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 .
This office action is in response to amendments filed June 19, 2023.
Claims 3, 4, 10, and 11 have been amended.
Claims 1-12 are pending.
Priority
As required by M.P.E.P. 201.14(c), acknowledgement is made of applicant’s claim for priority based on applications filed on December 22, 2021 (PCT/EP2021/087377) and December 22, 2020 (Sweden 2051541-7, 2051540-9, 2051545-8, 2051542-5, 2051543-3, 2051547-4, and 2051546-6 1).
Information Disclosure Statement
As required by M.P.E.P. 609(C), the applicant’s submissions of the Information Disclosure Statements dated June 19, 2023 and September 15, 2023 are acknowledged by the examiner and the cited references have been considered in the examination of the claims now pending. As required by M.P.E.P 609, a copy of the PTOL-1449 initialed and dated by the examiner is attached to the office action.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 11 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim 11, the claim recites “the behavior pattern” in line 18 of the claim. There is insufficient antecedent basis for this limitation in the claim. For the purposes of examination the limitation is interpreted as “the regular behavior pattern”.
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.
Claims 1, 2, 3, 11, and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Hershberger et al. (US Publication 20200172387A1) in further view of Crouse et al. (US Publication 20180044159A1).
Regarding claim 1, Hershberger teaches a beverage distribution system comprising:
a plurality of reusable beverage containers where each of the plurality of beverage containers carries a unique identification tag (The unique RFID process may begin at the brewery, as shown in FIG. 32 ... As a new keg is filled, the Brewery Inventory Computer may make a request to the cloud software to issue a new unique RFID serial number ... print a visible label or tag using the issued unique serial number ... The tag may be attached to a beer keg (D) … to refill the keg)([0276], [0279], and [0547]); unique serial number tags are attached to refillable kegs),
the system further comprising a plurality of identification tag readers, where at least some tag readers are located at different geographical locations, the tag reader being configured to read the identification tags (FIG. 31 is a flow chart of a draft beer supply chain system ... As the keg is moved into the brewery warehouse, it passes through the RFID gate (G). The RFID gate has UHF RFID readers that record ... As the keg is loaded onto the delivery vehicle, the keg passes through a RFID-equipped gate (F) ... The Brewery Truck may deliver the keg to the Distributor Warehouse, where it is unloaded off of the truck and passes through another RFID gate (I))([0275], [0279], [0280], [0281]; Figure 31 – a plurality of tag readers at different geographical locations is shown),
said tag readers being connected to a server (RFID-equipped gate reads the UHF tag of the keg and reports the unique serial number to the cloud)([0280]),
said server being configured to store a state of each of the plurality of beverage containers in a digitally stored dataset, where the state is that the beverage container is present at one of the tag readers (RFID readers that record and transmit to the cloud software a signal indicating that the keg has been moved into the brewery warehouse ... RFID-equipped gate reads the UHF tag of the keg and reports the unique serial number to the cloud software. The cloud software records that the keg has left the brewery ... the cloud software records that the keg has moved along the supply chain to a certain point)([0279], [0280], and [0281]; a container’s state (i.e., location) is present at a corresponding reader and is stored on a cloud server),
where the system is configured to … making a decision about taking an individual beverage container out of service (Using a computer system to produce a suggestion regarding one of whether to refill the keg with a beverage and whether to serve beverages from the keg)([0547]).
