Prosecution Insights
Last updated: April 17, 2026
Application No. 18/443,816

METHOD AND SYSTEM FOR MONITORING THE OCCUPANCY OF A STRUCTURE

Non-Final OA §103§112
Filed
Feb 16, 2024
Examiner
CESE, KENNY A
Art Unit
2663
Tech Center
2600 — Communications
Assignee
unknown
OA Round
1 (Non-Final)
75%
Grant Probability
Favorable
1-2
OA Rounds
2y 11m
To Grant
86%
With Interview

Examiner Intelligence

Grants 75% — above average
75%
Career Allow Rate
517 granted / 687 resolved
+13.3% vs TC avg
Moderate +10% lift
Without
With
+10.3%
Interview Lift
resolved cases with interview
Typical timeline
2y 11m
Avg Prosecution
48 currently pending
Career history
735
Total Applications
across all art units

Statute-Specific Performance

§101
9.2%
-30.8% vs TC avg
§103
54.5%
+14.5% vs TC avg
§102
12.2%
-27.8% vs TC avg
§112
22.1%
-17.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 687 resolved cases

Office Action

§103 §112
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 Objections Claims 2, 11 are objected to because of the following informalities: “plurality of camera arranged at different location.” Appropriate correction is required. 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. The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention. Claims 1 and 11 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Dependent claims 2-10 and 12-20 are rejected based on their dependency. The claims initially state identifying a single person and then states multiple persons. “identify whether the object is a person; associate a unique tracker with each identified person; keep track of the identified people in the structure; calculate a load on the structure based on an attribute of each person;” 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. 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. Claims 1, 3-9, 11, 13-19 are rejected under 35 U.S.C. 103 as being unpatentable over Sternitzke (US 2023/0039466) in view of Choi et al. (US 2021/0154843). Regarding claim 1, Sternitzke teaches a system for monitoring occupancy of a structure, comprising: at least one camera configured to acquire an image of the structure (see para. 003); processor circuitry coupled with a memory configured to process the image (see para. 0105, 0106, Sternitzke discusses capturing images and determining the number of persons in an elevator); and an output device; wherein, in order to process the image, the processor circuitry is configured to: detect an object in the image (see para. 0105, 0106, Sternitzke discusses capturing images and determining the number of persons in an elevator); extract one or more features of the object (see para. 0105-0106, 0156, Sternitzke discusses Convolutional Neural Network to generate a feature vector of detected objects and determining dimensions of persons); identify whether the object is a person (see para. 0105-0106, Sternitzke discusses determining dimensions of persons); associate a unique tracker with each identified person (see para. 0105, Sternitzke discusses a Convolutional Neural Network to generate a feature vector of detected objects); keep track of the identified people in the structure (see para. 0105, Sternitzke discusses a Convolutional Neural Network to track objects in regions); calculate a load on the structure based on an attribute of each person; (see para. 0105-0106, 0131, Sternitzke discusses determining a payload weight and determine their total weight by adding up the weight of each person). Sternitzke does not expressly disclose instruct the output device to generate an output signal when the calculated load reaches a predetermined threshold. However, Choi teaches instruct the output device to generate an output signal when the calculated load reaches a predetermined threshold (see para. 0154, Choi discusses an elevator detects a total weight of a passenger and object in the elevator (load weight). The elevator control device may limit boarding of an additional passenger or object when the load weight detected by the sensor reaches a preset threshold weight). Motivation to combine may be gleaned from the prior art considered. It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify the invention of Sternitzke with Choi to derive at the invention of claim 1. The result would have been expected, routine, and predictable in order to perform overweight payload detection. The determination of obviousness is predicated upon the following: One skilled in the art would have been motivated to modify Sternitzke in this manner in order to improve overweight payload detection by implementing a threshold used to determine when total weight of detected object reaches the maximum payload of a platform surface. Furthermore, the prior art collectively includes each element claimed (though not all in the same reference), and one of ordinary skill in the art could have combined the elements in this manner explained using known engineering design, interface and/or programming techniques, without changing a fundamental operating principle of Sternitzke, while the teaching of Choi continues to perform the same function as originally taught prior to being combined, in order to produce the repeatable and predictable result of using a weight threshold and calculating weight of objects to determine whether a maximum payload weight is met. The Sternitzke and Choi systems perform object weight detection, therefore one of ordinary skill in the art would have reasonable expectation of success in the combination. It is for at least the aforementioned reasons that the examiner has reached a conclusion of obviousness with respect to the claim in question. Regarding