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 .
Election/Restrictions
Applicant’s election without traverse of Group I (claims 1-10) in the reply filed on 04/17/2026 is acknowledged. Claims 11-21 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected invention.
Claim Rejections - 35 USC § 103
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating
obviousness or nonobviousness.
Claims 1, 2 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Accursi US 2019/0021543 in view of in view of Kohli US 2011/0038998 in view of Kwon US 2016/0342863 in view of Agon US 2015/0216352.
Regarding claim 1, Accursi discloses a method for preparing and dispensing a beverage (claim 1, claim 22, [0025, [0026]), the method comprising: inserting a capsule in a capsule feeder (infeed section 9) of a machine; recognizing a type of the capsule by a capsule recognition module of the machine ([0005], [0058], claim 22), wherein the capsule recognition module determines the type of the capsule inserted in the beverage preparation machine at a capsule recognition position by capturing an image of the capsule and processing the image ([0005], [0052]-[0058], claim 22); relatively moving a first part and a second part of an extraction unit of the machine into a distant position obviously automatically (Figs, 1-2, [0027]); supplying the capsule to an extraction chamber (extraction chamber 4) of the machine ([0035]); relatively moving the first and second parts into a close position to position the capsule in the extraction chamber ([0027], [0044]); extracting the capsule in the extraction chamber by applying extraction parameters determined on a basis of the type of the capsule determined by the recognition module ([0005], [0008]-[0012], [0070]), to prepare the beverage; and obviously dispensing the beverage via an outlet to a receptacle in a receptacle placing area of the machine ([0026]).
Claim 1 differs from Accursi in the recitation that the processing of the image is specifically by a neural network computing device. It is noted that Accursi discloses that any image processing/recognition method may be used ([0058]).
Kohli discloses that it was known it the art to utilize neural networks for image processing and which neural networks can compute technical parameters without requiring a detailed theoretical rule system having to be set up ([0017]).
Kwon discloses a method for determining/identifying an object or product represented in an image and discloses processing the image using a neural network (Abstract [0042], [0059]).
Agon discloses recognizing capsules using a capsule recognition module ([0020],[0036]). Agon discloses that the capsule recognition module measures a set of characteristics of the detected capsule and a profile of the detected capsule is drawn up by the measured characteristics. The profile comprises at least one minimal set of information to identify the belonging of the detected capsule to a reference group ([0030]). Agon discloses that approaches to determine if a profile matches one of the reference profiles includes using self-learning neural networks ([0030]). Thus, Agon recognizes a known recognition method includes using self-learning neural networks to process information regarding capsules.
Therefore, based on the art above as a whole, it would have been obvious to one of ordinary skill in the art to modify Accursi such that the processing of the image is specifically by a neural network computing device as suggested by Kohli and Kwon and Agon, since Accursi discloses that any image processing/recognition method may be used ([0058]) and the prior art recognizes that known image processing/recognition methods includes using neural network computing device. It has been held that “Combining prior art elements according to known methods to yield predictable results” and “Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results” supports a conclusion of obviousness (MPEP 2143.I.A,D).
Regarding claim 2 Accursi discloses that the recognizing the type of capsule by the capsule recognition module comprises lighting the capsule at the capsule recognition position by at least one source of light (‘543, [0049]).
Regarding claim 9, Modified Accursi makes obvious that the processing the image by the neural network computing device comprises using a neural network program previously trained to recognize the type of capsule based on a digital image of at least part of the capsule (‘998, [0017]) (‘863, Abstract, [0042], [0059]).
Claims 3-8 are rejected under 35 U.S.C. 103 as being unpatentable over Accursi US 2019/0021543 in view of Kohli US 2011/0038998 in view of Kwon US 2016/0342863 in view of Agon US 2015/0216352 in view of Accursi US 2020/0154937.
Regarding claim 3, claim 3 differs from Modified Accursi in the recitation that the recognizing the type of capsule by the capsule recognition module comprises diffusing the light of the at least one source of light towards the capsule recognition position by a diffusor.
Accursi discloses recognizing the type of capsule by the capsule recognition module comprises diffusing the light of the at least one source of light towards the capsule recognition position by a diffusor to promote more diffuse lighting which creates fewer reflections (surface finish on region 521) ([0067]-[0069]). It would have been obvious to one of ordinary skill in the art to modify Modified Accursi such that the recognizing the type of capsule by the capsule recognition module comprises diffusing the light of the at least one source of light towards the capsule recognition position by a diffusor as taught by Accursi in order to promote more diffuse lighting which creates fewer reflections.
Regarding claim 4, Modified Accursi discloses that the diffusing comprises contacting the light with a structured inner surface of the diffusor (rough finish of surface finish on region 521) (‘937, [0067]-[0069]).
Regarding claim 5, Modified Accursi discloses that the diffusor prevents direct reflection of light from the at least one source of light on the capsule located at the capsule recognition position (‘937, [0067]-[0069], [0097]).
Regarding claim 6, Modified Accursi discloses the recognizing the type of the capsule by the capsule recognition module comprises guiding the light emitted by the at least one source of light towards the capsule recognition position by a light guide in order to avoid sensing parasitic light (light guide prevents unwanted lighting of the optical sensor) (‘937, [0062]-[0065]).
Regarding claim 7, Modified Accursi discloses the recognizing the type of the capsule by the capsule recognition module comprises limiting light received by the camera of the machine to light reflected by the capsule located at the capsule recognition position in order to avoid sensing parasitic light (light guide prevents unwanted lighting of the optical sensor) (‘937, [0062]-[0065], [0086], [0008]).
Regarding claim 8, Modified Accursi discloses the light guide comprises at least one light guiding protrusion that guides light from the at least one source of light to the diffusor (‘937, [0062]-[0069])
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Accursi US 2019/0021543 in view of Kohli US 2011/0038998 in view of Kwon US 2016/0342863 in view of Agon US 2015/0216352 in view of Bugano US 2016/0157668.
Regarding claim 10, claim 10 differs from Modified Accursi in the recitation that the recognizing the type of the capsule comprises recognizing a plurality of predetermined capsules of different types by the capsule recognition module, and extracting the capsule comprises extracting the plurality of predetermined capsules of different types to prepare different beverages.
Bugano discloses providing sets of capsules for use in beverage preparation machines and discloses recognizing the type of the capsule comprises recognizing a plurality of predetermined capsules of different types by the capsule recognition module, and extracting the capsule comprises extracting the plurality of predetermined capsules of different types to prepare different beverages ([0110], Claim 15, Abstract).
It would have been obvious to one of ordinary skill in the art to have Modified Accursi such that the recognizing the type of the capsule comprises recognizing a plurality of predetermined capsules of different types by the capsule recognition module, and extracting the capsule comprises extracting the plurality of predetermined capsules of different types to prepare different beverages as suggested by Bugano in order to allow a user to suitably prepare different beverages utilizing the machine of Accursi. It has been held that “Combining prior art elements according to known methods to yield predictable results” and “Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results” supports a conclusion of obviousness (MPEP 2143.I.A,D).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ASHLEY AXTELL whose telephone number is (571)270-0316. The examiner can normally be reached M-F 9:00- 5:30.
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/A.A/
Ashley AxtellExaminer, Art Unit 1792
/VIREN A THAKUR/Primary Examiner, Art Unit 1792
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