CTNF 18/891,546 CTNF 88766 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 Objections Claim 1 is objected to because of the following informalities: the limitation “for detection protective equipment” is recited. Claim 4 is objected to because of the following informalities: the limitation “personal protectively equipment” is recited. 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. Claim 20 is directed to “one or more computer-readable storage media”. However, the claim is not limited to nontransitory embodiments, and the specification does not provide a definition limiting the meaning of this term to only nontransitory embodiments (see [0065] in the specification: “ As an example , a processor-readable medium may be a computer-readable storage medium that is not a signal and that is not a carrier wave.”). The claim therefore can be reasonably interpreted as encompassing transitory signal embodiments, which are nonstatutory (In re Nuijten, 500 F.3d 1346, 84 USPQ2d 1495 (Fed. Cir. 2007)). If the specification includes written description support, this rejection can be overcome by including the term “nontransitory” in the claim (see USPTO Official Gazette notice 1351 OG 212.). 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 – 07-08-aia AIA (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. 07-15-aia AIA Claim(s) 1-5 and 7-20 is/are rejected under 35 U.S.C. 102 (a)(1) as being anticipated by Ji et al. ( Ahigh-performance framework for personal protective equipment detection on the offshore drilling platform , 30 March 2023, Complex & Intelligent Systems, Vol. 9, Pages 5637-5652), hereinafter “ Ji ” . Regarding claim 1, Ji teaches: A method (See the Abstract.) comprising: receiving imagery data from a wellsite (See the input surveillance image of an offshore drilling platform in Figs. 1-2.) ; analyzing the imagery data for detection personal protective equipment (See the feature classification in Fig. 1.) ; determining a risk to a human at the wellsite based on the analyzing (See the “PHW” (worker is wearing both a helmet and workwear), “PH” (worker is only wearing a helmet), “PW” (worker is only wearing workwear), and “P” (worker is wearing neither a helmet nor workwear) results of feature classification in Fig. 1.) ; and responsive to the determining, issuing an instruction to reduce the risk (See page 5651, left column: “The framework can detect workers who are not wearing helmets or workwear in time and generate alarm messages .”) . Regarding claim 2, Ji teaches: The method of claim 1, wherein the analyzing comprises implementing a detector and implementing a classifier (See page 5639, right column: “Of which, the object detection part is to identify and locate the person, helmet and workwear targets by the proposed RFA-YOLO algorithm, then outputs the class and the bounding box coordinate information;”.) . Regarding claim 3, Ji teaches: The method of claim 2, wherein the detector detects a portion of a human body and wherein the classifier determines whether the portion of the human body has personal protective equipment (See page 5639, right column: “Of which, the object detection part is to identify and locate the person, helmet and workwear targets by the proposed RFA-YOLO algorithm, then outputs the class and the bounding box coordinate information;”.) . Regarding claim 4, Ji teaches: The method of claim 3, wherein the classifier determines a type of personal protectively equipment (See PHW, PH, PW, and P in Fig. 1.) . Regarding claim 5, Ji teaches: The method of claim 1, wherein the determining determines whether the human is wearing a type of personal protective equipment or is not wearing the type of personal protective equipment (See PHW, PH, and PW as opposed to P in Fig. 1.) . Regarding claim 7, Ji teaches: The method of claim 1, wherein the determining comprises implementing a pose estimator that distinguishes the human from one or more other humans (See page 5638, left column: “In addition, our further processing of the object detection results can satisfy the PPE detection under complex postures and can accurately identify the behavior of abnormal helmet wearing such as holding helmets.”) . Regarding claim 8, Ji teaches: The method of claim 1, wherein the determining comprises implementing a comparator that compares results of the analyzing to proscribed personal protective equipment (See page 5641, right column: “First, we propose an object matching mechanism to pair the person, safety helmet, and workwear according to the intersection ratio size of the bounding boxes.”) . Regarding claim 9, Ji teaches: The method of claim 8, wherein the proscribed personal protective equipment depends on one or more of a role of the human and a location of the human at the wellsite (See page 5651, left column: “However, there are still limitations of the proposed frame work in this paper, for example, in practical application scenarios, a few workers’ heads or torsos are partially obscured by pipes during operation, which makes the method in this paper unable to accurately identify the PPE wearing situation; in extreme weather such as fog and heavy rain at sea, the workers in the monitoring screen are blurred, which leads to the inability to accurately locate and identify the workers and also reduces the PPE detection accuracy.” A human having a worker role is detected, but the detection of the PPE depends on whether or not the worker is obscured by pipes in a complex environment/location.) . Regarding