DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
2. Responsive to the communication dated 12/22/2025.
3. Claims 1-8, 10-21, 24-25 and 27-28 are presented for examination.
Response to Amendment
4. The amendment filed on 12/22/2025 has been entered and considered by the examiner. By the amendment, claims 1, 15, 19 are amended, claims 23, 26 are cancelled and claim 28 is newly added. The previous 101 is still maintained in view of amendment made and an explanation is given below. The prior art rejection is modified in light of the amendment made to the claim and see office action for detail.
Response to 101 arguments
Applicant arguments
First, according to the 2019 Guidance, for a claim to be an abstract idea, the claim must recite limitations that incorporate mathematical concepts or constitute mental processes or certain methods or techniques of organizing human activity. MPEP § 2106.04(a). Applicant submits that the amended claims do not recite any limitations falling within any of these enumerated groupings. In that regard, the amended claims do not recite any mathematical relations, formulas, or calculations. See MPEP § 2106.04(a)(2)(I). The amended claims also do not recite any methods or techniques for organizing human activities, such as fundamental economic principles or practices, commercial or legal interactions, or personal behaviors or relationships or interactions between people. See MPEP § 2106.04(a)(2)(II). Furthermore, the amended claims are not directed towards mental processes. The Memorandum to technology centers 2100, 2600, and 3600 dated August 4, 2025, entitled Reminders on evaluating subject matter eligibility of claims under 35 U.S.C. 101 (hereinafter, the "August Memo") "provides important reminders pertaining to the United States Patent and Trademark Office's (USPTO's) subject matter eligibility guidance," including "reliance on the mental process grouping of abstract ideas." The August Memo indicates that "[t]he mental process grouping is not without limits. Examiners are reminded not to expand this grouping in a manner that encompasses claim limitations that cannot practically be performed in the human mind." In that vein, the August Memo also states that "a claim does not recite a mental process when it contains limitation(s) that cannot practically be performed in the human mind, for instance, when the human mind is not equipped to perform the claim limitation(s)."See also MPEP § 2106.04(a)(2)(III). Here, the amended claims recite the specific steps of processing a building layout comprising a three-dimensional (3D) model of a building by determining a direction of a target source based on site data that includes a location of the site, an orientation of the site, an elevation of the site, a topography of the site, a location of an adjacent site, an orientation of the adjacent site, an elevation of the adjacent site, and a topography of the adjacent site, and modifying the building layout of the building based on an overall work condition value to generate an additional building layout comprising an additional 3D model of the building. These steps quite clearly require the use of a computing device and are not steps that can practically be performed in someone's mind or using pen/paper. In particular, determining a direction of a target source based on site data that includes a location of the site, an orientation of the site, an elevation of the site, a topography of the site, a location of an adjacent site, an orientation of the adjacent site, an elevation of the adjacent site, and a topography of the adjacent site to generate an additional 3D model of the building is computationally intensive and cannot practically be executed without the use of a computing device. Because none of the limitations recited in the amended claims are directed towards any of the enumerated categories of abstract ideas, the amended claims cannot be properly interpreted as being abstract.
