DETAILED ACTION
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
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(s) 1-22 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more (See 2019 Update: Eligibility Guidance).
Independent Claim(s) 1 recites
obtaining wind prevailing conditions for a site;
obtaining sensor data information for the site;
processing the wind prevailing conditions and sensor data information
to
produce an event detection
and
record generation event;
storing the event detection and record event;
obtaining a facility map;
and
processing the facility map, the stored event detection, and record event
to
produce a potential source of emissions
[Mathematical Concepts – mathematical relationships; mathematical formulas or equations or mathematical calculation] and/or [Mental Processes - concepts performed in the human mind (including an observation, evaluation, judgement, opinion)].
Independent Claim(s) 11 recites
identifying a source of emissions for a given site,
obtaining wind prevailing conditions for the site;
obtaining sensor data information for the site;
processing the wind prevailing conditions and sensor data information
to
produce a detection
and
record generation event;
storing the detection and record event;
obtaining a facility map;
and
processing the facility map, the stored event detection, and record event
to
produce a potential source of emissions for the site
[Mathematical Concepts – mathematical relationships; mathematical formulas or equations or mathematical calculation] and/or [Mental Processes - concepts performed in the human mind (including an observation, evaluation, judgement, opinion)].
Independent Claim(s) 16 recites
developing an emissions spatial coverage map for a facility,
obtaining wind prevailing conditions for positions at the facility;
obtaining sensor data information for positions at the facility;
processing the wind prevailing conditions and sensor data information
to
produce the emissions spatial coverage map for the facility;
comparing the emissions spatial coverage map to a facility map;
and
determining if the emissions spatial coverage map encompasses a desired potential leak area for the facility map
[Mathematical Concepts – mathematical relationships; mathematical formulas or equations or mathematical calculation] and/or [Mental Processes - concepts performed in the human mind (including an observation, evaluation, judgement, opinion)].
Independent Claim(s) 17 recites
developing a spatial coverage map for a site,
obtaining wind prevailing conditions for a site;
obtaining sensor data information for the site;
establishing an objective function measure for the site;
processing the wind prevailing conditions and sensor data information
to
produce a wind realization for the site;
storing the wind realization for the site;
establishing a coverage measure evaluation for the site based on the wind realization;
determining when the objective measure function has been achieved for the coverage measure evaluation;
ending the method when the objective function measure is successfully achieved;
establishing the coverage measure for a given wind realization and subsequently,
establishing the mean coverage measure over all wind realizations then,
continuing an optimization of the mean coverage measure evaluation with the given set of wind realizations until the optimal objective function measure is achieved
[Mathematical Concepts – mathematical relationships; mathematical formulas or equations or mathematical calculation] and/or [Mental Processes - concepts performed in the human mind (including an observation, evaluation, judgement, opinion)].
In combination with Independent Claim(s) 1, 11, 16, 17, Claim(s) 2-10, 12-15, 18-22 recite(s)
obtaining at least one constraint;
and
using the at least one constraint with the solver.
the obtaining wind prevailing conditions for the site comprises
obtaining at least one of a wind speed, a wind direction, a weather for the site, a time, a temperature, a pressure, a humidity and historical information.
the sensor data information includes a sensor type.
the sensor data information includes a sensor global positioning satellite location.
the sensor data information includes sensor placement information.
the facility map comprises at least one of a site layout and a feasibility.
the at least one constraint included at least one imposed condition.
the processing the facility map, the stored event detection and record event to produce the potential source of emissions includes a location.
the processing the facility map, the stored event detection and record event to produce the potential source of emissions includes an emission rate.
the obtaining the prevailing wind conditions is through at least one of historical weather data and sensor data being generated at the site.
the objective function measure is a percentage of coverage of an area of the site.
a search and evaluation grid is established over a coverage area.
the search and evaluation grid establishes evaluation spaces and search spaces.
the evaluation spaces and search spaces are bounded by site constraints
[Mathematical Concepts – mathematical relationships; mathematical formulas or equations or mathematical calculation] and/or [Mental Processes - concepts performed in the human mind (including an observation, evaluation, judgement, opinion)].
