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 .
Claims 1, 3, 6-7, 9 and 11-16 are pending.
Claims 2, 4-5, 8 and 10 are canceled.
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, 3, 6-7, 12-13 and 16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea D1 without significantly more.
Regarding claim 1 (and claims 12-13), the following 2-step analysis is applied for analyzing the 35 U.S.C. § 101 subject matter eligibility of the claims. Claims 12-13 recite similar limitations.
Step 1: Statutory Categories
Claims 1, 12, and 13 recite, respectively, a machine, a process, and a non-transitory computer-readable storage medium, and therefore fall within statutory categories.
Step 2A, The Judicial Exceptions
Prong 1: does/do the claim(s) recite an exception?
Claims 1, 12, and 13 recite a mathematical concept comprising calculating a degree of association from the difference between a current size × coefficient value and a past size × coefficient value and prioritizing historical information according to that calculated relationship.
Prong 2: is the exception integrated into a practical application?
Claims 1, 12, and 13 do not integrate the mathematical concept into a practical application. The additional image acquisition, work-area segmentation, identification of size/workability information, storage, and output limitations provide data used by, and results from, the calculation in the field of work-time estimation, but the claims do not recite an improvement to image-processing or computer technology. The specification expressly permits known image-processing technology for the area determination.
Step 2B: The Inventive Concept
The additional elements in claims 1, 12, and 13, considered individually and as an ordered combination, do not amount to significantly more than the exception. The processors, memory/storage, captured-image acquisition, image-processing/data-generation operations, and priority output implement the mathematical comparison using otherwise generic information-processing functionality rather than supplying a technological inventive concept.
Conclusion: Claims 1, 12, and 13 are directed to an abstract mathematical idea and lack an inventive concept. Claims 1, 12, and 13 are rejected as ineligible subject matter under 35 U.S.C. § 101.
Regarding dependent claims 3, 6-7 and 16: Limitations in all dependent claims have been examined in a similar way to the above independent claims. It was found that none of the dependent claims recite a specific technical improvement to computer functionality or a non-conventional arrangement of components sufficient to overcome the § 101 rejection.
Claim 3, §101 ineligible: Division-specific area/workability/time information is principally further data organization.
Claim 6, §101 ineligible: Per-division priority output further specifies presentation/selection of the calculated results.
Claim 7, §101 ineligible: Selecting a predetermined number of highest-associated records is additional ranking/data selection.
Claim 16, §101 ineligible: Coefficients corresponding to those characteristics further particularize the mathematical weighting rather than supplying a technological improvement.
Prior Art
D1: US8875088B1 Holler et al
D2: US8126819B1 Ersek
D3: US20220156662A1 Pickreign (new)
D4: US20220413165A1 Song
Claim Rejections - 35 USC § 103
The following is a quotation of pre-AIA 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102 of this title, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negatived by the manner in which the invention was made.
Claim(s) 1-13 is/are rejected under 35 U.S.C. 103 as being unpatentable over D1 in view of D2 and further in view of D3.
Regarding claims 1, 12 and 13, D1 teaches an information processing device comprising a storage device configured to store history information in which area information regarding a past work area and time information regarding a work time in the past work area are associated with each other, the information processing device further comprising: one or more memories storing instructions; and one or more processors configured to execute the instructions to:
(D1, Fig. 6; "The server computer 600, which may be used as a server system 404 (FIG. 4), typically includes one or more processing units (CPUs) 602 ... memory 604", c19:30-40; Fig. 4; "historical work completion data 416", c12:60-65; D2, Fig. 1; "Normally, the customer will provide their lot size dimensions, any previous treatment provided by the lawn care service provider, and the desired treatment service.", c1:25-35; D1 teaches a server system with processors and memory storing historical project work data; D2 teaches lot size)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate the teachings of D2 into the system or method of D1 in order to store historical area and treatment information associated with time, size and effort estimates. The combination of D1 and D2 also teaches other enhanced capabilities.
The combination of D1 and D2 does not expressly disclose but D3 teaches:
acquire a captured image of a current work area from an image capturing device;
(D3, Fig. 1A; "Upon receiving the Address Location Request 118, the Imaging Satellite Provider 108 may communicate an Image Blob 120 to the Cellular Provider 106. The Cellular Provider 106 may relay the Image Blob 120 to the KGLS Software Application 102. The Image Blob 120 may be acquired in real-time or alternatively acquired at an earlier time and stored.", [0035]; D3 teaches acquiring an Image Blob representing the customer property from an Imaging Satellite Provider)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate D3’s image acquisition into D1/D2 in order to predictably enable automated physical-property assessment. The combination of D1, D2 and D3 also teaches other enhanced capabilities.