Examiner response
Examiner respectfully disagrees. The claims are directed to evaluating building layouts based on natural lighting conditions and selecting an optimal layout based on work condition value. These steps constitute mental process and mathematical modeling. The claim merely uses a CAD system as a tool to perform an analysis. According to Alice Corp. v. CLS Bank, merely restricting an abstract idea (like designing a building based on site data) to a computer environment does not make it non-abstract. The core, functional mental steps—assessing topography, adjacent buildings, and orientation—remain abstract, even if the calculations are too fast for a human. Examiner found the current claim starts with a 3D model of the building within the CAD software, then the model is then adjusted based on the specific features of the site where it will be built, including elevation changes and slopes. Then the design considers the direction of a specific target point (like a window facing a particular view) based on the site data and finally, the building layout is further modified based on an overall assessment of the working conditions on the site, potentially related to access, logistics, or environmental factors which includes evaluation or judgement that falls under the mental process of abstract ideas. For determining direction based on topography: A person can perform this task mentally. By looking at a topographical map and a potential site, a person can determine the best direction for a building's placement relative to a "target source" (e.g., the sun for passive solar heating, or a roadway for access). While a computer can speed up the calculation, the underlying process is an abstract mental concept of using spatial data to make a directional decision. For modifying a layout based on a condition value: An architect or designer performs this mental process during design work. They use site constraints and design goals (represented here by the "overall work condition value") to determine how to alter a building's layout. This is an abstract design step, and using CAD software to carry out the modification is merely a conventional computer function that facilitates the mental process, not an inventive concept in itself. The process involves using CAD software, site data, and work condition values to generate a building layout. It involves using computer as a tool (CAD software) to analyze site data, optimize building layouts for specific conditions, and generate multiple design options. This is a classic design challenge addressed by architects for hundreds of years. That the invention performs the analysis/calculations/comparisons on a 3D building model (digital representation, e.g. CAD model/file) utilizing a generic computer/processor does not integrate the abstract idea into a practical application – i.e. does not represent an improvement in the underlying technology (e.g. computer/processor). Thus, claim recites "a processor executing a computer-aided design (CAD) application." This language describes using a general-purpose computer to automate a known mental task. The Federal Circuit has repeatedly affirmed that simply automating a human task on a generic computer is not sufficient to establish patent eligibility, as it lacks the "inventive concept" necessary to transform an abstract idea into a patent-eligible invention. As MPEP (2106.04(a)(2)(III)(C)) states using a computer as tool to perform a mental process falls under the grouping of abstract ideas. The generic computing components do not add anything meaningful to integrate into practical application as the computing components are merely used as a tool to perform limitations that could otherwise be performed mentally. The instant application merely claims a method that can be performed in a human mind or via pen and paper (e.g. analyzing/simulating a 3D model of a building layout, modifying the 3D model/building layout based on based on an overall work condition value, analyzing/simulating the modified building layout).
Applicant arguments
Second, the amended claims recite limitations that integrate any purported abstract idea into a practical application. In Ex Parte Desiardins, the Appeals Review Panel of the Patent Trial and Appeal Board explained that "[o]n the one hand, claims '[g]generally linking the use of a judicial exception to a particular technological environment or field of use' are not patent eligible... On the other, claims directed to an improvement in the functioning of a computer, or an improvement to other technology or technical field are patent eligible. “See Ex Parte Desiardins, Decision on Request for Rehearing at 7-8 (emphasis added);see also Memorandum: Reminders on evaluating subject matter eligibility of claims under 35 U.S.C. 101 at 4-5 ("[i]n computer-related technologies, Examiners can conclude that claims are eligible in Step 2A Prong Two by finding that a claim reflects an improvement to the functioning of a computer or to another technology or technical field, integrating a recited judicial exception into a practical application of the exception ... [t]his consideration has also been referred to as the search for a technological solution to a technological problem"); MPEP § 2106.04(d) ("[l]imitations the courts have found indicative that an additional element (or combination of elements) may have integrated the exception into a practical application include: [a]n improvement in the functioning of a computer, or an improvement to other technology or technical field"). Applicant submits that the amended claims meet this standard. In that regard, the amended claims provide improvements to technology, rather than generally linking a judicial exception to a particular technological environment or field of use. In particular, the claimed approach is directed towards the practical application of automatically analyzing and comparing different building layouts comprising 3D models for a building based on subjective work conditions to identify an optimized building layout. See Application, paragraphs [0008], [0023], [0072] - [0075], and [0090] - [0093]. Through this practical application, the claimed approach imparts the technological improvement of automatically analyzing and comparing effects of modifications to a building layout on the subjective work conditions to identify an optimized building layout for implementation in a building, without requiring candidate building layouts to be actually implemented and in operational use to measure the subjective work conditions, which was required using conventional approaches. See Application, paragraphs [0008] and [0093]; see also Ex Parte Desiardins at 8-9 (where the Panel cites various advantages expressly described in the Specification to support patent eligibility); Memorandum: Reminders on evaluating subject matter eligibility of claims under 35 U.S.C. 101 at 4 ("[t]he examiner is reminded to consult the Specification to determine whether the disclosed invention improves technology or a technical field, and evaluate the claim to ensure it reflects the disclosed improvement"). In addition, these limitations place substantive and meaningful limits on the scope of the claims and similarly place substantive and meaningful limits on any purported abstract idea, thereby integrating any purported abstract idea into the practical application of generated computer-aided designs. See MPEP § 2106.04(d) ("[a] claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception"); see also MPEP § 2106.04(d)(I), citingMcRO, Inc. v. Bandai Namco Games America Inc., 837 F.3d 1299 (Fed. Cir. 2016) (claims that recite specifically limited steps or elements that effect a technological improvement or useful result are not abstract). As the foregoing illustrates, any purported abstract idea recited in the amended claims is integrated into a practical application. Accordingly, the amended claims are subject-matter eligible. Because the amended claims do not recite an abstract idea, and because the amended claims recite limitations that integrate any purported abstract idea into a practical application, the present claims are subject-matter eligible under Step 2A of the 2019 Guidance.
