Prosecution Insights
Last updated: April 19, 2026
Application No. 19/040,945

ENVIRONMENTAL INFORMATION COLLECTION DEVICE, ENVIRONMENTAL INFORMATION COLLECTION METHOD, AND RECORDING MEDIUM

Non-Final OA §101§102
Filed
Jan 30, 2025
Examiner
COBANOGLU, DILEK B
Art Unit
3687
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
NEC Corporation
OA Round
1 (Non-Final)
33%
Grant Probability
At Risk
1-2
OA Rounds
4y 9m
To Grant
61%
With Interview

Examiner Intelligence

Grants only 33% of cases
33%
Career Allow Rate
163 granted / 492 resolved
-18.9% vs TC avg
Strong +28% interview lift
Without
With
+27.9%
Interview Lift
resolved cases with interview
Typical timeline
4y 9m
Avg Prosecution
57 currently pending
Career history
549
Total Applications
across all art units

Statute-Specific Performance

§101
35.3%
-4.7% vs TC avg
§103
27.2%
-12.8% vs TC avg
§102
21.1%
-18.9% vs TC avg
§112
13.6%
-26.4% vs TC avg
Black line = Tech Center average estimate • Based on career data from 492 resolved cases

Office Action

§101 §102
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 . Claims 1-10 have been examined. 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 1-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Step 1: Claims 1-8 are drawn to a system which is within the four statutory categories (i.e. machine). Claim 9 is drawn to a method which is within the four statutory categories (i.e. process). Claim 10 is drawn to a non-transitory medium which is within the four statutory categories (i.e. manufacture). Step 2A, Prong 1: The independent claims 1, 9 and 10 recite: “…acquire user identification information for identifying a user; acquire first biometric information of the user; authenticate the user by comparing second biometric information associated with the user identification information with the first biometric information acquired; detect based on the first biometric information that the user is infected with the disease; acquire movement history information concerning each area through which the user passed, by using the user identification information; and output a collection request for requesting to collect environmental information concerning a state of each area through which the user passed” The limitations of “acquire user identification information”, “acquire first biometric information of the user”, “acquire movement history…” and “output a collection request…” correspond to mere data gathering (insignificant extra-solution activities, see the section below), and the limitations of “authenticate the user by comparing second biometric information associated with the user identification information with the first biometric information acquired” and “detect based on the first biometric information that the user is infected with the disease” correspond to an abstract idea of “certain methods of organizing human activity”. This is a method of managing interactions between people, such as user following rules and instructions. The mere nominal recitation of a generic processor and generic memory devices does not take the claims out of the methods of organizing human interactions grouping. The dependent claims also correspond to a method of managing interactions between people (a user following rules and instructions), such as, claim 4 recites “the processor specifies a symptom of the user based on the face image and the body temperature, calculates a probability that the user is infected with the disease, and detect presence of the disease in the user in a case where the probability is equal to or greater than a threshold value” and claim 7 recites “determine whether or not one or more of a shape and color of the facial area is abnormal, determine whether or not a body temperature of the user is equal to or greater than a threshold value, and determine whether or not an initial symptom has occurred based on the face image of the user … whether or not the initial symptom of the disease appearing on a face has occurred, in response to an input of the face image, wherein the processor specifies the symptom of the user based on respective results from determining whether or not one or more of the shape and the color of the facial area is abnormal, determining whether or not the body temperature of the user is equal to or greater than a threshold value, and determining whether or not the initial symptom has occurred, and calculates the probability that the user is infected with the disease”. These limitations correspond to “certain methods of organizing human activity”, with a recitation of generic computing device (a processor). The processor is described in the current speciation as a generic computing device. For instance, the specification recites “The processor 12 is a computer such as a CPU (Central Processing Unit) and controls the entire server 2 by executing programs prepared in advance. Incidentally, as the processor 12, the CPU, a GPU (Graphics Processing Unit), a DSP (Digital Signal Processor), a MPU (Micro Processing Unit), a FPU (Floating Point number Processing Unit), a PPU (Physics Processing Unit), a TPU (Tensor Processing Unit), a quantum processor, a microcontroller, or a combination thereof can be used.” in [0021]. The limitation of “determine whether or not an initial symptom has occurred based on the face image of the user by using a machine learning model trained to output whether or not the initial symptom of the disease appearing on a face has occurred, in response to an input of the face image” corresponds to performing mathematical calculations, therefore the limitation falls within the “mathematical concept” grouping of abstract ideas. After considering all claim elements, both individually and in combination and in ordered combination, it has been determined that the claims do not amount to significantly more than the abstract idea itself. Claims 2-8 are ultimately dependent from claim 1 and include all the limitations of claim 1. Therefore, claims 2-8 recite the same abstract idea. Claims 2-8 describe a further limitation regarding the basis for determining whether the user is infected with a disease. These are all just further describing the abstract idea recited in claim 1, without adding significantly more. Step 2A, Prong 2: This judicial exception is not integrated into a practical application. In particular, claims recite the additional elements of “at least one memory configured to store instructions”, “at least one processor”, using the generic processor to perform: “authenticating the user”, “detecting the user is infected with a disease, acquire movement history of the user and determining an outbreak”, “determine whether or not an initial symptom has occurred based on the face image of the user by using a machine learning model trained to output whether or not the initial symptom of the disease appearing on a face has occurred, in response to an input of the face image”. The processor in these steps is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of determining information based on acquired information) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea. Claims also recite other additional limitations beyond abstract idea, including functions such as acquiring data from/to a database, outputting data are insignificant extra-solution activities (see MPEP 2106.05 (g)), which do not provide a practical application for the abstract idea. