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 .
DETAILED ACTION
Claims 1-20 are pending, the instant action is a non-final office action on the merits.
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 1-20 are rejected because they are directed to an abstract idea without more.
Claim 1, 8 and 14 are independent claims which are directed to a method, system and medium respectively. These are statutory classes of invention. (Step 1: yes)
The examiner has identified method claim 1 as the claim that represents the invention for analysis and is similar to independent claims 7 and 13.
Claim 1 recites the following limitations;
1. A method for automated dispensing of restricted goods based on user verification, the method being implemented by at least one processor, the method comprising: obtaining user feature data via a user device; performing verification of the user feature data via at least one of a government database or a third-party identity verification database with a digitized representation of a government-issued physical card saved on the user device, wherein the verification is based on a cryptographic operation occurring locally within the user device; performing analysis of the user feature data with at least one deep learning model for signs of inebriation; and dispensing automatically, via a digital tap system, the restricted goods upon a positive verification of the user feature data via at least one of the government database or the third- party identity verification database with the digitized representation of the government-issued physical card based on the cryptographic operation and a result of the analysis with the at least one deep learning model showing no signs of inebriation or signs of inebriation below a predetermined threshold level.
These limitations under their broadest reasonable interpretation cover performance of the limitation as certain methods of organizing human activity.
The abstract elements;
obtaining user feature data via a …; performing verification of the user feature data via at least one of a government database or a third-party identity verification database with a digitized representation of a government-issued … saved on the …, wherein the verification is based on a cryptographic operation occurring locally within the …; performing analysis of the user feature data with at least one deep learning model for signs of inebriation; and dispensing automatically, via a …, the restricted goods upon a positive verification of the user feature data via at least one of the government database or the third- party identity verification database with the digitized representation of the government-issued … based on the cryptographic operation and a result of the analysis with the at least one deep learning model showing no signs of inebriation or signs of inebriation below a predetermined threshold level.
Here the non-abstract elements include a user device, physical card and digital tap system. The claim limitations under it’s broadest reasonable interpretation covers performance of the limitation as a fundamental economic practice, then it falls within the certain methods of organizing human activity grouping of abstract ideas. Accordingly the claim recites an abstract idea. The user device, physical card and digital tap of claim 1 are just applying generic computing elements to the recited abstract limitations. The recitation of generic computer components in a claim does not necessarily preclude that claim from reciting an abstract idea. Claims 7 and 13 are similar to claim 1. (Step 2A prong 1)yes the claims recite an abstract idea.
This judicial exception is not integrated into a practical application. In particular the claims recite the additional elements such as product dispenser for POS display in claim 4, and server claim 5, mobile device claim 6, and respective claims 10-12 and 16-18.
The computer hardware is recited at a high level of generality, ie generic processor performing a generic computing function such that it amounts to no more than mere instructions to apply the exception using a generic computer component. Accordingly these additional elements when considered separately and as an ordered combination do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea and are at a high level of generality. Therefor claims x, y and z are directed to an abstract idea without a practical application . (Step 2A prong 2 No. )
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because when considered separately and as an ordered combination they do not add significantly more known as inventive concept. As discussed above with respect to integration of the abstract idea into a practical application the additional element amounts not no more than mere instructions to apply the exception using a generic computing component. Mere instructions to apply an exception using a generic computing component cannot provide an inventive concept. Applicant’s specification does recite a specialized digital tap for dispensing drinks so it is possible to hone in on this inventive concept. (Step 2 B No the claims do not provide significantly more)
Dependent claims 2-7,9-13,15-20 do not include additional elements that integrate the abstract idea into a practical application or amount to significantly more. Thus claims 1-20 are ineligible.
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.
Claim(s) 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over US Patent Publication to Trelin 20210264395 in view of US Patent Publication 20090157515 to Lafauci further in view of US Patent Publication to Block 20240406211 (learning and ai)
As per claim 1, Trelin discloses;
A method for automated dispensing of restricted goods based on user verification and a fitness-for-duty determination, the method being implemented by at least one processor, the method comprising:
obtaining user feature data via a user device; Trelin(0049, and 0077, this element could be a lot of different things)
performing verification of the user feature data via at least one of a government database or a third-party identity verification database with a … of a government-issued physical card saved on the user device, Trelin(0184)
wherein the verification is based on a cryptographic operation occurring locally within the user device; Trelin(0185 encryption)
the restricted goods upon a positive verification of the user feature data via at least one of the government database or the third- party identity verification database with the digitized representation of the government-issued physical card based on the cryptographic operation
Trelin(0038, this id system may be biometric and third party identify the person by database)
and a result of the
analysis with the at least one deep learning model determining that the user is fit-for-duty based on no signs of inebriation or signs of inebriation below a predetermined threshold level.
