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 .
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.
Claims 7 and 18 recites the limitation "the mismatched rack storage area". There is insufficient antecedent basis for this limitation.
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 under 35 U.S.C. 101. Claim(s) 1-20 is/are directed to statutory methods, non-transitory computer readable medium, and systems under Step 1 of the eligibility analysis. However, the claims are further directed toward a judicial exception under Step 2A Prong One of the eligibility analysis, namely an abstract idea. Under Step 2A Prong Two of the eligibility analysis, the claim(s) does/do not include additional elements to integrate the exception into a practical application of that exception. Under Step 2B of the eligibility analysis, the claims are not sufficient to amount to significantly more than the judicial exception because nothing in the asserted claims purports to improve the functioning of the computer itself or effect an improvement in any other technology or technical field. The claim(s) is/are directed to the abstract idea of determine whether an article is present in a plurality of rack storage areas and comparing the presence of the article in the plurality of rack storage areas with a rack inventory status stored in a database, which is considered to be a mental process. This is a mental process (see MPEP 2106.04(a)(2)(III)) similar to collecting and comparing known information, which is an abstract idea, (see Classen Immunotherapies Inc. v. Biogen IDEC, 659 F.3d 1057 (Fed. Cir. 2011)). It is also similar to collecting information, analyzing it, and displaying certain results of the collection and analysis, (see Electric Power Group, LLC v. Alstom, 830 F.3d 1350 (Fed. Cir. 2016)). In this case a human can easily determine whether an article is present in a plurality of rack storage areas and comparing the presence of the article in the plurality of rack storage areas with a rack inventory status stored in a database. This is similar to collecting and comparing known information (claim 1), which are steps that can be practically performed in the human mind, Classen Immunotherapies, Inc. v. Biogen IDEC, 659 F.3d 1057, 1067, 100 USPQ2d 1492, 1500 (Fed. Cir. 2011)(See also "comparing BRCA sequences and determining the existence of alterations," where the claims cover any way of comparing BRCA sequences such that the comparison steps can practically be performed in the human mind, University of Utah Research Foundation v. Ambry Genetics, 774 F.3d 755, 763, 113 USPQ2d 1241, 1246 (Fed. Cir. 2014) (see MPEP 2106.04(a)(2)).
Claim(s) 4 and 15-17 are also directed to the abstract idea of “generating an object recognition rate that is a ratio of a size defined by a corresponding edge to a size of a rack storage area in an initial state of each of the plurality of rack storage areas”. This falls under MPEP 2106.04(a)(2), Abstract Idea Groupings, I. MATHEMATICAL CONCEPTS, A. Mathematical Relationships, “iv. organizing information and manipulating information through mathematical correlations, Digitech Image Techs., LLC v. Electronics for Imaging, Inc., 758 F.3d 1344, 1350, 111 USPQ2d 1717, 1721 (Fed. Cir. 2014). The patentee in Digitech claimed methods of generating first and second data by taking existing information, manipulating the data using mathematical functions, and organizing this information into a new form. The court explained that such claims were directed to an abstract idea because they described a process of organizing information through mathematical correlations, like Flook's method of calculating using a mathematical formula. 758 F.3d at 1350, 111 USPQ2d at 1721”. Here the claims recite a number of abstract mathematical concepts such as: generating an object recognition rate; determining that the article… is present when the recognized edge …is maintained for a predetermined period of time, calculating an object recognition rate, etc.
The additional element(s) or combination of elements in the claim(s) other than the abstract
idea per se include: a camera, computing device, logistics management server, processor, a plurality of rack storage areas, a worker terminal or administrator terminal, CCTV, etc. This amount(s) to no more than implementing the abstract idea on a generic computer system, (see MPEP 2106.04(a)(2)(III)(C)(1)). Therefore, claim(s) 1-20 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by MARQUETTE, EP 3651091 A1.
