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 .
Status of the Application
Claims 1-20 are currently pending in this application.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 08/14/2024 was filed. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
The information disclosure statement (IDS) submitted on 02/18/2026 was filed. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 17-20 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 it is related to a signal per se. The claims do not define a non-transitory computer-readable storage media and is thus non-statutory for that reason (i.e., "When functional descriptive material is recorded on some non-transitory computer-readable medium it becomes structurally and functionally interrelated to the non- transitory medium and will be statutory in most cases since use of technology permits the function of the descriptive material to be realized"- Guidelines Annex IV).
Claim Rejections - 35 USC § 103
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 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.
Claim(s) 1-6, 9-14, and 17-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over STEPHEN CHRISTOPHER COLIN et al. (Hereafter, “Stephen”) [WO 2021/174291 A1].
In regard to claim 1, Stephen discloses a method of operating a computing system to predict an ignition potential of a lightning event ([00105] That is, described herein is a lightning ignition prediction system or process that utilises an artificial intelligence or machine learning system for predicting the probability of ignition following a lightning strike.), the method comprising: in the computing system ([00123] As a further example, the data and variables associated with a particular emergency response and emergency situation may be stored. This data may be analysed by a machine learning or artificial intelligence (Al) system to assess and adapt emergency responses for future emergency situations based on the analysis. The machine learning and/or Al may be carried out by the server or an alternative computing system in communication with the server.): obtaining data associated with the lightning event, wherein the data includes a location of the lightning event and one or more measurements of the lightning event captured by a sensor ([00485] One or more of the cameras on the sensing towers may pointed towards clouds in the sky to enable the system to capture and analyse images to resolve the location in the cloud where the lightning started, as well as the location where the lightning hit. The system may use the captured images to measure the path of the lightning.); identifying attributes of the lightning event based at least on the one or more measurements included in the data ([00485] The system may use the captured images to measure the path of the lightning. The determined path of the lightning may be used by the system to classify the lightning type and/or lightning shape based on the captured images.); and predicting the ignition potential of the lightning event based at least on the lightning event attributes and one or more environmental factors associated with the location ([00485] The path of lightning, lightning type (e.g. polarity) and/or lightning shape may be used to determine a probability of ignition of a fire. For example, an algorithm and/or machine learning system may be used to calculate the probability of ignition of a fire. [00486] Weather information (temperature, wind, humidity etc.) may also be obtained at the sensing towers. The weather information may be used as part of the algorithm and/or machine learning system to calculate the probability of ignition of a fire during lightning.).
It would have been obvious to one of ordinary skill in the art at the time of the invention to incorporate the different embodiments and examples of the method and system of Stephen in order to improve how emergency situations are detected, monitored, controlled or acted upon [See Stephen].
In regard to claim 2, the limitations of claim 1 have been addressed. Stephen discloses wherein the attributes of the lightning event comprise a time ([00548-00549] determination of time, [00485] duration implies time recorded), a duration ([00485] The duration of the lightning may also be measured to give a measure of the energy flowing.), the location ([00485] One or more of the cameras on the sensing towers may pointed towards clouds in the sky to enable the system to capture and analyse images to resolve the location in the cloud where the lightning started, as well as the location where the lightning hit.) , and intensity parameters of the lightning event ([00485] The system may use the captured images to measure the path of the lightning. The determined path of the lightning may be used by the system to classify the lightning type and/or lightning shape based on the captured images. The duration of the lightning may also be measured to give a measure of the energy flowing. That is, the longer the duration, the more energy may flow and the higher the probability of a lightning ignition. This may be factored into the algorithm and/or machine learning system to calculate the probability of ignition of a fire.).
In regard to claim 3, the limitations of claim 1 have been addressed. Stephen discloses wherein the one or more environmental factors associated with the location comprise at least one among fuels characteristics, weather data ([00486] Weather information (temperature, wind, humidity etc.) may also be obtained at the sensing towers. The weather information may be used as part of the algorithm and/or machine learning system to calculate the probability of ignition of a fire during lightning.), and topographical data ([00124] The server may also be arranged to receive environmental data. For example, this environmental data may be data associated with one or more of i) weather data, ii) terrain data, iii) infrastructure data, iv) vulnerable infrastructure data, v) vegetal location data, vi) stock and wildlife location data, and vii) historic lightning strike data.).