claim 10, Ji teaches: The method of claim 9, wherein the analyzing comprises detecting one or more of the role of the human and the location of the human (See the categories of targets in Fig. 1.) . Regarding claim 11, Ji teaches: The method of claim 1, wherein the analyzing comprises detecting more than one type of personal protective equipment (See the detection of helmets and workwear in Fig. 1.) . Regarding claim 12, Ji teaches: The method of claim 1, wherein the personal protective equipment (PPE) comprises one or more of eye PPE, ear PPE, respiratory PPE, clothing PPE, head PPE, face PPE, hand PPE, and foot PPE (See the “PHW” (worker is wearing both a helmet and workwear), “PH” (worker is only wearing a helmet), “PW” (worker is only wearing workwear), and “P” (worker is wearing neither a helmet nor workwear) results of feature classification in Fig. 1.) . Regarding claim 13, Ji teaches: The method of claim 1, wherein one or more of the analyzing and the determining comprise implementing at least one machine learning model (See the YOLOv4 network in Fig. 2.) . Regarding claim 14, Ji teaches: The method of claim 13, wherein the at least one machine learning model comprises an object detection model (See the RFA-YOLO model in Fig. 1.) . Regarding claim 15, Ji teaches: The method of claim 13, wherein the at least one machine learning model comprises an object classification model (See the feature classification in Fig. 1.) . Regarding claim 16, Ji teaches: The method of claim 13, wherein the at least one machine learning model comprises an object localization model (See page 5640, left column: “To improve the localization and recognition accuracy of the person, helmet, and workwear, we propose the RFA-YOLO algorithm based on the residual feature augmentation (RFA)module[38]withYOLOv4[39] as the baseline.”) . Regarding claim 17, Ji teaches: The method of claim 13, wherein the at least one machine learning model comprises a you-only-look-once (YOLO) model (See the YOLOv4 network in Fig. 2.) . Regarding claim 18, Ji teaches: The method of claim 17, wherein the YOLO model performs at least object detection and object classification (See detection and classification in Fig. 1.) . Ji teaches the system of claim 19 for the reasons given in the treatment of claim 1. Ji teaches the system of claim 20 for the reasons given in the treatment of claim 1 . Claim Rejections - 35 USC § 103 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. 07-23-aia AIA 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. 07-21-aia AIA Claim (s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ji ( Ahigh-performance framework for personal protective equipment detection on the offshore drilling platform , 30 March 2023, Complex & Intelligent Systems, Vol. 9, Pages 5637-5652) in view of Emimi et al. ( The Current Opportunities and Challenges in Drone Technology , 20 July 2023, IJEES, Pages 74-89), hereinafter “ Emimi ” . Claim 6 is met by the combination of Ji and Emimi, wherein Ji teaches: The method of claim 1, wherein the issuing comprises Ji does not disclose the following; however, Emimi suggests: instructing a drone to transport a type of personal protective equipment to the human… (See page 75: “In the context of the COVID-19 pandemic, drones have exhibited their capacity to deliver personal protective equipment (PPE), test kits, vaccines, medications, and laboratory samples. Moreover, drones can facilitate automated inspections to ensure compliance with social distancing protocols in public spaces, thus aiding in the management of the pandemic.”) . Ji and Emimi together partly disclose the limitations of claim 6. Emimi is directed to a similar field of art (ensuring compliance to safety protocols by inspections and by transproting PPE). Therefore, Ji and Emimi are combinable. Modifying the system and method of Ji by adding the capability of “instructing a drone to transport a type of personal protective equipment to the human”, as taught by Emimi, would yield the expected and predictable result of swift delivery of PPE in emergency situations. Although Emimi does not appear to describe drone delivery of PPE in the context of “at the wellsite”, one of ordinary skill in the art would recognize the flexibility of drone navigation through a variety of environments. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine Ji and Emimi to meet “instructing a drone to transport a type of personal protective equipment to the human at the wellsite“. Contact Any inquiry concerning this communication or earlier communications from the examiner should be directed to JONATHAN S LEE whose telephone number is (571)272-1981. The examiner can normally be reached 11:30 AM - 7:30 PM. 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, Andrew Bee can be reached at (571)270-5183. 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. /Jonathan S Lee/Primary Examiner, Art Unit 2677 Application/Control Number: 18/891,546 Page 2 Art Unit: 2677 Application/Control Number: 18/891,546 Page 3 Art Unit: 2677 Application/Control Number: 18/891,546 Page 4 Art Unit: 2677 Application/Control Number: 18/891,546 Page 5 Art Unit: 2677 Application/Control Number: 18/891,546 Page 6 Art Unit: 2677 Application/Control Number: 18/891,546 Page 7 Art Unit: 2677 Application/Control Number: 18/891,546 Page 8 Art Unit: 2677 Application/Control Number: 18/891,546 Page 9 Art Unit: 2677 Application/Control Number: 18/891,546 Page 10 Art Unit: 2677
Prosecution Insights