A rack inventory tracking system comprising:
a camera configured to acquire an image of a rack, (see Marquette, “it is also possible to use abstract information for identification of the storage area, such as, for example, an outline that can be detected by a camera, which can be recognized using methods of automatic image recognition and can be used to identify the storage area”);
a computing device configured to receive the image from the camera, distinguish a plurality of rack storage areas in the image, and perform object recognition on the plurality of rack storage areas to determine whether an article is present in the plurality of rack storage areas, (see Marquette, “the determination device can be designed to determine at least a part of the storage areas and / or at least a part of the stored goods by means of image recognition based on image data captured by the at least one camera, in particular using the storage area identification devices and / or the stored goods identification devices”); and
a logistics management server configured to perform inventory tracking on the plurality of rack storage areas by comparing the presence of the article in the plurality of rack storage areas, (see Marquette, “The detection device, which detects stored goods and / or storage areas”) with a rack inventory status stored in a database, (see Marquette, “The warehouse management system 100 can be scaled as desired and can dynamically record and track changes in the inventory”; “Using a simple database query, the position and the storage area of the stored goods can be determined and, for example, a robot for transporting the identified and queried stored goods can be directed to a further processing point”).
2. The rack inventory tracking system of claim 1, wherein the computing device includes: a processor configured to set an initial image for an initial state where there is no article in the rack as a master image, and recognize the rack in the master image to set a zone to be used for storing the article, (see Marquette, “The detection device, which detects stored goods and / or storage areas, can also detect the absence of one or more stored goods in one storage area”)(emphasis added).
3. The rack inventory tracking system of claim 2, wherein the processor sets the plurality of rack storage areas by dividing the zone into a plurality of areas, and performs edge recognition on the zone by using image data received from the camera at predetermined monitoring intervals, and determines which of the plurality of rack storage areas the recognized edge corresponds to, (see Marquette, “use abstract information for identification of the storage area, such as, for example, an outline that can be detected by a camera, which can be recognized using methods of automatic image recognition and can be used to identify the storage area”). An outline that can be detected by a camera, which can be recognized, is a form of “recognized edge” as claimed.
4. The rack inventory tracking system of claim 3, wherein the processor generates an object recognition rate that is a ratio of a size defined by a corresponding edge to a size of each rack storage area in an initial state of each of the plurality of rack storage areas, and determines that the article is present in each of the rack storage areas when the object recognition rate within each rack storage area is equal to or greater than a predetermined threshold, and determines that the article is not present in each of the rack storage areas when the object recognition rate is less than a predetermined threshold, (see Marquette, “the predetermined reordering event may indicate a sensorially recorded decrease in a number of remaining stored goods 102 an assigned storage area 104 below a predetermined threshold”)(emphasis added). A sensorially recorded decrease is considered to be a form of the “object recognition rate” as claimed.
5. The rack inventory tracking system of claim 3, wherein the processor determines that the article is present in any one of the plurality of rack storage areas when the recognized edge corresponding to the one of the plurality of rack storage areas is maintained for a predetermined period of time, (see Marquette, “the term "warehouse management system" can be understood to mean, in particular, a fully or partially automated and preferably network-based arrangement of entities or nodes that are preferably coupled or can be coupled with one another and that have a stock of warehouse goods at or in warehouse areas that exists at a certain point in time qualitatively and / or quantitatively and can determine corresponding position information and assignment information of stored goods and storage areas”)(emphasis added).
6. The rack inventory tracking system of claim 3, wherein the processor calculates an object recognition rate in each rack storage area for the recognized edge when the recognized edge is located over two rack storage areas of the plurality of rack storage areas, and determines that the article is present in the rack storage area of the two rack storage areas with a higher object recognition rate, (see Marquette, “the determination device can be designed to determine at least a part of the storage areas and / or at least a part of the stored goods by means of image recognition based on image data captured by the at least one camera, in particular using the storage area identification devices and / or the stored goods identification devices. As a basis for the image recognition carried out, the determination device can fall back on a database in which sample data of expected storage areas and / or storage goods can be stored. The determining device can then search for corresponding patterns on the captured images and thereby identify storage areas and / or stored goods”). For example, if a product spanned two storage areas, the system camera could detect a barcode in one of the two occupied storage areas and assign the barcoded item to that one storage area.