In regard to claim 4, the limitations of claim 1 have been addressed. Stephen discloses wherein the data comprises data from a space-based lightning detector ([0014] satellite lightning detection).
In regard to claim 5, the limitations of claim 1 have been addressed. Stephen discloses wherein the ignition potential comprises an indication of a potential of ignition at an area corresponding to the location ([00105] That is, described herein is a lightning ignition prediction system or process that utilises an artificial intelligence or machine learning system for predicting the probability of ignition following a lightning strike. The system is arranged to determine the probability of ignition based on one or more of: the determined type of lightning in the lightning strike; and the determined location of the lightning strike. [00485] One or more of the cameras on the sensing towers may pointed towards clouds in the sky to enable the system to capture and analyse images to resolve the location in the cloud where the lightning started, as well as the location where the lightning hit. The system may use the captured images to measure the path of the lightning. The determined path of the lightning may be used by the system to classify the lightning type and/or lightning shape based on the captured images. The path of lightning, lightning type (e.g. polarity) and/or lightning shape may be used to determine a probability of ignition of a fire.).
In regard to claim 6, the limitations of claim 1 have been addressed. Stephen discloses wherein the data comprises optical or infrared sensor data ([00419] Also disclosed is a system of observation (sensing) towers, located strategically across the area of control, whose purpose is to detect the location of fire ignitions or potential fire ignitions. The location can be determined by stereoscopic camera arrays and by triangulation, where such stereoscopic location and triangulation is achieved using techniques that include at least some of the following: a) Observations in the visual spectrum using arrays of cameras to identify characteristic visual signatures, such as lightning strikes, smoke and or flame; b) Observations in the infrared spectrum using arrays of infrared cameras to identify characteristic thermal signatures of fire ignitions against the background thermal pattern.).
Claim 9 lists all the same elements of claim 1, but in apparatus form rather than method form. Therefore, the supporting rationale of the rejection to claim 1 applies equally as well to claim 9. Regarding claim 9, Stephen discloses a computing apparatus ([0055] computer system 100) comprising: one or more computer readable storage media ([0056] computer readable medium); program instructions stored on the one or more computer readable storage media that, when executed by one or more processors ([0060] processor 1305), direct the computing apparatus ([0056] The software may be stored in a computer readable medium, including the storage devices described below, for example. The software may be loaded into the computer system 100 from the computer readable medium, and then executed by the computer system 100. A computer readable medium having such software or computer program recorded on the computer readable medium is a computer program product.).
Claim 10 lists all the same elements of claim 2, but in apparatus form rather than method form. Therefore, the supporting rationale of the rejection to claim 2 applies equally as well to claim 10.
Claim 11 lists all the same elements of claim 3, but in apparatus form rather than method form. Therefore, the supporting rationale of the rejection to claim 3 applies equally as well to claim 11.
Claim 12 lists all the same elements of claim 4, but in apparatus form rather than method form. Therefore, the supporting rationale of the rejection to claim 4 applies equally as well to claim 12.
Claim 13 lists all the same elements of claim 5, but in apparatus form rather than method form. Therefore, the supporting rationale of the rejection to claim 5 applies equally as well to claim 13.
Claim 14 lists all the same elements of claim 6, but in apparatus form rather than method form. Therefore, the supporting rationale of the rejection to claim 6 applies equally as well to claim 14.
Claim 17 lists all the same elements of claim 9, but in computer-readable storage media form rather than apparatus form. Therefore, the supporting rationale of the rejection to claim 9 applies equally as well to claim 17.
In regard to claim 18, the limitations of claim 17 have been addressed. Stephen discloses wherein to identify the attributes of the lightning event, the program instructions direct the computing device to identify the unique attributes and characteristics of the event based on optical properties of the lightning event derived from the data ([00485] One or more of the cameras on the sensing towers may pointed towards clouds in the sky to enable the system to capture and analyse images to resolve the location in the cloud where the lightning started, as well as the location where the lightning hit. The system may use the captured images to measure the path of the lightning. The determined path of the lightning may be used by the system to classify the lightning type and/or lightning shape based on the captured images. The path of lightning, lightning type (e.g. polarity) and/or lightning shape may be used to determine a probability of ignition of a fire. For example, an algorithm and/or machine learning system may be used to calculate the probability of ignition of a fire. The duration of the lightning may also be measured to give a measure of the energy flowing. That is, the longer the duration, the more energy may flow and the higher the probability of a lightning ignition. This may be factored into the algorithm and/or machine learning system to calculate the probability of ignition of a fire.).