Hershberger differs from the claim in that Hershberger fails to teach applying machine learning to the dataset to produce a decision rule that comprises a statistical model for regular behavior pattern of a plurality of beverage containers. However, applying machine learning to a dataset to produce a decision rule that comprises a statistical model for regular behavior pattern of a plurality of beverage containers is taught by Crouse (FIG. 10B shows an illustrative process 950 to implement a machine learning algorithm ... an artificial neural network (ANN) model ... system 150 using machine learning to train the ANN model ... the number of data points in each of the input and output layers which will be separated in the ANN model by one or more layers of neurons. Any number of input and output data points can be utilized for the input and output layers ... an ANN model or other machine learning algorithm may be deployed for refill optimization purposes ... For example, if tank 1 in location A is 10% full while tank 2 in location B is 20% full, the delivery driver and/or ERP may assume tank 1 needs refilled before tank 2. However, if tank 2 is generally used at a much faster rate than tank 1, then tank 2 may need to be refilled first)([0072], [0075], [0092]). The examiner notes Hershberger and Crouse teach a system of beverage distribution. As such, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Hershberger to include the applying of Crouse such that the system applies machine learning to a dataset to produce a decision rule for making a decision. One would be motivated to make such a combination to provide the advantage of improving decision making ([0092]; Crouse).
Regarding claim 2, Hershberger-Crouse teach the system of claim 1 where an end-of life for the beverage container is determined (Crouse - the machine learning algorithm receiving the response data can be capable of outputting a fill level measurement)([0011]; a fill level (e.g., empty) is indicative of end of life of a container).
Regarding claim 3, Hershberger-Crouse teach the system of claim 1 where the state is stored together with a time point (Hershberger - The Inventory Management portion of the system may include a Keg Tracker that receives updated keg information (e.g., location, sensor ID, volume, and/or time stamp))([0273]).
Regarding claim 11, Hershberger teaches a method in beverage distribution system said beverage distribution system comprising:
a plurality of reusable and portable beverage containers where each of the plurality of beverage containers carries a unique identification tag (The unique RFID process may begin at the brewery, as shown in FIG. 32 ... As a new keg is filled, the Brewery Inventory Computer may make a request to the cloud software to issue a new unique RFID serial number ... print a visible label or tag using the issued unique serial number ... The tag may be attached to a beer keg (D) … to refill the keg)([0276], [0279], and [0547]); unique serial number tags are attached to refillable kegs),
the system further comprising a plurality of identification tag readers, where at least some tag readers are located at different geographical locations, the tag reader being configured to read the identification tags (FIG. 31 is a flow chart of a draft beer supply chain system ... As the keg is moved into the brewery warehouse, it passes through the RFID gate (G). The RFID gate has UHF RFID readers that record ... As the keg is loaded onto the delivery vehicle, the keg passes through a RFID-equipped gate (F) ... The Brewery Truck may deliver the keg to the Distributor Warehouse, where it is unloaded off of the truck and passes through another RFID gate (I))([0275], [0279], [0280], [0281]; Figure 31 – a plurality of tag readers at different geographical locations is shown),
said tag readers being connected to a server (RFID-equipped gate reads the UHF tag of the keg and reports the unique serial number to the cloud)([0280]),
said server being configured to store a state of each of the plurality of beverage containers in a digitally stored dataset, where the state is that the beverage container is present at one of the tag readers (RFID readers that record and transmit to the cloud software a signal indicating that the keg has been moved into the brewery warehouse ... RFID-equipped gate reads the UHF tag of the keg and reports the unique serial number to the cloud software. The cloud software records that the keg has left the brewery ... the cloud software records that the keg has moved along the supply chain to a certain point)([0279], [0280], and [0281]; a container’s state (i.e., location) is present at a corresponding reader and is stored on a cloud server), the method comprising:
… make a decision about taking an individual beverage container out of service (Using a computer system to produce a suggestion regarding one of whether to refill the keg with a beverage and whether to serve beverages from the keg)([0547]).
