedule formulation unit 62 formulates a cooking schedule using attributes of the shop 32, events, etc., as ancillary cooking parameters. In the formulation of a cooking schedule, the relationship between a cooking schedule formulated based on at least one ancillary cooking parameter and maximum future sales in the shop 32 can be searched for by AI, machine learning, deep learning, etc”.
product, wherein the number of products to be cooked is estimated for each time zone in a way that includes a time zone in which cooking is not performed;
We understand the oil replacement process to encompass a period in which cooking is not being performed. In [0103] we have support for managing the cooking schedule such that we factor in periods in which oil is being replaced, "Therefore, it is desirable that the work of replacing the frying oil 17 in the oil tank 15 is completed before a busy period, and that the frying oil 17 is not disposed of too early and is not wasted. As an appropriate measure, for example, when the degree of deterioration of the frying oil 17 in the oil tank 15 is approaching the upper limit, a cooking schedule that is early and generous in allowing for the cooking of the fried foods 19 is formulated so that the frying oil 17 is fully used before being disposed of. It is thereby possible to carry out replacement work before a busy period and conserve the frying oil 17".
and output the number of products to be cooked to an output device as an alert.
In [0113-0114], “In STEP 108, the reporting unit 63 issues a report. The report includes information relating to the disposal time point determined in STEP 104, the cooking schedule formulated in STEP 105, the first display section state set in STEP 106, and the second display section state set in STEP 107. The reporting unit 63 reports the recommended display section state to the shop worker using the display 25, etc. The reporting unit 63 can also instruct the shop worker of the recommended display section state by using voice. See the example alert outputted by the reporting unit and the response by the worker (denoted by fwdarw.) in [0120-0121], “(c3) “Event in neighborhood today, expected sales are: ______ pieces of XX chicken, YY . . . ...fwdarw.Cooks corresponding type of fried foods 19.”
Watanabe combined with Baca discloses a system for managing the display of food. Suzuki discloses a system meant to manage the display and production of fried food. Each reference discloses the management of food on display. Extending the analytical methods as recorded in Suzuki to the system of Watanabe combined with Baca as they are both directed to the same task of fried food on display.
It would have been obvious to one having ordinary skill in the art at the effective filling date of the invention to apply the analytical methods as taught in Suzuki and apply that to the system as taught in Watanabe combined with Baca. Motivation to do so comes from the fact that the claim is plainly directed to the predictable result of combining known items in the prior art, with the expected benefit that adopting such methods would give the end user much greater control in administering the display, with intelligent assistance in factors such as cooking schedules.
Claims 9 and 10 are rejected as disclosing substantially similar limitations as Claim 1.
Claim 10 additionally recites, “A non-transitory computer-readable recording medium that records a program for causing a computer to execute”. This can be found in [0047] of Watanabe.
Claim 2
As to Claim 2, Watanabe combined with Baca and Suzuki teaches all the limitations of Claim 1 as discussed above.
Watanabe teaches:
The product management device according to claim 1, wherein the one or more processors are further configured to execute the instructions to acquire the discard time of the product based on an elapsed time from a time when the product is displayed.
In [0074-0075], "The significance of dynamically changing the display position will be explained below along with the relationship between the predicted sales volume and sales priority. FIG. 10 shows the sales status during the display period along with the change in the deterioration level e of a plurality of fried foods 35k1 to 35k5 that were displayed in the hotter 18 at different display start times. The fried foods 35k1 to 35k5 are put on display on the hot plate 18 at display times n=N1 to N4 and N6, respectively. The deterioration degree e of each fried food 35 increases during the display period. EI corresponds to the deterioration level e when the fried food 35 is removed from the hot plate 18, that is, at the time of the display expiration date. Therefore, each fried food 35 is removed from the hotter 18 when it reaches the deterioration level e=El".
Claim 3
As to Claim 3, Watanabe combined with Baca and Suzuki teaches all the limitations of Claim 1 as discussed above.
Watanabe combined with Baca does not expressly disclose the remaining limitations.
However, Suzuki teaches:
The product management device according to claim 1, wherein the one or more processors are further configured to execute the instructions to estimate the number of products to be cooked for each time zone to include a time zone in which cooking is not performed.