Claim 19 lists all the same elements of claim 13, but in computer-readable storage media form rather than apparatus form. Therefore, the supporting rationale of the rejection to claim 13 applies equally as well to claim 19.
Claim 20 lists all the same elements of claim 11, but in computer-readable storage media form rather than apparatus form. Therefore, the supporting rationale of the rejection to claim 11 applies equally as well to claim 20.
Claim(s) 7, 8, 15, and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Stephen in view of Tohidi et al. (Hereafter, “Tohidi”) [US 2020/0159397 A1].
In regard to claim 7, the limitations of claim 1 have been addressed. Stephen discloses further comprising generating a map for display in a user interface, wherein the map includes the location of the lightning event and the ignition potential ([00553] The system may use small fire propagation models that may predict the fire growth based variables which include some or all of the following: weather conditions (wind speed, temperature, humidity), soil moisture, fuel load, fuel dryness, topography (fires like to burn uphill and the wind may not be able to get to the fire if it is sheltered from the wind) etc. [00555] The fire propagation model may provide an effective and detailed fire suppression strategy for each fire. For example, a pilot may be provided with a map of the ignition which indicated where and how much fire suppressant should be dropped in what order in what place to best contain the fire.).
Tohidi discloses further comprising generating a map for display in a user interface, wherein the map includes the location of the lightning event and the ignition potential ([0057] Initially, the weather predictions 302 are gathered, and an ignition forecasting method 304 predicts where fire may ignite, e.g., resulting from lighting or embers traveling in the air. The real-time fire map is then calculated 306 that shows the current location of the fire. After calculating 306 the real-time fire map, the behavior of the fire may be predicted 308, as well as which population and property are vulnerable 310 to the fire, and the planning of evacuating model 312 for people and animals. [0036] A fire forecasting tool generates forecasts for the evolution of the fire, which include the evolution of the fire perimeter and possible new ignition sites. The fire forecasting information may be presented on a user interface that includes maps with the details about the fire evolution. [0066] The live monitor 414 provides user interfaces (e.g., on a display or printed on paper) that enable the view of the fire and its evolution.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Stephen with the explicit teachings of a real-time fire map displayed on a user interface which includes the location of the fire and prediction of the behavior/evolution of the fire as taught by Tohidi in order to provide live fire view, in near real-time, allows for better decision-making and improved firefighter safety [See Tohidi].
In regard to claim 8, the limitations of claim 7 have been addressed. Stephen fails to explicitly disclose wherein the location of the lightning event is color-coded according to the ignition potential.
Tohidi discloses wherein the location of the lightning event is color-coded according to the ignition potential ([0071] FIG. 6 is a user interface 602, of the computer system, for monitoring wildfires based on current conditions, according to some example embodiments. User interface 602 shows the likelihood of wildfires starting based on the present situation. Diamond icons 608 show the probability of lighting happening during the storm, which may cause new fires. [0072] Colored areas 610-612 show where fire may ignite. Legend 604 shows the color legend for the risk of fire (e.g., numbered from 0 to 3, with 3 being for the highest risk). Box 606 includes an option for selecting whether to show the icons 608 representing the probability of lightning. The user interface 1202 provides a color-coded representation of the fuel materials in the region.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Stephen with the explicit teachings of a color-coded real-time fire map displayed on a user interface as taught by Tohidi in order to provide live fire view, in near real-time, allows for better decision-making and improved firefighter safety [See Tohidi].
Claim 15 lists all the same elements of claim 7, but in apparatus form rather than method form. Therefore, the supporting rationale of the rejection to claim 7 applies equally as well to claim 15.
Claim 16 lists all the same elements of claim 8, but in apparatus form rather than method form. Therefore, the supporting rationale of the rejection to claim 8 applies equally as well to claim 16.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Kaitlin A Retallick whose telephone number is (571)270-3841. The examiner can normally be reached Monday-Friday 8am-5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Chris Kelley can be reached at (571) 272-7331. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/KAITLIN A RETALLICK/Primary Examiner, Art Unit 2482
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