This judicial exception is not integrated into a practical application. Limitations that are not indicative of integration into a practical application:
Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP § 2106.05(f)) (i.e. A method, comprising:);
Adding insignificant extra-solution activity to the judicial exception (see MPEP § 2106.05(g)) (i.e. generic data acquisition); or
Generally linking the use of the judicial exception to a particular technological environment or field of use (MPEP § 2106.05(h)).
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because looking at the additional elements as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. The additional elements simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 134 S. Ct. at 2359-60, 110 USPQ2d at 1984 (see MPEP § 2106.05(d)) (i.e. See Alice Corp. and cited references for evidence of additional elements (i.e., generic computer structure)).
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.
(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) 1-22 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by EICHENLAUB ET AL. (US 20230304982 A1) (hereinafter “EICHENLAUB”).
With respect to Claim(s) 1, EICHENLAUB teaches ‘a method of locating an emission source of a target substance at a site is disclosed. The method may include obtaining predicted substance concentrations of the target substance from a prediction model to generate a mapping of a weighted mean of the plurality of the predicted substance concentrations grouped in a predetermined number of feature groups. A simulated plume model is generated for each emission source present at the site to calculate representative circular normal distributions for each air quality monitor. By performing an analysis of the plurality of representative circular normal distributions in relation to the mapping, a target emission source is identified’ and the BRI of:
A method,
comprising:
obtaining wind prevailing conditions for a site (See, e.g., ¶ 0250; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46);
obtaining sensor data information for the site (See, e.g., Fig(s). 2, 24, 25, 34, 40-46);
processing the wind prevailing conditions and sensor data information to produce an event detection and record generation event (See, e.g., Fig(s). 2, 24, 25, 34, 40-46);
storing the event detection and record event (See, e.g., Fig(s). 2, 24, 25, 34, 40-46);
obtaining a facility map (See, e.g., Fig(s). 2, 24, 25, 34, 40-46);
and
processing the facility map, the stored event detection, and record event (See, e.g., Fig(s). 2, 24, 25, 34, 40-46)
to
produce a potential source of emissions (See, e.g., Fig(s). 2, 24, 25, 34, 40-46).
With respect to Claim(s) 11, EICHENLAUB teaches ‘a method of locating an emission source of a target substance at a site is disclosed. The method may include obtaining predicted substance concentrations of the target substance from a prediction model to generate a mapping of a weighted mean of the plurality of the predicted substance concentrations grouped in a predetermined number of feature groups. A simulated plume model is generated for each emission source present at the site to calculate representative circular normal distributions for each air quality monitor. By performing an analysis of the plurality of representative circular normal distributions in relation to the mapping, a target emission source is identified’ and the BRI of:
A method
for
identifying a source of emissions for a given site (See, e.g., Fig(s). 2, 24, 25, 34, 40-46),
comprising:
obtaining wind prevailing conditions for the site (See, e.g., ¶ 0250);
obtaining sensor data information for the site (See, e.g., Fig(s). 2);
processing the wind prevailing conditions and sensor data information to produce a detection and record generation event (See, e.g., Fig(s). 2, 24, 25);
storing the detection and record event (See, e.g., Fig(s). 2, 24, 25);
obtaining a facility map (See, e.g., Fig(s). 34);
and
processing the facility map, the stored event detection, and record event (See, e.g., Fig(s). 2, 24, 25, 34)
to
produce a potential source of emissions for the site (See, e.g., Fig(s). 2, 24, 25, 34).