Hershberger differs from the claim in that Hershberger fails to teach applying machine learning to the dataset to produce a decision rule that comprises a statistical model for regular behavior pattern of a plurality of beverage containers and applying the decision rule to the dataset at a predetermined time period, where a container that departs from behavior pattern is flagged in the dataset for being taken out of service. However, applying machine learning to a dataset to produce a decision rule that comprises a statistical model for regular behavior pattern of a plurality of beverage containers and applying the decision rule to a dataset at a predetermined time period, where a container that departs from behavior pattern is flagged in the dataset for being taken out of service is taught by Crouse (the method and desired accuracy of fill level determination from ... sampling rate … FIG. 10B shows an illustrative process 950 to implement a machine learning algorithm ... an artificial neural network (ANN) model ... system 150 using machine learning to train the ANN model ... the number of data points in each of the input and output layers which will be separated in the ANN model by one or more layers of neurons. Any number of input and output data points can be utilized for the input and output layers ... measuring the fill level 140 over a period of time delay 837 … an ANN model or other machine learning algorithm may be deployed for refill optimization purposes ... For example, if tank 1 in location A is 10% full while tank 2 in location B is 20% full, the delivery driver and/or ERP may assume tank 1 needs refilled before tank 2. However, if tank 2 is generally used at a much faster rate than tank 1, then tank 2 may need to be refilled first)([0048], [0072], [0075], [0088], and [0092]). The examiner notes Hershberger and Crouse teach a method of beverage distribution. As such, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Hershberger to include the applying of Crouse such that the method applies machine learning to a dataset to produce a decision rule which is applied at predetermined time periods to make a decision. One would be motivated to make such a combination to provide the advantage of improving decision making ([0092]; Crouse).
Regarding claim 12, Hershberger-Crouse teach the method of claim 11 where an end-of life for the beverage container is determined (Crouse - the machine learning algorithm receiving the response data can be capable of outputting a fill level measurement)([0011]; a fill level (e.g., empty) is indicative of end of life of a container).
Claims 4, 5, 6, 9, and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Hershberger, Crouse, in further view of Wing et al. (US Publication 20200031654A1).
Regarding claim 4, Hershberger-Crouse teach the system as applied above, wherein the tag reader detects presence (Hershberger - When the Distributor Truck (N) arrives at the retailer, e.g., a bar or restaurant, the keg is off loaded from the truck ... As the keg is moved into the cooler of the retailer, the keg passes through an RFID gate (O))([0284]). Hershberger-Crouse differs from the claim in that Hershberger-Crouse fails to teach a beverage dispensing station comprises one of the tag readers and connects to the beverage container to dispense beverage, wherein the tag reader detects a beverage container present at the beverage dispensing station. However, a beverage dispensing station comprising a tag reader and connects to a beverage container to dispense beverage, wherein the tag reader to detect a beverage container present at the beverage dispensing station is taught by Wing (a beverage dispenser includes ... a nozzle ... The beverage dispenser of claim can be configured to have ... ready to drink beverages (such as juice, beer, or wine) ... a nozzle for dispensing beverages that include ... a first inlet for cold liquids to be included in beverages to be dispensed, a flow path from the first inlet through the nozzle to the outlet ... slots also includes an RFID reader 285 for each of the modules held in the slot. The RFID reader can read RFID tags 291 on ... each of the consumable containers)([0010], [0011], [0030], and [0112]). The examiner notes Hershberger, Crouse, and Wing teach a system of beverage distribution. As such, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Hershberger-Crouse to include the beverage dispensing station of Wing such that the system utilizes a beverage dispensing station to dispense beverage from containers and detects containers present at the beverage dispensing station. One would be motivated to make such a combination to provide the advantage of controlling the dispensing of beverages ([0002]; Wing).
Regarding claim 5, Hershberger-Crouse-Wing teach the system of claim 4 where said beverage dispensing station has a sensor, the dispensing station being configured to collect data from the sensor and provide it, using the wireless data connection, to the server, the server further being configured to include the sensor data in the dataset (Wing - As shown in FIG. 8, the main electronics components are ... base unit control board also reads data from a variety of sensors ... each machine communicates with a central server to send information about the state and operation of the machine ... The central server includes one or more processors and databases ... application of machine learning to data in the database)([0070], [0187], and [0188]).
