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 .
Continuation Data
2. This application claims priority to PCT/KR2024/006204, filed May 9, 2024.
Priority
3. Receipt is acknowledged of papers submitted under 35 U.S.C. 119(a)-(d), which papers have been placed of record in the file.
Information Disclosure Statement
4. The Information Disclosure Statement filed on November 7, 2025 has been considered. An initialed copy of the Form 1449 is enclosed herewith.
Claim Rejections - 35 USC § 103
5. The following is a quotation of 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102 of this title, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negatived by the manner in which the invention was made.
6. Claims 1, 2, 6, and 7 are rejected under 35 U.S.C. 103(a) as being unpatentable over Hoynash et al (2017/0057748), hereinafter Hoynash in view of Gorman (2020/0324974).
With respect to claims 1, 6, and 7, Hoynash teaches an unmanned store product checkout apparatus (check-out apparatus for automated storing of goods corresponding to a purchase transaction: paragraphs 0114-0116 and figure 19), comprising: a transfer unit having partitions installed at preset intervals to divide compartments, to transfer a product to scan the product desired by a user to purchase (feed component 1602 receives transports items corresponding to a purchase/transaction and can be a conveyor belt/cross belt: paragraph 0118; interlocking palettes which form narrow width chambers arranged along the conveying path: paragraphs 0097, 0102, and 0158); first product recognition unit installed at a first point where transfer of the product begins
by the transfer unit (feed component 1602 may automatically detect the presence/receipt of an item and react by beginning to transport it toward identification device 1604. Detection can be by item weight or motion of placement: paragraph 0118), to recognize that the product is placed on the transfer unit; a weight sensor installed at a lower one side of the transfer unit, to measure a weight of the product (identification device 1604 can identify using weight and may include a weight/density scale: paragraph 0117); a scan unit installed to be spaced apart from the transfer unit as much as a preset distance, to scan a barcode and an image of the product transferred by the transfer unit (camera: paragraph 0121); a processor for identifying what the product is by using artificial intelligence learning data on the basis of the barcode and image of the product scanned by the scan unit and the weight of the product measured through the weight sensor (identification device identifies items using barcodes: paragraph 0121);
a second product recognition unit installed at a second point where scan of the product by the scan unit is terminated, to recognize that the product has arrived at the second point (various types of sensors for scanning a barcode: paragraph 0121); a product classification unit installed at the second point, to classify the product on the
basis of a result of the product identification (paragraphs 0123-0126); a calculation unit for calculating a total price of the products (pricing information may be obtained and purchase processed: paragraph 0120); a display unit for providing the user with the total price and a product list (display: paragraph 0127); and a control unit for controlling operations of the transfer unit and the product classification unit on the basis of a result of first product recognition performed by the first product recognition unit, a result of second product recognition performed by the second product recognition unit, and a result of product identification performed by the processor (controller is electrically connected to the cross-belt system: paragraph 0057; controller send a signal: paragraph 0079; identification device 1604 identifies the item and selects a receiving area for the transaction: paragraph 0120). Claims 6 and 7 combined include the limitations set forth in claim 1.
With respect to claim 2, Hoynash teaches the apparatus, wherein the scan unit includes: a barcode scanner for recognizing the barcode of the product; and
an image scanner for acquiring image information by scanning the image of the product (barcode scanner: paragraph 0121; camera: paragraph 0122).
Hoynash’ teaching above however fail to specifically teach a processor for identifying what the product is by using artificial intelligence.
With respect to claims 1 and 7, Gorman teaches using AI learning data to identify a product, wherein the processing system employs AI including a trained machine-learning algorithm using historical datasets, and AI such as convolutional neural network to recognize and/or classify items based on image data captured by automated reading stations (paragraph 0151-0521).
In view of Gorman’s teachings, it would have been obvious to an artisan of ordinary skill in the art, before the effective filling date of the claimed invention to modify the product identification processing of Hoynash to employ the AI/machine-learning techniques taught by Gorman for recognizing and/or classifying products. One would be motivated to use Gorman’s techniques for the purpose providing automated recognition and classification of products, thereby reducing the need for manual product identification and increasing efficiency of the automated system.
Allowable Subject Matter
7. Claims 3-5 and 8-10 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form, including all of the limitations of the base claim and any intervening claims.
The following is an examiner’s reason for allowance: Although Olmstead et al teaches a light source mechanism of a barcode scanner, the above identified prior art of record, taken alone, or in combination with any other prior art, fails to teach or fairly suggest the specific features of claims 3-5 of the present claimed invention. Specifically, prior art fails to teach claimed apparatus, wherein the processor identifies the product as a scanned product corresponding to identification information included in the barcode when the barcode is recognized, acquires a product name and a character string from the image information and identifies the product as a scanned product on the basis of the image information, the product name, and the character string using artificial intelligence learning data when the barcode is not recognized, compares the weight of the product measured using the weight sensor with weight information included in product information corresponding to the scanned product, transmits a first signal indicating that the product has been normally identified to the control unit when the product is verified as a scanned product as a result of the comparison, and transmits a second signal indicating that the product has not been normally identified to the control unit when the product is not verified as a scanned product or it is verified that the product is not a scanned product as a result of the comparison and similarly fails to teach the claimed method, wherein the step of classifying the product includes the steps of: comparing weight information of a scanned product included in the scanned product information with a measured weight of the product; and transferring the product through the transfer unit to be classified into the first area when the product is verified as the scanned product as a result of the comparison. Lastly, prior art fails to teach the claimed method wherein the step of classifying the product includes the steps of: comparing weight information of a scanned product included in the scanned product information with a measured weight of the product; recognizing through the second product recognition unit whether the product has arrived at a second point where the second product recognition unit is installed, when the product is verified as a different product as a result of the comparison or when the product is an unconfirmed product; controlling the transfer unit to stop the operation when it is recognized through the second product recognition unit that the product has arrived at the second point; controlling the operation of the product classification unit to push the product to get out of the transfer unit so that the product may be classified into the second area; and providing a notification indicating that the product has been classified into the second area to the user terminal. The above limitations are not disclosed in prior art and moreover, one of ordinary skill in the art would not have been motivated to come to the claimed invention.
Conclusion
8. The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure: See attached PTO form 892, Refence Cited.
9. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Allyson N. Trail whose telephone number is (571) 272-2406. The examiner can normally be reached between the hours of 7:30AM to 4:00PM Monday thru Friday.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Thomas Pham, can be reached on (571) 272-3689. The fax phone number for this Group is (571) 273-8300.
Communications via Internet e-mail regarding this application, other than those under 35 U.S.C. 132 or which otherwise require a signature, may be used by the applicant and should be addressed to [allyson.trail@uspto.gov].
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/ALLYSON N TRAIL/Primary Examiner, Art Unit 2876
September 19, 2026
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