The combination of D1, D2 and D3 further teaches:
perform area determination processing on the captured image to divide the current work area into a plurality of work divisions according to work to be performed in the current work area;
(D3, Fig. 2; "The Image Blob 220 may have at least a periphery (border) 226, service zones 228, exclusion zones 230, and a topography 232. The Image Blob 220 may be analyzed by the Image AI and details regarding the periphery 226, service zones 228, exclusion zones 230, and the topography 232, may be determined.", [0045]; "The types of service may be determined by further analysis of the service zones 228 by the Image AI.", [0047]; D3 teaches image analysis identifying service zones and determining work types for those zones. Incorporating this zoning into D1/D2 would automate determining work-specific portions of a property)
identify, based on the captured image, a size of each of the plurality of work divisions and workability information for each of the plurality of work divisions;
(D3, Fig. 2; "The square footage of the exclusion zones 230 may be subtracted from the total square footage of the topography 232 leaving the square footage of the service zones 228.", "The Image AI may also determine a complexity parameter based on the topography 232 of the Address Location 112 a . . . 112 n.", [0047]; "Lawn services may be more difficult to perform in the convex and concave areas.", [0048]; D3 teaches image-derived service-zone square footage and topography complexity reflecting work difficulty. D3 does not expressly state separate size and complexity values for each individual service zone. However, maintaining those already-determined attributes per identified zone would have been an obvious implementation)
generate the area information regarding the current work area to include size information regarding the identified sizes and the identified workability information;
(D3, Fig. 1A; "According to an example embodiment, the Image Blob 120 is processed by the Image AI and may determine a set of Image Parameters (not shown). The Image Parameters may be communicated to an Estimation AI of the KGLS Software Application 102.", [0037]; "The Image AI determines at least a periphery, exclusion zone, service zone, topography complexity and service types (608)", [0068]; D3 teaches generating Image Parameters describing service-zone geometry and topography complexity from image processing. Incorporating those generated parameters into D1/D2 would provide size/workability area information for automated estimation)
identify a degree of association between the generated area information and the history information stored in the storage device; and
(D1, Fig. 2J; "The project management software identifies work items that satisfy the criteria provided by the user in the menu 2132", c12:10-15; matching the inputted criteria to the stored historical data to identify associated records.)
output information included in the history information with priority according to the identified degree of association,
(D1, Fig. 2I; "The graph 2116 includes a group of bars 2118 displaying historical work estimate data for the selected project hierarchy level 2012 ", c10:40-45; outputting and displaying the identified historical data that matched the specified criteria.)
wherein the degree of association is a difference between (i) a value of size x coefficient of the current work area and (ii) a value of size x coefficient of the past work area, and
wherein the coefficient corresponds to the workability information, and
wherein the smaller the difference is the higher the degree of association is.
(D1, Fig. 2C; "values calculated according to a formula ("synthetic attributes")", c5:55-60; Fig. 2K; "statistical metrics include, for example, average velocity", c12:45-50; “Other rates of work completion include but are not limited to the amount of estimated work completed per release or per a specified period of time (e.g., a day, a week, or a month)”, c5:35-40; completion time = size of work x [1/(rate of work)]; “Summary information below the graph 2116 also displays May 24, 2008 as the estimated time of completion 2128, which may be compared against the previously scheduled time of completion 2130”, c10:60-end; comparing historical completion times to figure out how close the completions are => degree of association for different works in history)
Regarding claim 6, the combination of D1, D2 and D3 teaches its/their respective based claim(s).
The combination further teaches the information processing device according to claim 1, wherein
the one or more processors execute the instructions to output information included in the history information for each division of the work with priority according to the identified degree of association.
(D1, Fig. 1; "groups of work items may be defined.", c4:10-15; "Reports may be generated for a specified level or node in the project hierarchy", c5:10-15; dividing the overall work area into designated groups (divisions) and outputting generated reports/historical information for each specific division based on the established parameters and associations)
Regarding claim 7, the combination of D1, D2 and D3 teaches its/their respective based claim(s).
The combination further teaches the information processing device according to claim 6, wherein the one or more processors execute the instructions to output information included in predetermined number of pieces of the history information having the high degree of association for each division of the work.
