CTNF 18/189,314 CTNF 86653 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia 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 § 101 07-04-01 AIA 07-04 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 8-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because neither a “computer-readable tangible storage medium” nor a “computer program product” are one of a process, a machine, a manufacture or a composition of matter. As Applicant’s specification describe storage media as a ”medium” for which machine readable code is stored thereon, where the medium can be transitory, i.e., is not explicitly limited as disclosed as only being non-transitory computer readable tangible storage medium or a non-transitory computer program product; therefore, fail(s) to fall within a statutory category of invention. Applicant’s specification later discloses a computer readable storage medium as not being directed to transitory signals, but the computer readable storage medium language differs from the claimed computer-readable tangible storage medium and computer program product. Applicant should note that adding “non-transitory” to the claim to limit a claimed computer-readable tangible storage medium or a computer program product to being statutory would be acceptable. Claim Rejections - 35 USC § 102 07-06 AIA 15-10-15 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. 07-07-aia AIA 07-07 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 – 07-12-aia AIA (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. 07-15-03-aia AIA Claim(s) 1-5, 8-12 and 15-19 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by McCann et al. (McCann; US Patent No. 11,699,250 B1) . As per claim 1, McCann discloses a processor-implemented method for generating a real-time virtualized traffic view, the method comprising: receiving real-time traffic data from one or more selected live traffic status inputs (col. 9, lines 31-38) ; identifying one or more objects comprised within the real-time traffic data (col. 9, lines 46-48) ; determining one or more traffic characteristics of the identified objects (col. 5, lines 28-30) ; converting classified real-time traffic data to one or more virtualized live traffic images (col. 9, lines 64-67; col. 10, lines 1-2) ; stitching the one or more virtualized live traffic images together to create a virtualized live traffic stream (col. 5, lines 10-12) ; and rendering the virtualized live traffic stream on a client device (col. 5, lines 1-16; col. 9, lines 16-45) . As per claim 2, McCann discloses the method of claim 1, further comprising: modifying the virtualized live traffic stream (col. 11, lines 45-51) . As per claim 3, McCann discloses the method of claim 2, wherein the modifying of the virtualized live traffic stream comprises rendering one or more highlighted objects in the virtualized live traffic stream in a current frame on the client device based on user preferences (col. 11, lines 45-51: determining optimal visual output based on detected user features, therefore provided a preferred output for the user) . As per claim 4, McCann discloses the method of claim 1, further comprising: classifying the real-time traffic data (col. 10, line 61- col. 11, line 3: determining a confidence level of the detected traffic data) . As per claim 5, McCann discloses the method of claim 1, wherein the virtualized live traffic stream may comprise a live video or a two-dimensional digital map (col. 9, lines 50-54) . As per claim 8, (see rejection of claim 1 above) a computer system for generating a real-time virtualized traffic view, the computer system comprising: one or more processors, one or more computer-readable memories, one or more computer- readable tangible storage medium, and program instructions stored on at least one of the one or more tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more memories (McCann, paragraph [0103]) , wherein the computer system is capable of performing a method comprising: receiving real-time traffic data from one or more selected live traffic status inputs; identifying one or more objects comprised within the real-time traffic data; determining one or more traffic characteristics of the identified objects; converting classified real-time traffic data to one or more virtualized live traffic images; stitching the one or more virtualized live traffic images together to create a virtualized live traffic stream; and rendering the virtualized live traffic stream on a client device. As per claim 9, (see rejection of claim 2 above) the computer system of claim 8, further comprising: modifying the virtualized live traffic stream. As per claim 10, (see rejection of claim 3 above) the computer system of claim 9, wherein the modifying of the virtualized live traffic stream comprises rendering one or more highlighted objects in the virtualized live traffic stream in a current frame on the client device based on user preferences. As per claim 11, (see rejection of claim 4 above) the computer system of claim 8, further comprising: classifying the real-time traffic data. As per claim 12, (see rejection of claim 5 above) the computer system of claim 8, wherein the virtualized live traffic stream may comprise a live video or a two-dimensional digital map. As per claim 15, (see