Examiner response
Examiner respectfully disagrees, In Ex parte Desjardins, the claim is eligible because it improves the functioning of a computer itself or improved specific technical process, however the instant claim recites the use of conventional CAD application, processor, GUI and 3D model and do not improved 3D render techniques, ray-tracing technology or any technology. Improving decision making about business layouts does not constitute an improvement for the functioning of a computer or to computer technology. Claim merely generate representation of natural light, compute values, modify layouts and compare results. The claims apply an abstract idea-evaluating work conditions and selecting an optimal layout-within a CAD environment but do not improve that environment. Further the claims do not integrate the abstract idea into a practical application (i.e. technical solution to a technical problem; technical improvement). The core of the invention involves evaluating and comparing different designs to find an "optimized" one. Architects, designers, and engineers have performed this mental process for centuries. The patent may merely describe using a computer to perform the steps faster, which is often not enough to confer patent eligibility. Applicant’s claims are clearly directed to modifying a layout design of building based on a set calculated/computed/simulated human worker overall work condition value. This is a classic design challenge addressed by architects for hundreds of years. That the invention performs the analysis/calculations/comparisons on a 3D building model (digital representation, e.g. CAD model/file) utilizing a generic computer/processor does not integrate the abstract idea into a practical application – i.e. does not represent an improvement in the underlying technology (e.g. computer/processor). “Automatically analyzing and comparing building layouts...” still falls under the mental process because this evaluation is that which could be performed mentally. The argument that the claim "automatically" performs the analysis is often not enough to distinguish it from an abstract idea. Under the Alice framework, claims that merely use a generic computer to automate a well-known human activity are not patent-eligible. To be eligible, the claimed invention must improve the computer's functionality or offer a specific, technical solution that could not be practically performed by a human. Simply tying an abstract idea to a generic computer or a generic field of use (e.g., building design) is not enough to satisfy the "practical application" requirement. Thus, the abstract idea itself will not integrate the abstract idea into practical application because it has no additional elements recited in the claim that, individually or in combination, that provides significantly more than the abstract idea. Unlike the McRO claim that achieved a specific, tangible outcome of improved computer-generated animation, the instant claim outcome is an "optimized building layout," which is a goal that humans have always sought to achieve. The method for reaching that outcome is still an abstract, even if the result is a tangible 3D model.
Applicant arguments
The Federal Circuit has ruled in numerous cases that claims directed towards technological solutions to technological problems are not abstract under the two-step Alice test. Applicant submits that the amended claims are similarly directed towards a technological solution to a technological problem.
In that regard, the present Application makes clear that a technical problem that existed in the prior art prior to the development of the claimed approach was that prior approaches generated building layouts via conventional CAD applications that were incapable of analyzing and comparing building layouts based on subjective/qualitative metrics relating to work conditions. Such prior approaches are undesirable because the subjective work conditions of a candidate design layout generated by a conventional CAD application could be measured only after the design layout was actually implemented and in operational use. See Application, paragraphs [0003] - [0005]. The present Application also makes clear that one of technical advantages of the claimed approach is that the claimed approach provides new functionality to a CAD application to automatically analyze and compare effects of modifications to a building layout on subjective work conditions to identify an optimized building layout for implementation in a building, without requiring candidate building layouts to be actually implemented and in operational use to measure the subjective work conditions, which was required using conventional approaches. See Application, paragraphs [0008] and [0093]. Thus, among other things, the claimed approach solves the above technical problem that existed in the prior art, as expressly set forth in the present Application.
