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 Status
Claims 1-18 are pending for examination.
Response to Arguments
Applicant's arguments filed 7/28/2026 have been fully considered.
In response to “Allowable Subject Matter” at page 7, claim 1 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph in view of the amendment. Accordingly, claims 3, 5-8 and 12-14 are also rejected because they depend on claim 1.
However, claims 3, 5-8 and 13-14 would be allowable if claim 1 is rewritten to overcome the rejections under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims, and claim 18 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, and claim objection, set forth in this Office action.
In response to 35 “Claim Rejections – 35 U.S.C. § 112” at page 7, the previous rejection has been withdrawn in view of the amendment. However, the amendment presents new 35 U.S.C. 112 issues. Please see details below.
Under “Claim Rejections – 35 U.S.C. §§ 102 / 103”, Applicant argues Kraus fails to teach the newly introduced limitation “said georeferenced image being a cartographic map for which at least three points have known geographical coordinates and in which said at least one symbol, or marker, has been placed at a position which corresponds to an actual position of said pedological data measurement point in the geographical zone, said pedological data measurement point being a point in the geographical zone, where said pedological data measurement has been collected by carrying out an analysis of at least one characteristic of soil at said point” in claims 1, 16 and 18.
In response to the arguments at pages 8-9 that Kraus fails to teach “a cartographic map for which at least three points have known geographical coordinates”, Kraus discloses at paragraph [0046] that the photographed images are converted to line drawing shown in Fig. 5 and displayed in Fig. 2. These images of Fig. 2 and Fig. 5 correspond to a cartographic map Furthermore; Kraus discloses at paragraph [0032] that GPS coordinates are used to delineate the boundaries of an imaged crop field. These field boundaries necessarily include at least three GPS coordinates that define the upper, lower, left and right boundaries
In response to the arguments at pages 9-10 that Kraus fails to teach “at least one symbol, or marker, has been placed at a position which corresponds to an actual position of said pedological data measurement point”, Fig. 5 of Kraus clearly shows the location of each vegetation, represented by line drawing, corresponds to the actual location of the vegetation because each vegetation is converted from the photographed image. The presentation of the vegetation changes from an image to a line drawing as shown in Fig. 5 but the location of each vegetation remains the same after the conversion.
In response to the arguments at page 10 that Kraus fails to teach “where said pedological data measurement has been collected by carrying out an analysis of at least one characteristic of soil at said point”, Kraus discloses at Fig. 2 a diagram of generating a soil characteristic map and paragraph [0035] discloses:
“The soil mapping system may utilize any non-crop vegetation distributions, as identified in the captured crop field images, to infer the soil characteristic or characteristics desirably subject to mapping; e.g., giving greater or lesser weight or probability to likely soil characteristics, as inferred from the non-crop vegetation distributions, based upon non-crop vegetation type and density. Such soil characteristics can include, but are not limited to, soil fertility levels, soil moisture levels, pH levels, chemical toxicity levels, soil nutrient levels, soil composition, and soil compaction levels.” and para [0037].
The cited disclosure clearly teaches the SMS generates a soil characteristic map (analogous to “pedological data measurement”) based on an analysis of the vegetations growing on the soil. The vegetation is interpreted as a proxy for soil characteristics because specific types of vegetation survive under specific soil characteristics. In other words, the vegetation growing on the soil is considered as a characteristic of a soil type. For example, by analyzing the distribution of a specific plant (e.g., sorrel plant) growing in a field, the SMS determines the soil has a dry characteristic and adds that soil characteristic to the corresponding field location of the soil characteristic map.
The Applicant further argues Kraus avoids the need to conduct physical, ground-truth soil analysis.
However, the claim language fails to expressly or inherently recite any requirement for conducting a physical, ground-truth soil analysis. Under the broadest reasonable interpretation, analyzing vegetation that reflects soil characteristic is sufficient to meet the claim limitation and anticipate the claim.
In response to “Claim 1 is Non-Obvious”, claim 1 is rejected under 35 U.S.C. 102(a)(1) as being anticipated by Kraus, rather than under 35 U.S.C. 103 for obviousness.
Accordingly, the rejection is maintained in view of Kraus based on the reasons provided.
Claim Objections
Regarding claim 18, is objected to because it repeats claims 1-3.
Appropriate correction is required.
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.
Regarding claim 15, is rejected under 35 USC 101 for being directed to nonstatutory “a computer program”. Although the specification gives examples of digital storage medias, exemplification does not preclude the computer program from including other potentially nonstatutory media. When a claim covers both statutory and nonstatutory elements, a rejection under 35 USC 101 is proper. The Examiner suggests amending the claim in concordance with the OG notice (2/23/2010) to “A non-transitory computer readable storage device comprising executable instructions ….”.