rejection of claim 1 above) a computer program product for generating a real-time virtualized traffic view, the computer program product comprising: one or more computer-readable tangible storage medium and program instructions stored on at least one of the one or more tangible storage medium, the program instructions executable by a processor to cause the processor to perform a method (McCann, paragraph [0103]) comprising: receiving real-time traffic data from one or more selected live traffic status inputs; identifying one or more objects comprised within the real-time traffic data; determining one or more traffic characteristics of the identified objects; converting classified real-time traffic data to one or more virtualized live traffic images; stitching the one or more virtualized live traffic images together to create a virtualized live traffic stream; and rendering the virtualized live traffic stream on a client device. As per claim 16, (see rejection of claim 2 above) the computer program product of claim 15, further comprising: modifying the virtualized live traffic stream. As per claim 17, (see rejection of claim 3 above) the computer program product of claim 16, wherein the modifying of the virtualized live traffic stream comprises rendering one or more highlighted objects in the virtualized live traffic stream in a current frame on the client device based on user preferences. As per claim 18, (see rejection of claim 4 above) the computer program product of claim 15, further comprising: classifying the real-time traffic data. As per claim 19, (see rejection of claim 5 above) the computer program product of claim 15, wherein the virtualized live traffic stream may comprise a live video or a two-dimensional digital map . Claim Rejections - 35 USC § 103 07-06 AIA 15-10-15 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. 07-20-aia AIA 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. 07-21-aia AIA Claim (s) 6, 7, 13, 14 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over McCann in view of Krishna et al. (Krishna; US Pub No. 2023/0298467 A1) . As per claim 6, McCann teaches the method of claim 1. McCann does not expressly teach further comprising: a network of one or more internet of things devices collecting the real-time traffic data. Krishna teaches further comprising: a network of one or more internet of things devices collecting the real-time traffic data (paragraph [0089], lines 1-6) . It would have been obvious to one having ordinary skill in the art at the time the invention was effectively filed to implement the network of Internet-of-Things sensors as taught by Krishna, since Krishna states in paragraph [0089] that such a modification would result in a roadway messaging system for dispersing traffic data between a plurality of vehicles on a roadway. As per claim 7, McCann teaches the method of claim 1. McCann does not expressly teach wherein a live traffic status input comprises a network of one or more internet of things devices. Krishna teaches wherein a live traffic status input comprises a network of one or more internet of things devices (paragraph [0089]) . It would have been obvious to one having ordinary skill in the art at the time the invention was effectively filed to implement the network of Internet-of-Things sensors as taught by Krishna, since Krishna states in paragraph [0089] that such a modification would result in a roadway messaging system for dispersing traffic data between a plurality of vehicles on a roadway. As per claim 13, (see rejection of claim 6 above) the computer system of claim 8, further comprising: a network of one or more internet of things devices collecting the real-time traffic data. As per claim 14, (see rejection of claim 7 above) the computer system of claim 8, wherein a live traffic status input comprises a network of one or more internet of things devices. As per claim 20, (see rejection of claim 6 above) the computer program product of claim 15, further comprising: a network of one or more internet of things devices collecting the real-time traffic data . Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Miu (US Patent No. 11,112,498 B2): similar inventive concept Golov (US Pub No. 2021/0053489 A1): similar inventive concept Shapiro (US Pub No. 2013/0093583 A1): similar inventive concept Any inquiry concerning this communication or earlier communications from the examiner should be directed to NAOMI J SMALL whose telephone number is (571)270-5184. The examiner can normally be reached Monday-Friday 8:30AM-5PM. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Quan-Zhen Wang can be reached at 571-272-3114. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /NAOMI J SMALL/Primary Examiner, Art Unit 2685 Application/Control Number: 18/189,314 Page 2 Art Unit: 2685 Application/Control Number: 18/189,314 Page 3 Art Unit: 2685 Application/Control Number: 18/189,314 Page 4 Art Unit: 2685 Application/Control Number: 18/189,314 Page 5 Art Unit: 2685 Application/Control Number: 18/189,314 Page 6 Art Unit: 2685 Application/Control Number: 18/189,314 Page 7 Art Unit: 2685 Application/Control Number: 18/189,314 Page 9 Art Unit: 2685 Application/Control Number: 18/189,314 Page 10 Art Unit: 2685
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