claim 3, Sternitzke teaches wherein the one or more features comprise human features (see para. 0105, Sternitzke discusses a Convolutional Neural Network to generate a feature vectors of detected objects and determine the dimensions of persons). The same motivation of claim 1 is applied to claim 3. Motivation to combine may be gleaned from the prior art considered. It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify the invention of Sternitzke with Choi to derive at the invention of claim 3. The result would have been expected, routine, and predictable in order to perform overweight payload detection. Regarding claim 4, Sternitzke teaches wherein each unique tracker comprises meta-data associated with the corresponding person (see para. 0105-0106, Sternitzke discusses a Convolutional Neural Network to generate a feature vectors of detected objects, determining dimensions of persons, and estimating weight of each person). The same motivation of claim 1 is applied to claim 4. Motivation to combine may be gleaned from the prior art considered. It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify the invention of Sternitzke with Choi to derive at the invention of claim 4. The result would have been expected, routine, and predictable in order to perform overweight payload detection. Regarding claim 5, Sternitzke teaches wherein the meta-data comprises physical attributes of the person (see para. 0105-0106, Sternitzke discusses estimating weight of each person). The same motivation of claim 1 is applied to claim 5. Motivation to combine may be gleaned from the prior art considered. It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify the invention of Sternitzke with Choi to derive at the invention of claim 5. The result would have been expected, routine, and predictable in order to perform overweight payload detection. Regarding claim 6, Sternitzke teaches wherein the physical attributes include an estimated weight of the person (see para. 0105-0106, Sternitzke discusses estimating weight of each person). The same motivation of claim 1 is applied to claim 6. Motivation to combine may be gleaned from the prior art considered. It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify the invention of Sternitzke with Choi to derive at the invention of claim 6. The result would have been expected, routine, and predictable in order to perform overweight payload detection. Regarding claim 7, Sternitzke teaches wherein the to keep track of the identified people comprises to count the number of people currently in the structure and to adjust the number when a new person enters the structure, a person leaves the structure, or a person who has left the structure re-enters the structure (see para. 0105-0106, Sternitzke discusses estimating weight of each person to calculate the total weight in the structure, therefore if a person leaves the total calculation is affected). The same motivation of claim 1 is applied to claim 7. Motivation to combine may be gleaned from the prior art considered. It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify the invention of Sternitzke with Choi to derive at the invention of claim 7. The result would have been expected, routine, and predictable in order to perform overweight payload detection. Regarding claim 8, Sternitzke teaches wherein the processor circuitry is configured to execute a machine learning tool program code (see para. 0105-0106, Sternitzke discusses a Convolutional Neural Network to generate a feature vectors of detected objects, determining dimensions of persons, and estimating weight of each person). The same motivation of claim 1 is applied to claim 8. Motivation to combine may be gleaned from the prior art considered. It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify the invention of Sternitzke with Choi to derive at the invention of claim 8. The result would have been expected, routine, and predictable in order to perform overweight payload detection. Regarding claim 9, Sternitzke teaches wherein the machine learning tool is implemented as a deep neural network transformer for real-time video analytics, feature extraction, object detection, and tracking (see para. 0105-0106, Sternitzke discusses a Convolutional Neural Network to generate a feature vectors of detected objects, determining dimensions of persons, and estimating weight of each person). The same motivation of claim 1 is applied to claim 9. Motivation to combine may be gleaned from the prior art considered. It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify the invention of Sternitzke with Choi to derive at the invention of claim 9. The result would have been expected, routine, and predictable in order to perform overweight payload detection. Claim 11 is rejected as applied to claim 1 as pertaining to a corresponding method. Claim 13 is rejected as applied to claim 3 as pertaining to a corresponding method. Claim 14 is rejected as applied to claim 4 as pertaining to a corresponding method. Claim 15 is rejected as applied to claim 5 as pertaining to a corresponding method. Claim 16 is rejected as applied to claim 6 as pertaining to a corresponding method. Claim 17 is rejected as applied to claim 7 as pertaining to a corresponding method. Claim 18 is rejected as applied to claim 8 as pertaining to a corresponding method. Claim 19 is rejected as applied to claim 9 as pertaining to a corresponding method. Claims 2, 10, 12, 20 are rejected under 35 U.S.C. 103 as being unpatentable over Sternitzke (US 2023/0039466) in view of Choi et al. (US 2021/0154843) in view of Matsuzawa et al. (US 2023/0162533). Regarding claim 2, Sternitzke and Choi