Trelin(0061, the system can check for inebriation via a fingerprint tester )
Trelin does not explicitly disclose what Lafauci teaches;
a digitized representation of the id.
Lafauci (0113, in view of 0008)
It would therefore have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine the digital dispenser of Trelin with the id card of Lafauci for the motivation of
”screening and preventing … rather than preventing public intoxication” (0005)
Trelin and Lafauci do not explicitly disclose what Block teaches;
performing analysis of the user feature data with at least one deep learning model
Block 0078
It would therefore have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine the digital dispenser of Trelin with the deep learning and I teachings of Block for the motivation of identifying fraud in access (in summary 0002)
Claims 8 and 14 are similar to claim 1.
As per claim 2 Trelin does not explicitly disclose what Block teaches;
The method of claim 1,further comprising: training the at least one deep learning model to analyze the user feature data to detect the signs of inebriation (Trelin)
and updating the at least one deep learning model via backpropagation of errors.
Block(0082, backpropagation)
It would therefore have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine the digital dispenser of Trelin with the deep learning and convolution teachings of Block for the motivation of identifying fraud in access (in summary 0002)
Claim 15 is similar to claim 2
As per claim 3 Trelin does not explicitly disclose what Block teaches;
The method of claim 2, wherein the at least one deep learning model comprises an ensemble of deep convolutional neural networks (CNNs).
Convolutional- 0078 of Block
It would therefore have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine the digital dispenser of Trelin with the deep learning and convolution teachings of Block for the motivation of identifying fraud in access (in summary 0002)
Claim 16 is similar to claim 3
(9 is similar to 2, 3 combined)
As per claim 4 Trelin discloses; The method of claim 1, wherein the digital tap system comprises: a product dispenser, at least one sensor, at least one camera, and at least one interface comprising a point-of-sale display operably attached to flow-metered dispensaries for communicating with the user device and with computing devices to manage and operate the digital tap system. Trelin(0061, sensor, dispenser 0066, camera 0038, etc.)
Claims 10 and 17 are similar to claim 4
As per claim 5 Trelin does not explicitly disclose what Lafauchi teaches;
the method of claim 1, wherein the performing the verification of the user feature data comprises verifying the user feature data comprising
an age and a name of the user with the digitized representation of the government-issued physical card; and wherein the cryptographic operation occurs locally within the user device such that an internet connection to a remote server is not required in the performing the verification.
Lafauci (0113, in view of 0008)
It would therefore have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine the digital dispenser of Trelin with the id card of Laufaci for the motivation of
”screening and preventing … rather than preventing public intoxication” (0005)
claims 11 and 18 are similar to claim 5.
As per claim 6, Trelin The method of claim 5, wherein the digitized representation of the government-issued physical card is accessible via the user device comprising a mobile device.
Trelin(0066)
Claims 12 and 19 are similar to claim 6
As per claim 7, Trelin discloses;
The method of claim 1, wherein the performing the analysis further comprises: generating a weighted combination measurement based on the obtained user feature data as obtained from at least one sensor; and determining whether the user is fit-for-duty by
based on the weighted combination measurement. Trelin( 0061)
Trelin and Lafauci do not explicitly disclose what Block teaches;
the at least one deep learning model. Block (0078)
It would therefore have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine the digital dispenser of Trelin with the deep learning and convolution teachings of Block for the motivation of identifying fraud in access (in summary 0002)
Claims 13 and 20 are similar to claim 7
Conclusion
The following non-patent literature was identified;
Beverages in Dispenser Machine According to Capsule Identification with Barcode, IEEE 2017
Bluetooth-Enabled Smart Juicebot Controlled via Mobile App, IEEE 2024
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BRUCE I EBERSMAN whose telephone number is (571)270-3442. The examiner can normally be reached 8:00 am - 5:00 pm Monday-Friday.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Michael W Anderson can be reached at 571-270-0508. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/BRUCE I EBERSMAN/Primary Examiner, Art Unit 3693