With respect to Claim(s) 16, EICHENLAUB teaches ‘a method of locating an emission source of a target substance at a site is disclosed. The method may include obtaining predicted substance concentrations of the target substance from a prediction model to generate a mapping of a weighted mean of the plurality of the predicted substance concentrations grouped in a predetermined number of feature groups. A simulated plume model is generated for each emission source present at the site to calculate representative circular normal distributions for each air quality monitor. By performing an analysis of the plurality of representative circular normal distributions in relation to the mapping, a target emission source is identified’ and the BRI of:
A method
for
developing an emissions spatial coverage map for a facility (See, e.g., ¶ 0328, 0333; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46),
comprising:
obtaining wind prevailing conditions for positions at the facility (See, e.g., ¶ 0343; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46);
obtaining sensor data information for positions at the facility (See, e.g., Fig(s). 2, 24, 25, 34, 40-46);
processing the wind prevailing conditions and sensor data information (See, e.g., Fig(s). 2, 24, 25, 34, 40-46)
to
produce the emissions spatial coverage map for the facility (See, e.g., Fig(s). 2, 24, 25, 34, 40-46);
comparing the emissions spatial coverage map to a facility map (See, e.g., ¶ 0022; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46);
and
determining if the emissions spatial coverage map encompasses a desired potential leak area for the facility map (See, e.g., ¶ 0013; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46).
With respect to Claim(s) 17, EICHENLAUB teaches ‘a method of locating an emission source of a target substance at a site is disclosed. The method may include obtaining predicted substance concentrations of the target substance from a prediction model to generate a mapping of a weighted mean of the plurality of the predicted substance concentrations grouped in a predetermined number of feature groups. A simulated plume model is generated for each emission source present at the site to calculate representative circular normal distributions for each air quality monitor. By performing an analysis of the plurality of representative circular normal distributions in relation to the mapping, a target emission source is identified’ and the BRI of:
A method
for
developing a spatial coverage map for a site (See, e.g., ¶ 0328, 0333; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46),
comprising:
obtaining wind prevailing conditions for a site (See, e.g., ¶ 0343; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46);
obtaining sensor data information for the site (See, e.g., Fig(s). 2, 24, 25, 34, 40-46);
establishing an objective function measure for the site (See, e.g., ¶ 0206; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46);
processing the wind prevailing conditions and sensor data information (See, e.g., Fig(s). 2, 24, 25, 34, 40-46)
to
produce a wind realization for the site (See, e.g., ¶ 0206-0209; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46);
storing the wind realization for the site (See, e.g., Fig(s). 2, 24, 25, 34, 40-46);
establishing a coverage measure evaluation for the site based on the wind realization (See, e.g., Fig(s). 2, 24, 25, 34, 40-46);
determining when the objective measure function has been achieved for the coverage measure evaluation (See, e.g., ¶ 0206-0209; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46);
ending the method when the objective function measure is successfully achieved (See, e.g., ¶ 0206-0209; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46);
establishing the coverage measure for a given wind realization and subsequently (See, e.g., Fig(s). 31, 33),
establishing the mean coverage measure over all wind realizations (See, e.g., Fig(s). 31, 33)
then,
continuing an optimization of the mean coverage measure evaluation with the given set of wind realizations until the optimal objective function measure is achieved (See, e.g., Fig(s). 31, 33).
With respect to Claim(s) 2, the cited reference(s) of the parent claim(s) teaches the BRI of the parent claim(s).
EICHENLAUB further teaches the BRI of:
obtaining at least one constraint (See, e.g., ¶ 0177, 0184; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46);
and
using the at least one constraint with the solver (See, e.g., ¶ 0177, 0184; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46);.
With respect to Claim(s) 3, 12, the cited reference(s) of the parent claim(s) teaches the BRI of the parent claim(s).
EICHENLAUB further teaches the BRI of:
the obtaining wind prevailing conditions for the site comprises
obtaining at least one of a wind speed, a wind direction, a weather for the site, a time, a temperature, a pressure, a humidity and historical information (See, e.g., Fig(s). 2, 24, 25, 34, 40-46).