do not expressly disclose wherein the system comprises a plurality of camera arranged at different location and configured to acquire a plurality of images from different directions at the same time; and wherein the to process the image is based on the plurality of acquired images. However, Matsuzawa teaches wherein the system comprises a plurality of camera arranged at different location and configured to acquire a plurality of images from different directions at the same time; and wherein the to process the image is based on the plurality of acquired images (see figure 23, Matsuzawa discusses multiple cameras capturing images from different directions at the same time). Motivation to combine may be gleaned from the prior art considered. It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify the invention of Sternitzke and Choi with Matsuzawa to derive at the invention of claim 2. The result would have been expected, routine, and predictable in order to perform overweight payload detection. The determination of obviousness is predicated upon the following: One skilled in the art would have been motivated to modify Sternitzke and Choi in this manner in order to improve overweight payload detection by implementing a threshold used to determine when total weight of tracked objects using different cameras. Furthermore, the prior art collectively includes each element claimed (though not all in the same reference), and one of ordinary skill in the art could have combined the elements in this manner explained using known engineering design, interface and/or programming techniques, without changing a fundamental operating principle of Sternitzke and Choi, while the teaching of Matsuzawa continues to perform the same function as originally taught prior to being combined, in order to produce the repeatable and predictable result of using different cameras to detect and track objects and calculating weight of objects to determine whether a maximum payload weight is met. The Sternitzke, Choi, and Matsuzawa systems perform object detection, therefore one of ordinary skill in the art would have reasonable expectation of success in the combination. It is for at least the aforementioned reasons that the examiner has reached a conclusion of obviousness with respect to the claim in question. Regarding claim 10, Sternitzke and Choi do not expressly disclose wherein each of the unique tracker is stored in the memory until the person associated with the tracker leaves the structure. However, Matsuzawa teaches wherein each of the unique tracker is stored in the memory until the person associated with the tracker leaves the structure (see figure 8, Matsuzawa discusses deleting user ID data when a user associated with the user ID is detected leaving a facility). Motivation to combine may be gleaned from the prior art considered. It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify the invention of Sternitzke and Choi with Matsuzawa to derive at the invention of claim 10. The result would have been expected, routine, and predictable in order to perform overweight payload detection. The determination of obviousness is predicated upon the following: One skilled in the art would have been motivated to modify Sternitzke and Choi in this manner in order to improve overweight payload detection by implementing a threshold used to determine when total weight of tracked objects using stored object IDs. Furthermore, the prior art collectively includes each element claimed (though not all in the same reference), and one of ordinary skill in the art could have combined the elements in this manner explained using known engineering design, interface and/or programming techniques, without changing a fundamental operating principle of Sternitzke and Choi, while the teaching of Matsuzawa continues to perform the same function as originally taught prior to being combined, in order to produce the repeatable and predictable result of using different cameras to detect and track objects using objects identifiers. The Sternitzke, Choi, and Matsuzawa systems perform object detection, therefore one of ordinary skill in the art would have reasonable expectation of success in the combination. It is for at least the aforementioned reasons that the examiner has reached a conclusion of obviousness with respect to the claim in question. Claim 12 is rejected as applied to claim 2 as pertaining to a corresponding method. Claim 20 is rejected as applied to claim 10 as pertaining to a corresponding method. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Sverdlov et al. (US 2022/0089237) discusses detecting total weight of passengers and comparing the total weight to a predetermined value. Contact Information Any inquiry concerning this communication or earlier communications from the examiner should be directed to KENNY A CESE whose telephone number is (571) 270-1896. The examiner can normally be reached on Monday – Friday, 9am – 4pm. If attempts to reach the primary examiner by telephone are unsuccessful, the examiner’s supervisor, Gregory Morse can be reached on (571) 272-3838. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /Kenny A Cese/ Primary Examiner, Art Unit 2663
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Prosecution Timeline

Feb 16, 2024
Application Filed
Jan 08, 2026
Non-Final Rejection — §103, §112 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
75%
Grant Probability
86%
With Interview (+10.3%)
2y 11m
Median Time to Grant
Low
PTA Risk
Based on 687 resolved cases by this examiner. Grant probability derived from career allow rate.

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