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.
Regarding claims 1, 16 and 18, recite the limitation “said pedological data measurement” in line 9 of claim 1, line 12 of claim 16 and line 9 of claim 18. This limitation lacks sufficient antecedent basis. The claims defined “pedological data measurement point” but not “pedological data measurement”.
Regarding claims 2-15 and 17, the claims are also rejected because they depend on claim 1.
Regarding claim 15, recites the limitation “they” in line 1. The limitation is indefinite because it is unclear what the limitation is referring to.
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 1-2, 4, 9-12 and 15-16 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Kraus (Pub. No.: US 2022/0245383 A1).
Regarding claim 1, Kraus teaches a method for determining at least one characteristic of soil in a geographical zone (abstract, system and method for image-based soil characteristic mapping), the method being implemented by computer and comprising:
detecting, in at least one georeferenced image associated with the geographical zone (Fig. 2 step 58 and Fig. 6, the soil mapping server (SMS) receives images of the geographical zones), at least one symbol representative of a pedological data measurement point, and an associated unique identifier (Fig. 2, para [0033], “In this regard, a convolutional or other neural network can be trained to recognize leaf shape, stem coloring, flower shape and color (if applicable), and other such phenotypical traits utilized to visually identify different plant species, including non-crop plants or “weeds,” which are typically visible in (e.g., aerial) crop field imagery. For example, dandelion (Taraxacum) can be readily recognized by, among other features, the presence of yellow flowers in early growth stages and by their distinct puffball seed cluster in later growth stages.”. The SMS detects one or more symbols that uniquely identifies the one or more vegetations), said georeferenced image being a cartographic map (Figs. 5-6, para [0046], “The camera onboard the drone 116 is generically represented by a camera symbol 120 shown on the left of FIG. 5, while the camera FOV is represented by a graphic 122. A single georeferenced field image (e.g., a still image or a frame extracted from a video) is further represented in FIG. 6 by a graphic 124 and generally corresponds with the line drawing 126 (converted from a crop field photograph) shown in perspective in FIG. 5.”. The photographed images are converted to line drawing shown in Fig. 5 and Fig. 2 shows the soil map) for which at least three points have known geographical coordinates (para [0032], “Accordingly, the particular location of a crop field image can be deduced or ascertained based upon location data for other crop field images; and/or based upon previously-established geolocation data of the imaged crop field (e.g., GPS coordinate sets outlining crop field boundaries) in at least some embodiments.”. The GPS data delineates the boundaries of a specific field. The field boundaries include at least three GPS coordinates that indicate the top, left, right and bottom boundaries) and in which said at least one symbol, or marker, has been placed at a position which corresponds to an actual position of said pedological data measurement point in the geographical zone (Fig. 5 and para [0046], each vegetation is converted form the photographed image into a line drawing. Therefore, the location of each vegetation is the actual location of the vegetation), said pedological data measurement point being a point in the geographical zone (Fig. 6, the image 124 captured being one of the areas within the field 118), where said pedological data measurement has been collected by carrying out an analysis of at least one characteristic of soil at said point (Fig. 2, para [0035], “The soil mapping system may utilize any non-crop vegetation distributions, as identified in the captured crop field images, to infer the soil characteristic or characteristics desirably subject to mapping; e.g., giving greater or lesser weight or probability to likely soil characteristics, as inferred from the non-crop vegetation distributions, based upon non-crop vegetation type and density. Such soil characteristics can include, but are not limited to, soil fertility levels, soil moisture levels, pH levels, chemical toxicity levels, soil nutrient levels, soil composition, and soil compaction levels.” and para [0037]. The SMS generates a soil map based on an analysis of the vegetations growing on the soil. The vegetation indicates the characteristic of the soil (e.g., dry or wet). For example, an analysis of the distribution of sorrel plants on a field indicates the soil has a dry characteristic.); and
for each symbol detected:
calculating geographical coordinates of a corresponding measurement point, from a position of said symbol in the image and the georeferencing of the image (Fig. 2 step 60, and Fig, 6, the SMS calculates coordinates of each vegetation from the photographed image and GPS to categorize distribution); and
from the corresponding unique identifier, identifying, in a pedological database associated with the geographical zone, the pedological data corresponding to the respective measurement point (Fig. 1, look-up table 54, Fig. 2, steps 62-68 and para [0035] the SMS determines soil characteristic in different areas of the image based on the identified vegetations and the distribution of the vegetations).