With respect to Claim(s) 4, 13, the cited reference(s) of the parent claim(s) teaches the BRI of the parent claim(s).
EICHENLAUB further teaches the BRI of:
the sensor data information includes a sensor type (See, e.g., ¶ 0147, 0215; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46).
With respect to Claim(s) 5, 14, the cited reference(s) of the parent claim(s) teaches the BRI of the parent claim(s).
EICHENLAUB further teaches the BRI of:
the sensor data information includes a sensor global positioning satellite location (See, e.g., ¶ 0147, 0215; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46).
With respect to Claim(s) 6, 15, the cited reference(s) of the parent claim(s) teaches the BRI of the parent claim(s).
EICHENLAUB further teaches the BRI of:
the sensor data information includes sensor placement information (See, e.g., ¶ 0147, 0215; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46).
With respect to Claim(s) 7, the cited reference(s) of the parent claim(s) teaches the BRI of the parent claim(s).
EICHENLAUB further teaches the BRI of:
the facility map comprises at least one of a site layout and a feasibility (See, e.g., ¶ 0096; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46).
With respect to Claim(s) 8, the cited reference(s) of the parent claim(s) teaches the BRI of the parent claim(s).
EICHENLAUB further teaches the BRI of:
the at least one constraint included at least one imposed condition (See, e.g., ¶ 0177, 0184; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46).
With respect to Claim(s) 9, the cited reference(s) of the parent claim(s) teaches the BRI of the parent claim(s).
EICHENLAUB further teaches the BRI of:
the processing the facility map, the stored event detection and record event to produce the potential source of emissions includes a location (See, e.g., Fig(s). 2, 24, 25, 34, 40-46).
With respect to Claim(s) 10, the cited reference(s) of the parent claim(s) teaches the BRI of the parent claim(s).
EICHENLAUB further teaches the BRI of:
the processing the facility map, the stored event detection and record event to produce the potential source of emissions includes an emission rate (See, e.g., ¶ 0234; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46).
With respect to Claim(s) 18, the cited reference(s) of the parent claim(s) teaches the BRI of the parent claim(s).
EICHENLAUB further teaches the BRI of:
the obtaining the prevailing wind conditions is through at least one of historical weather data and sensor data being generated at the site (See, e.g., ¶ 0250; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46).
With respect to Claim(s) 19, the cited reference(s) of the parent claim(s) teaches the BRI of the parent claim(s).
EICHENLAUB further teaches the BRI of:
the objective function measure is a percentage of coverage of an area of the site (See, e.g., ¶ 0150-0151; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46).
With respect to Claim(s) 20, the cited reference(s) of the parent claim(s) teaches the BRI of the parent claim(s).
EICHENLAUB further teaches the BRI of:
a search and evaluation grid is established over a coverage area (See, e.g., ¶ 0205, 0277; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46).
With respect to Claim(s) 21, the cited reference(s) of the parent claim(s) teaches the BRI of the parent claim(s).
EICHENLAUB further teaches the BRI of:
the search and evaluation grid establishes evaluation spaces and search spaces (See, e.g., ¶ 0205, 0277; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46).
With respect to Claim(s) 22, the cited reference(s) of the parent claim(s) teaches the BRI of the parent claim(s).
EICHENLAUB further teaches the BRI of:
the evaluation spaces and search spaces are bounded by site constraints (See, e.g., ¶ 0205, 0277; See also, e.g., Fig(s). 2, 24, 25, 34, 40-46).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RAYMOND NIMOX whose telephone number is (469)295-9226. The examiner can normally be reached Mon-Thu 10am-8pm CT.
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 SCHECHTER can be reached at (571) 272-2302. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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RAYMOND NIMOX
Primary Examiner
Art Unit 2857
/RAYMOND L NIMOX/Primary Examiner, Art Unit
Prosecution Insights