Regarding claim 6, Hershberger-Crouse-Wing teach the system of claim 5 where the sensor is a weight determining means, an accelerometer or a temperature sensor (Wing - The components of the machine also include ... a temperature sensor 94)([0071]).
Regarding claim 9, Hershberger-Crouse-Wing teach the system of claim 6 where the sensor is a temperature sensor (Wing - The components of the machine also include ... a temperature sensor 94)([0071]).
Regarding claim 10, Hershberger-Crouse teach the system above, wherein the system includes a tag reader (Hershberger - When the Distributor Truck (N) arrives at the retailer, e.g., a bar or restaurant, the keg is off loaded from the truck ... As the keg is moved into the cooler of the retailer, the keg passes through an RFID gate (O))([0284]). Hershberger-Crouse differs from the claim in that Hershberger-Crouse fails to teach a beverage dispensing station, wherein at least one of tag readers is in the beverage dispensing station. However, a beverage dispensing station comprising a tag reader is taught by Wing (The beverage dispenser of claim can be configured to have ... ready to drink beverages (such as juice, beer, or wine) ... slots also includes an RFID reader 285 for each of the modules held in the slot. The RFID reader can read RFID tags 291 on ... each of the consumable containers)([0011] and [0112]). The examiner notes Hershberger, Crouse, and Wing teach a system of beverage distribution. As such, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Hershberger-Crouse to include the beverage dispensing station of Wing such that the system utilizes a beverage dispensing station comprising of tag readers. One would be motivated to make such a combination to provide the advantage of controlling the dispensing of beverages ([0002]; Wing).
Claims 7 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Hershberger, Crouse, Wing, in further view of Manwani et al. (WO2016141322A1).
Regarding claim 7, Hershberger-Crouse-Wing teach the system as applied above, wherein the system includes a plurality of sensors (Wing - The base unit control board also reads data from a variety of sensors)([0070]). Hershberger-Crouse-Wing differs from the claim in that Hershberger-Crouse-Wing fails to teach the sensor is a weight determining means. However, weight determining sensor is taught by Manwani (The system 200 may include one or more other sensors ... may also or instead include ... weight sensor)([0068] and [0070]). The examiner notes Hershberger, Crouse, Wing, and Manwani teach a system of beverage distribution. As such, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Hershberger-Crouse-Wing to include the sensor of Manwani such that the station includes a weight sensor. One would be motivated to make such a combination to provide the advantage of improving accuracy at predicating useful self life ([0070]; Manwani).
Regarding claim 8, Hershberger-Crouse-Wing teach the system as applied above, wherein the system includes a plurality of sensors (Wing - The base unit control board also reads data from a variety of sensors)([0070]). Hershberger-Crouse-Wing differs from the claim in that Hershberger-Crouse-Wing fails to teach the sensor is an accelerometer. However, an accelerometer sensor is taught by Manwani (The system 200 may include one or more other sensors ... may also or instead include an accelerometer)([0068] and [0070]). The examiner notes Hershberger, Crouse, Wing, and Manwani teach a system of beverage distribution. As such, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Hershberger-Crouse-Wing to include the sensor of Manwani such that the station includes an accelerometer sensor. One would be motivated to make such a combination to provide the advantage of improving accuracy at predicating useful self life ([0070]; Manwani).
Conclusion
The prior art made of record on form PTO-892 and not relied upon is considered pertinent to applicant's disclosure. Applicant is required under 37 C.F.R. § 1.111(c) to consider the reference fully when responding to this action. The document cited therein and enumerated below teaches a method and apparatus for beverage distribution.
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Any inquiry concerning this communication or earlier communications from the examiner should be directed to Yongjia Pan whose telephone number is (571)270-1177. The examiner can normally be reached Monday - Friday, 9:00 AM - 5:00 PM EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Scott Baderman can be reached at 571-272-3644. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/YONGJIA PAN/ Primary Examiner, Art Unit 2118