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea. Step 2B: The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor to perform both the detecting and determining steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims are not patent eligible. Claim Rejections - 35 USC § 102 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. 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)(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. Claims 1-10 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Abdallah (US 2021/0327595 A1). Claim 1 recites an environmental information collection device comprising: at least one memory configured to store instructions (Abdallah; [0052]); and at least one processor (Abdallah; [0052]) configured to execute the instructions to: acquire user identification information for identifying a user (Abdallah discloses “…authenticating a user using at least one of the input devices…” in [0009]); acquire first biometric information of the user (Abdallah discloses “…capturing biometric data of the finger scanner input device…” in [0009]); authenticate the user by comparing second biometric information associated with the user identification information with the first biometric information acquired (Abdallah discloses “…safe pass authentication…verify that the bio data was collected from the same person that is currently holding the device using a combination of bio metrics and identity recognition…” in [0042]); detect based on the first biometric information that the user is infected with the disease (Abdallah discloses “…face can be used to verify the identity of the individual being analyzed through a face or eye recognition scheme in addition to being used to detect possible underlying illness / infection or health issues …” in [0040]); acquire movement history information concerning each area through which the user passed, by using the user identification information (Abdallah discloses “…The records include a time associated with a location , the location ( e.g. , coordinate data ) , devices in proximity to the individual's devices at the time , and any sensor data captured at the time . In FIG . 2A , the records of Individual B are kept private and anonymous . The records include a time associated with a location , the location ( e.g. , coordinate data ) , devices in proximity to the individuals a devices at the time , and any sensor data captured at the time …” in [0035]); and output a collection request for requesting to collect environmental information concerning a state of each area through which the user passed (Abdallah discloses “…tracking and tracing of potential contamination to other individuals who later are confirmed to be infected carriers of an infection in accordance with 3D location or enhanced GPS data …” in [0044]). Claim 2 recites the environmental information collection device according to the environmental information collection device according to wherein the environmental information collection device is connected to a satellite system, and the processor sends a request for capturing an image of each area through which the user passed, to the satellite system (Abdallah discloses “…tracking and tracing of potential contamination to other individuals who later are confirmed to be infected carriers of an infection in accordance with 3D location or enhanced GPS data …” in [0044]). Claim 3 recites the environmental information collection device according to the environmental information collection device according to wherein the environmental information is information of a state of each area and disease corresponding to the state of each area (Abdallah; [0041], [0044]). Claim 4 recites the environmental information collection device according to claim 1, wherein the biometric information includes a face image and a body temperature of the user; and the processor specifies a symptom of the user based on the face image and the body temperature, calculates a probability that the user is infected with the disease, and detect presence of the disease in the user in a case where the probability is equal to or greater than a threshold value (Abdallah; [0040], [0050]). Claim 5 recites the environmental information collection device according to the environmental information collection device according to further comprising a report storage unit configured to store report information in which the user identification information of an infected user for whom the presence of the disease is detected is associated with the symptom and the movement history information, wherein the processor outputs the collection request based on the report information (Abdallah; [0044]). Claim 6 recites the environmental information collection device according to the environmental information collection device according to wherein the processor is further configured to specify, based on the report information, an area where the infected user encountered a state leading to the disease as an outbreak region, wherein the processor outputs the collection request concerning the outbreak region (Abdallah; [0044]-[0045]). Claim 7 recites the environmental information collection device according to the environmental information collection device according to wherein in a case of detecting based on the first biometric information that the user is infected with the disease, the processor performs to determine whether or not one or more of a shape and color of the facial area is abnormal (Abdallah; [0050]), determine whether or not a body temperature of the user is equal to or greater than a threshold value (Abdallah; [0051]), and determine whether or not an initial symptom has occurred based on the face image of the user by using a machine learning model trained to output whether or not the initial symptom of the disease appearing on a face has occurred, in response to an input of the face