Regarding claim 2, Kraus teaches the method according to claim 1, further comprising estimating, from the geographical coordinates calculated for each measurement point and the corresponding identified pedological data, the pedological data at any point in the geographical zone (Fig. 2 step 68, shows the SMS determines and displays the estimated soil characteristic for each point of the image).
Regarding claim 4, Kraus teaches the method according to claim 2, wherein the estimation of pedological data at any point in the geographical zone comprises implementing at least one artificial intelligence model (para [0027], “In certain cases, the SMS server end 14 may store a neural network algorithm, or a similar machine-learning algorithm, trained to recognize visual patterns within the collected crop field images and identify different crop species based upon various aspects of the phenotype or appearance of different crop species.”).
Regarding claim 9, Kraus teaches the method according to claim 2, wherein the estimation of pedological data at any point in the geographical zone is also a function of soil covariables of the geographical zone (Fig. 2, step 60, the soil characteristic is partially determined based on the vegetation distribution.).
Regarding claim 10, Kraus teaches the method according to claim 9, wherein the covariables include information relating to topography, information relating to geology and/or information relating to land use of the geographical zone (Figs. 5-6 show the topography of the geographic zone).
Regarding claim 11, Kraus teaches the method according to claim 1, wherein the at least one characteristic of the soil comprises a useful water capacity (para [0021], “The soil mapping system then utilizes any non-crop vegetation distributions, as identified in the field images, to infer or deduce the soil characteristic(s) desirably subject to mapping, taken in conjunction with any other relevant data including, for example, the soil conditions supporting the desirably-grown crop species. Such soil characteristics can include, but are not limited to, soil fertility levels, soil moisture levels,”. The soil characteristic includes soil moisture level.).
Regarding claim 12, Kraus teaches the method according to claim 1, wherein the pedological data comprises upper and lower depths, mass percentages of gravel and stones, a weight percentage of fine earth, an apparent density, an equivalent humidity and/or a structural coefficient for each stratum (para [0035], “With respect to soil type, and as also previously noted, soil present within different regions of the mapped crop field may be classified as clay, sandy, silty, peaty, chalky, loamy, and combinations thereof.”).
Regarding claim 15, Kraus teaches a computer program comprising executable instructions which, when they are executed by computer, implement a method according to claim 1 (para [0027], “Accordingly, the SMS server end 14 may likewise include a processor architecture 32 (e.g., one or more processors) and a memory 34 storing computer-readable instructions or information for carrying-out the processes or functions described herein”).
Regarding claim 16, Kraus teaches a device for determining at least one characteristic of soil in a geographical zone (Fig. 1 soil mapping support (SMS) server 14), the device comprising a database (Fig. 1, look-up table 54) and a processing unit (Fig. 1, processor 32),
the database being configured to store pedological data associated with the geographical zone (Fig. 1, the look-up table includes soil characteristics), the processing unit being configured to:
detect, in at least one georeferenced image associated with the geographical zone, at least one symbol representative of a pedological data measurement point, and an associated unique identifier; said georeferenced image being a cartographic map for which at least three points have known geographical coordinates and in which said at least one symbol, or marker, has been placed at a position which corresponds to an actual position of said pedological data measurement point in the geographical zone, said pedological data measurement point being a point in the geographical zone, where said pedological data measurement has been collected by carrying out an analysis of the characteristic of soil at said point; and
for each symbol detected:
calculate geographical coordinates of a corresponding measurement point, from a position of said symbol in the image and the georeferencing of the image; and
from the corresponding unique identifier, identify, in the database, the pedological data corresponding to the respective measurement point (The rejection is similar to Claim 1.).
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 17 is rejected under 35 U.S.C. 103 as being unpatentable over Kraus (Pub. No.: US 2022/0245383 A1).
Regarding claim 17, Kraus teaches the method according to claim 4, but fails to teach wherein said at least one artificial intelligence model is a fast forest quantile regression.
However, it would have been obvious to a person having ordinary skill in the art before the claimed invention to perform a simple substitution of any well-known machine learning algorithm, such as a fast forest quantile regression, to obtain similar and predictable results.
Allowable Subject Matter
Claims 3, 5-8 and 13-14 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Claim 18 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, and claim objection, set forth in this Office action.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Nelan (Pub. No.: US 2015/0310633 A1) teaches a system and method of processing image to determine soil characteristics.
Norberg (Pub. No.: US 2012/0139325 A1) teaches a system and method for terrain analysis based on captured image.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ZHEN Y WU whose telephone number is (571)272-5711. The examiner can normally be reached Monday-Friday, 10AM-6PM, EST.
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/ZHEN Y WU/Primary Examiner, Art Unit 2685