(D1, Fig. 2K; "a Start Iteration field 2154 for selecting a first historical iteration, a Stop Iteration field 2156 for selecting a second historical iteration ", c12:40-45; Fig. 2I; " The graph 2116 includes a group of bars 2118 displaying historical work estimate data for the selected project hierarchy level 2012", c10:40-4; using defined start and stop parameters to output a predetermined number of historical data pieces (iterations) that correlate with the chosen work division metrics.)
Claim(s) 3, 9 and 14-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over D1 in view of D2 and further in view of D3 and D4.
Regarding claim 3, the combination of D1, D2 and D3 teaches its/their respective based claim(s).
The combination further teaches the information processing device according to claim 1, wherein
the area information includes division information regarding a division of work,
the size information includes information regarding an area for each division of the work,
the workability information includes information regarding workability for each division of the work, and
the time information includes information regarding a work time for each division of the work.
(D4, Fig. 7; "the lawn has been marked with several zones of different sizes and shapes.", [0044]; Fig. 10; "calculations for the area sizes of each zone and the whole lawn, number of obstacles in each zone if there is any, number of segments in each zone, slope of each segment, time to finish mowing or caring for each zone and the lawn, difficulty level for each zone and the lawn", [0050])
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate D4 into the combination of D1-D3 in order to allow the system to divide the overall work area into granular zones (divisions), generating the specific size, time, and difficulty (workability) for each individual zone to produce highly accurate, division-by-division schedules and quotes. The combination of D1, D2, D3 and D4 also teaches other enhanced capabilities.
Regarding claim 9, the combination of D1, D2 and D3 teaches its/their respective based claim(s).
The combination of D1, D2, D3 and D4 further teaches the information processing device according to claim 1, wherein the size information includes information regarding a surface area of a hedge to be a work target.
(D4, Fig. 12; "While going through a boundary, the tool collects length, direction, and slope information.", [0052]; Fig. 5a; "The slope of a segment can be calculated by heights of both ends.", [0041]; Fig. 7; "The object next to Segment 1 is a tree.", [0047]; Fig. 7; "The object next to Segment 5 is a wall.", [0046]; D2, Fig. 1; "lawn care services", c2:10-15; While D4 does not explicitly use the exact word "hedge," it explicitly teaches collecting the length and height dimensions of lawn boundaries and plant-based obstacles (like trees, walls, and fences) to map the work area. Under the KSR principle of applying a known technique to a similar item to achieve a predictable result, it would be obvious to a person having ordinary skill in the art to apply D4's known dimension-measuring capabilities to a hedge, which is essentially a living, plant-based wall or boundary common in the lawn care services of D2. Calculating the surface area (length x height) of a hedge target using these established size-gathering methods is a finite, identified, and predictable solution to accurately estimate the required work effort)
Regarding claim 14, the combination of D1, D2 and D3 teaches its/their respective based claim(s).
The combination further teaches the information processing device according to claim 1, wherein the plurality of work divisions include a lawn area, a grass area, a handheld area, and a hedge area.
(D4, see comments on claim 9)
Regarding claim 15, the combination of D1, D2 and D3 teaches its/their respective based claim(s).
The combination of D1, D2, D3 and D4 further teaches the information processing device according to claim 1, wherein the workability information includes at least one of an inclination, a waterside, an object to be avoided, and a type of a plant in the current work area.
(D4, Fig. 5a; "The slope of a segment can be calculated by heights of both ends.", [0041]; => “inclination”; Fig. 7; "The object next to Segment 1 is a tree.", [0047]; incorporating D4 into D1-D3 would provide specific workability metrics, such as slopes (inclination) and trees (plants), to function as the coefficients that adjust the difficulty and time estimates for the specific work area)
Regarding claim 16, the combination of D1, D2 and D3 teaches its/their respective based claim(s).
The combination of D1, D2, D3 and D4 further teaches the information processing device according to claim 1, wherein the coefficient includes at least one of coefficients regarding the inclination, the waterside, the object to be avoided, and the type of the plant.
(D4, see comments on claim 15)
Response to Arguments
Applicant's arguments filed on 9/14/2026 with respect to one or more of the pending claims have been fully considered but are moot in view of the new ground(s) of rejection.
Regarding the 35 USC § 101 rejection to claims 1, 3, 6-7, 12-13 and 16, the office action has been updated to address the amended limitations of the claims. See the updated review comments for details.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JIANXUN YANG whose telephone number is (571)272-9874. The examiner can normally be reached on MON-FRI: 8AM-5PM Pacific Time.
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/JIANXUN YANG/
Primary Examiner, Art Unit 2662 10/3/2026
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