Examiner response
Examiner respectfully disagrees. Here the only additional element recited in the claims beyond the abstract idea is computer, process, CAD application (software per se), and memories,” i.e., generic computer component. See Alice, 573 U.S. at 223 (“[T]he mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention.”). That the claims utilize well-known and widely available CAD application (software) to perform the various method steps does not represent a technical solution to a technical problem. The CAD application works/is used as all CAD programs are commonly used by human users (e.g. architects) and that is to generate, analyze, evaluate and compare various CAD models, space designs and the like (Specification: Paragraph 008). Applicant has not identified any additional elements recited in the claim that, individually or in combination, provides significantly more than the abstract idea. The newly recited method steps processing user inputs that modify the building layout) the claims are clearly directed to assisting a human user in to modifying a building design/layout in response based on a computer simulation of overall work condition value utilizing a conventional computer and a convention Computer Aided Design (CAD) application/software. Wherein at best the system/method merely automates the well-known user-driven/manual design process, utilized by building designers/architects well prior to the advent of computers, of improving building layouts based on various metrics (in this case overall work condition value). Data remains data regardless of how it is processed. The core of the invention is the "evaluation" and "optimization" of a building layout based on "subjective/qualitative metrics." An examiner could argue this is simply a formalized version of a process a human designer already performs. For example, an architect manually evaluates a building's layout by reviewing a CAD drawing and making a qualitative judgment on the work conditions, such as the flow of people, light, or proximity of offices. While the claims are tied to a CAD application, the computer is merely being used as a tool to perform the abstract mental process, similar to using a pen and paper. If a human designer could, in theory, perform the evaluation process manually—albeit more slowly or with less precision—the computer implementation may not be enough to transform the abstract idea into a patent-eligible invention. The claimed "solution" is the idea itself, not a specific, inventive means of implementing it that improves the functioning of the computer or another technology.
Applicant 103 arguments
Amended claim 1 recites the limitations of, for a particular work condition element indicating at least one of an amount of natural light exposure or an amount of glare from a target source, determining a direction of the target source based on site data that includes a location of the site, an orientation of the site, an elevation of the site, a topography of the site, a location of an adjacent site, an orientation of the adjacent site, an elevation of the adjacent site, and a topography of the adjacent site. None of the cited references teaches or suggests these limitations. Therefore, no combination of the cited references can teach or suggest each and every limitation of claim 1. New claim 28 recites identifying a subset of rays of the plurality of rays, wherein each ray of the subset of rays is unobstructed, wherein the particular element value corresponding to the particular work condition element is equal to the first total number of rays in the subset of rays divided by a second total number of rays in the plurality of rays. New claim 28 is supported by at least paragraphs [0063] and [0064] of the present Application, as originally filed. Therefore, new claim 28 does not introduce any new matter.
Examiner response
In view of Applicant arguments and amendment, Examiner has withdrawn the Fuscoe reference and added the new reference Marceau et al. US20150234945A1 to teach the part of the limitation of “….for a particular work condition element indicating at least one of an amount of natural light exposure or an amount of glare from a target source, determining a direction of the target source based on site data that includes a location of the site, an orientation of the site, an elevation of the site, a topography of the site, a location of an adjacent site, an orientation of the adjacent site, an elevation of the adjacent site, and a topography of the adjacent site…”. Regarding the newly added claim 28, Examiner added the new reference Savioja. See office action for detail.
Claim Rejections - 35 USC §101
5. 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.
6. Claims 1-8, 10-21, 24-25 and 27-28 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. These claims are directed to an abstract idea without significantly more.
(Step 1) Is the claims to a process, machine, manufacture, or composition of matter?
Claims: 1-8, 10-14, 21, 24-25 and 27-28 are directed to process or method, which falls into the one of the statutory category.
Claims: 15-18 are directed to non-transitory computer readable medium, which falls into the one of the statutory category.
Claims: 19-20 are directed to system or device, which falls into the one of the statutory category.
(Step 2A) (Prong 1) Is the claim directed to a law of nature, a natural phenomenon, or an abstract idea? (Judicially recognized exceptions)?