We understand the oil replacement process to encompass a period in which cooking is not being performed. In [0103] we have support for managing the cooking schedule such that we factor in periods in which oil is being replaced, "Therefore, it is desirable that the work of replacing the frying oil 17 in the oil tank 15 is completed before a busy period, and that the frying oil 17 is not disposed of too early and is not wasted. As an appropriate measure, for example, when the degree of deterioration of the frying oil 17 in the oil tank 15 is approaching the upper limit, a cooking schedule that is early and generous in allowing for the cooking of the fried foods 19 is formulated so that the frying oil 17 is fully used before being disposed of. It is thereby possible to carry out replacement work before a busy period and conserve the frying oil 17".
It would have been obvious to one having ordinary skill in the art at the effective filling date of the invention to apply the analytical methods as taught in Suzuki and apply that to the system as taught in Watanabe combined with Baca. Motivation to do so comes from the same rationale as outlined above with respect to Claim 1.
Claim 4
As to Claim 4, Watanabe combined with Baca and Suzuki teaches all the limitations of Claim 1 as discussed above.
Watanabe teaches:
The product management device according to claim 1, wherein the one or more processors are further configured to execute the instructions to predict the sales quantity for each time zone by using a prediction formula represented by a parameter that affects the sales quantity.
We construe the plurality of parameters taken into account when performing the prediction in [0088] to disclose the limitation of a parameter that affects the sales quantity, "Since the POS data includes information on the sales time and number of each type of fried food 35 up to the current time, it is possible to predict the sales number of each type of fried food 35 from the current time to a certain time in the future based on the POS data. Specifically, for example, correlations between the past sales numbers of fried foods based on past POS data and the sales numbers of each type of fried food 35 with past weather, temperature, humidity, and events (festivals and special events) around the store individually or in combination with two or more of these are analyzed from past statistics and created in advance. Next, at the prediction point in time when the predicted sales volume is to be predicted, the sales volume of each type of fried food 35 from a point in time a predetermined time before the prediction point in time to the prediction point in time is checked from the POS data. Then, based on the investigated sales numbers by type and the correlation created in advance, the sales numbers by type of fried food 35 from the time of prediction to the expiration date of fried food 35 (e.g., = investigated sales numbers by type x correlation value of the correlation created in advance) are predicted".
Claim 5
As to Claim 5, Watanabe combined with Baca and Suzuki teaches all the limitations of Claim 1 as discussed above.
Watanabe teaches:
The product management device according to claim 4, wherein the one or more processors are further configured to execute the instructions to predict the sales quantity for each time zone by using a prediction formula represented by a parameter different for each time zone.
We construe the plurality of dynamic parameters taken into account when performing the prediction in [0088] to disclose the limitation of a parameter that affects the sales quantity, "Since the POS data includes information on the sales time and number of each type of fried food 35 up to the current time, it is possible to predict the sales number of each type of fried food 35 from the current time to a certain time in the future based on the POS data. Specifically, for example, correlations between the past sales numbers of fried foods based on past POS data and the sales numbers of each type of fried food 35 with past weather, temperature, humidity, and events (festivals and special events) around the store individually or in combination with two or more of these are analyzed from past statistics and created in advance. Next, at the prediction point in time when the predicted sales volume is to be predicted, the sales volume of each type of fried food 35 from a point in time a predetermined time before the prediction point in time to the prediction point in time is checked from the POS data. Then, based on the investigated sales numbers by type and the correlation created in advance, the sales numbers by type of fried food 35 from the time of prediction to the expiration date of fried food 35 (e.g., = investigated sales numbers by type x correlation value of the correlation created in advance) are predicted". While it is certainly possible for all climatic variables to hold constant over multiple time zones, we construe this limitation to be disclosed by the reference's support for dynamic variables.
Claim 6
As to Claim 6, Watanabe combined with Baca and Suzuki teaches all the limitations of Claim 1 as discussed above.
Watanabe combined with Baca does not expressly disclose the remaining limitations.