image (Abdallah discloses “The personal mobile devices with the input ports , sensors , and software application are connected to a logically centralized ( but potentially physically distributed ) apparatus that employ artificial intelligence machine learning schemes to train its machine learning algorithms using large amounts of biological data collected through the device and system and to analyze , detect and eventually predict potential infections ( “ cases ” ) that can be then identified as a candidate for formal infection medical testing and medical attention.” in [0031]), wherein the processor specifies the symptom of the user based on respective results from determining whether or not one or more of the shape and the color of the facial area is abnormal, determining whether or not the body temperature of the user is equal to or greater than a threshold value, and determining whether or not the initial symptom has occurred, and calculates the probability that the user is infected with the disease (Abdallah; [0051]). Claim 8 recites the environmental information collection device according to the environmental information collection device according to wherein the processor outputs a collection request corresponding the symptom and a movement history of the user by using a machine learning model trained to output an optimized collection request in response to the symptom and the movement history of the user (Abdallah; [0031]). Claim 9 recites an environmental information collection method executed by an environmental information collection device, the environmental information collection method comprising: acquiring user identification information for identifying a user (Abdallah discloses “…authenticating a user using at least one of the input devices…” in [0009]); acquiring first biometric information of the user (Abdallah discloses “…capturing biometric data of the finger scanner input device…” in [0009]); authenticating the user by comparing second biometric information associated with the user identification information with the first biometric information acquired (Abdallah discloses “…safe pass authentication…verify that the bio data was collected from the same person that is currently holding the device using a combination of bio metrics and identity recognition…” in [0042]); detecting based on the first biometric information that the user is infected with the disease (Abdallah discloses “…face can be used to verify the identity of the individual being analyzed through a face or eye recognition scheme in addition to being used to detect possible underlying illness / infection or health issues …” in [0040]); acquiring movement history information concerning each area through which the user passed, by using the user identification information (Abdallah discloses “…The records include a time associated with a location , the location ( e.g. , coordinate data ) , devices in proximity to the individual's devices at the time , and any sensor data captured at the time . In FIG . 2A , the records of Individual B are kept private and anonymous . The records include a time associated with a location , the location ( e.g. , coordinate data ) , devices in proximity to the individuals a devices at the time , and any sensor data captured at the time …” in [0035]); and outputting a collection request for requesting to collect environmental information concerning a state of each area through which the user passed (Abdallah discloses “…tracking and tracing of potential contamination to other individuals who later are confirmed to be infected carriers of an infection in accordance with 3D location or enhanced GPS data …” in [0044]). Claim 10 recites a non-transitory computer-readable recording medium storing a program causing a computer to execute processing of: acquiring user identification information for identifying a user (Abdallah discloses “…authenticating a user using at least one of the input devices…” in [0009]); acquiring first biometric information of the user (Abdallah discloses “…capturing biometric data of the finger scanner input device…” in [0009]); authenticating the user by comparing second biometric information associated with the user identification information with the first bio metric information acquired (Abdallah discloses “…safe pass authentication…verify that the bio data was collected from the same person that is currently holding the device using a combination of bio metrics and identity recognition…” in [0042]); detecting based on the first biometric information that the user is infected with the disease (Abdallah discloses “…face can be used to verify the identity of the individual being analyzed through a face or eye recognition scheme in addition to being used to detect possible underlying illness / infection or health issues …” in [0040]); acquiring movement history information concerning each area through which the user passed, by using the user identification information (Abdallah discloses “…The records include a time associated with a location , the location ( e.g. , coordinate data ) , devices in proximity to the individual's devices at the time , and any sensor data captured at the time . In FIG . 2A , the records of Individual B are kept private and anonymous . The records include a time associated with a location , the location ( e.g. , coordinate data ) , devices in proximity to the individuals a devices at the time , and any sensor data captured at the time …” in [0035]); and outputting a collection request for requesting to collect environmental information concerning a state of each area through which the user passed (Abdallah discloses “…tracking and tracing of potential contamination to other individuals who later are confirmed to be infected carriers of an infection in accordance with 3D location or enhanced GPS data …” in [0044]). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to DILEK B COBANOGLU whose telephone number is (571)272-8295. The examiner can normally be reached 8:30-5:00 ET. 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, Obeid Mamon can be reached at (571) 270-1813. 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. /DILEK B COBANOGLU/Primary Examiner, Art Unit 3687
Read full office action

Prosecution Timeline

Jan 30, 2025
Application Filed
Mar 02, 2026
Non-Final Rejection — §101, §102 (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
33%
Grant Probability
61%
With Interview (+27.9%)
4y 9m
Median Time to Grant
Low
PTA Risk
Based on 492 resolved cases by this examiner. Grant probability derived from career allow rate.

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