7. The rack inventory tracking system of claim 1, wherein the logistics management server: compares an article recognition result received from the computing device with the rack inventory status stored in the database, determines that the rack inventory status is normally tracked when the article recognition result received from the computing device matches the rack inventory status stored in the database as a result of the comparison, and notifies a terminal of a worker who has performed work on the mismatched rack storage area of a work error when the article recognition result received from the computing device does not match the rack inventory status stored in the database as a result of the comparison, (see Marquette, “error-proof and simple management of even highly complex warehouses with many different goods 102 and many different storage areas 104 is possible. The warehouse management system 100 can be scaled as desired and can dynamically record and track changes in the inventory. User activity can optionally be entered into the warehouse management system 100 via the portable user interface 116. Furthermore, the warehouse management system 100 can operate particularly error-proof in view of the described operation”). An error is a form of “mismatch” as claimed. User activity is a type of “performed work” as claimed.
8. The rack inventory tracking system of claim 7, wherein the logistics management server stores a work error history for each worker, and notifies an administrator terminal of a repeat of a work error of a specific worker when the specific worker repeats a work error a predetermined number of times or more, “User activity can optionally be entered into the warehouse management system 100 via the portable user interface 116. Furthermore, the warehouse management system 100 can operate particularly error-proof in view of the described operation”).
9. The rack inventory tracking system of claim 1, wherein the logistics management server receives, from the computing device, object recognition for a first rack storage area based on a change in state of the first rack storage area where the article is not present, receives article information corresponding to an object through a worker terminal, and checks whether the received article information is information about the article to be stocked stored in a database of the logistics management server, and whether a stocking location matched to the article to be stocked in the database matches a location of the first rack storage area, (see Marquette, “the presence of a reorder event can be detected by means of the detection device. The detection device, which detects stored goods and / or storage areas, can also detect the absence of one or more stored goods in one storage area. For example, the detection device can detect that all stored goods in a storage area are out of stock or that the remaining quantity of stored goods in the storage area is below a predetermined threshold value. If this has been detected (for example optically), can this will be reported to the reorder facility. A person responsible for the reorder can then trigger the reorder”). Out of stock status based on the detected absence of a stored good is a “change in state” as claimed.
10. The rack inventory tracking system of claim 9, wherein: the logistics management server notifies a worker terminal or administrator terminal of a worker who performed stocking work of a failure of the stocking work when the stocking location does not match the location of the first rack storage area, (see Marquette, “a stock of warehouse goods at or in warehouse areas that exists at a certain point in time qualitatively and / or quantitatively and can determine corresponding position information and assignment information of stored goods and storage areas. In particular, such a warehouse management system can optionally - for example automatically and / or user-controlled - trigger reorders of warehouse goods.”). Anything resulting in the remaining quantity of stored goods in the storage area falling below a predetermined threshold value is considered to be a type of “failure of the stocking work when the stocking location does not match the location of the first rack storage area” because a person responsible for the reorder, i.e. “worker”, can then trigger the reorder and restock the goods.
11. The rack inventory tracking system of claim 9, wherein the logistics management server: instructs the worker terminal, the camera attached to equipment, or a CCTV located proximate to the stocking location to photograph a rack storage area corresponding to the stocking location and transmit the photographed rack storage area to the computing device, and receives a result of determining whether the object is recognized for the first rack storage area from the computing device, (see Marquette, “an outline that can be detected by a camera, which can be recognized using methods of automatic image recognition and can be used to identify the storage area”).
Claims 12-20 contain the same or similar features as claims 1-11 rejected above, and therefore the remaining claims are rejected on the same basis and rationale as those above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: DE-102013222263-A1, WO-2017175301-A1, US-20200143315-A1, US-11014745-B2, and US-8630924-B2.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RUSSELL S GLASS whose telephone number is (571)272-7285. The examiner can normally be reached M-F, 9-5.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, FLORIAN ZEENDER can be reached at 571-272-6790. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/RUSSELL S GLASS/Primary Examiner, Art Unit 3627
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