However, Suzuki teaches:
The product management device according to claim 1, wherein the one or more processors are further configured to execute the instructions to: further predict a replacement timing of an ingredient to be used for cooking the product based on the estimated number of products to be cooked;
In [0103], "Therefore, it is desirable that the work of replacing the frying oil 17 in the oil tank 15 is completed before a busy period, and that the frying oil 17 is not disposed of too early and is not wasted. As an appropriate measure, for example, when the degree of deterioration of the frying oil 17 in the oil tank 15 is approaching the upper limit, a cooking schedule that is early and generous in allowing for the cooking of the fried foods 19 is formulated so that the frying oil 17 is fully used before being disposed of. It is thereby possible to carry out replacement work before a busy period and conserve the frying oil 17".
and output the replacement timing of the ingredient.
In [0054-0055], "Furthermore, when a degree of deterioration of the frying oil 17 is measured based on acid value, viscosity, etc., and the degree of deterioration reaches a first threshold value, the display 25 may read, for example, “Replace frying oil...Furthermore, when the degree of deterioration of the frying oil 17 reaches a second threshold value (that is greater than the first threshold value), the information processing device 27 may, from that point onward, continuously display on the display 25 that the degree of deterioration of the frying oil 17 has reached the second threshold value.”
It would have been obvious to one having ordinary skill in the art at the effective filling date of the invention to apply the analytical methods of Suzuki and apply that to the system of Watanabe combined with Baca. Motivation to do so comes from the same rationale as outlined above with respect to Claim 1.
Claim 7
As to Claim 7, Watanabe combined with Baca and Suzuki teaches all the limitations of Claim 6 as discussed above.
Watanabe does not expressly disclose the remaining limitations.
However, Baca teaches:
The product management device according to claim 6, wherein the one or more processors are further configured to execute the instructions to: further detect a product whose discard time has passed in the photographed image;
In [0012], "In embodiments, the apparatus may use sensors such as three-dimensional depth-based cameras and odor sensors along with predictive analytics with real-time learning into an intelligent food consumption platform, for example for a refrigerator and/or a pantry, to know exactly when certain foods will expire, and what foods may need to be replaced and when".
and further output an alert to notify that the discard time has passed.
In [0032], "In embodiments, the server 210 may include predictive analytics functions and/or real-time learning functions to provide useful information and/or recommendations for actions based upon sensor data received from the sensors included in the food storage 202. In embodiments, predictive analytics may be based on pattern recognition models such as a hidden Markov model, to identify the food items 108 within food storage 202, the condition of the individual food items within food storage 202, and to determine if a food item is fresh, spoiled, calculate/predict an estimated time to spoilage, or perform some other prediction of the future condition of the food item".
It would have been obvious to one having ordinary skill in the art at the effective filling date of the invention to apply the sensor analytics of Baca and apply that to the system of Watanabe. Motivation to do so comes from the same rationale as outlined above with respect to Claim 1.
Claim 8
As to Claim 8, Watanabe combined with Baca and Suzuki teaches all the limitations of Claim 7 as discussed above.
Watanabe combined with Baca does not expressly disclose the remaining limitations.
However, Suzuki teaches:
The product management device according to claim 7, wherein the one or more processors are further configured to execute the instructions to: further detect insufficiency of a product displayed on the furniture as compared with the sales quantity, and further output an alert to notify that the displayed product is insufficient.
In generating a report, shortages can be accounted for as outlined in [0115-0117], "Possible specific examples of the content of the report issued by the reporting unit 63 include the following. The response of the shop worker who received such a report is described after the symbol “.fwdarw”. c1) “Quantity of fried foods 19 in display case 40 is low.” .fwdarw.Cooks fried foods 19". This can be dynamically performed in response to changes in sale expectations, in [0120-0121], "(c3) “Event in neighborhood today, expected sales are: ______ pieces of XX chicken, YY . . . ” .fwdarw.Cooks corresponding type of fried foods 19".
It would have been obvious to one having ordinary skill in the art at the effective filling date of the invention to apply the analytical methods of Suzuki and apply that to the system of Watanabe combined with Baca. Motivation to do so comes from the same rationale as outlined above with respect to Claim 1.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to THEODORE L XIE whose telephone number is (571)272-7102. The examiner can normally be reached M-F 9-5.
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/THEODORE XIE/Examiner, Art Unit 3623
/WILLIAM S BROCKINGTON III/Primary Examiner, Art Unit 3623