Claim 1, 15 and 19 recites
processing, a building layout comprising a three-dimensional (3D) model of a building, the building layout specifying, for each workspace of a plurality of workspaces included in a workplace, a respective location of the workspace; (With the broadest reasonable interpretation, the cited features contain steps people go through in their minds since it involves evaluation or judgement. So, it falls under the mental process of abstract ideas. This step is recited at a high level of generality and merely used generic computers as a tool to perform the processes. (See MPEP 2106.04(a)(2)(III))(C) (3) )
selecting one or more work condition elements from a plurality of work condition elements based at least on the plurality of workspaces; (it is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(III)). For example, a person could make a mentally select one or more work condition elements from a plurality of work condition elements of available spaces within a site based on certain information.)
for each work condition element of the one or more work condition elements: evaluating the plurality of workspaces based on the work condition element including, for a particular work condition element indicating at least one of an amount of natural light exposure or an amount of glare from a target source, determining a direction of the target source based on site data that describes a site that includes the building, wherein the site data includes a location of the site, an orientation of the site, an elevation of the site, a topography of the site, a location of an adjacent site, an orientation of the adjacent site, and elevation of the adjacent site, and a topography of the adjacent site, generating, based on the direction of the target source to the plurality of workspaces, wherein the plurality of represent at
0and based on the evaluating the plurality of workspaces, generating an element value corresponding to the work condition element including generating a particular element value corresponding to the particular work condition element; (it is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(III)). For example, a person could mentally, or using pen and paper, assign a element value to work condition element within a site.)
computing, based on element values corresponding to the one or more work condition elements, an overall work condition value associated with the building layout; (it is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(III)). For example, a person could mentally, or using pen and paper, calculate and assign an overall element value to a characteristic of a building (geometry or placement) based on certain information.)
and
modifying the building layout of the building based on the overall work condition value to generate an additional building layout of the building; (It is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(III)). For example, a person could mentally, or using pen and paper, make adjustments to a building design based on certain information.)
processing, the additional building layout comprising an additional 3D model of the building by computing an additional overall work condition value associated with the additional building layout; (With the broadest reasonable interpretation, the cited features contain steps people go through in their minds since it involves evaluation or judgement. So, it falls under the mental process of abstract ideas. While the computation itself may be done by a computer, the human's understanding, planning, and decision-making related to the layout and work condition are inherently mental processes. This step is recited at a high level of generality and merely used generic computers as a tool to perform the processes. (See MPEP 2106.04(a)(2)(III)) (C) (3))
displaying, a comparison between the overall work condition value of the building layout and the additional overall work condition value of the additional building layout that indicates the additional overall work condition value of the additional building layout is improved relative to the overall work condition value of the building layout; and identifying the additional building layout as an optimal building layout for implementation in the building. (With the broadest reasonable interpretation, the cited features contain steps people go through in their minds since it involves evaluation or judgement. So, it falls under the mental process of abstract ideas. The user needs to perceive the visual information, interpret the presented data, and then mentally assess the relationship between the two layouts and their respective work condition values. The step of comparing the "overall work condition value" of a building layout with that of a modified, or "additional," layout is a fundamental mental step. It is analogous to comparing two numbers and determining which is larger. This type of basic evaluation can be performed in the human mind without relying on a specific technological process. The step of "identifying the additional building layout as an optimal building layout" is a judgment based on the comparison. It is the conclusion of a mental process, not an inventive technological application.)
Step 2A, Prong 2: Does the claim recite additional elements that integrate the judicial exception into a practical application?
In accordance with Step 2A, Prong 2, the judicial exception is not integrated into a practical application. In particular, the claim 1, 15 and 19 recites processing, via a computer-aided design application being executed by a processor is a mere instruction to implement an abstract idea on a generic computer, as discussed in MPEP § 2106.05(f) or they merely linked the use of the abstract idea to a particular technological environment (i.e., "implementation via computers"). Also, the displaying via, GUI a comparison also falls under insignificant extra solution activity (see MPEP 2106.05(g)Selecting a particular data source or type of data to be manipulated). The additional element of a computer system, comprising: a memory storing instructions; and one or more processors for executing the instructions in claim 19 and one or more non-transitory computer readable media storing instructions that, when executed by one or more processors, cause the one or more processors to perform the step in claim 15 is mere instructions to implement an abstract idea on a computer, as discussed in MPEP § 2106.05(f). Thus, a computer-implemented method for computationally determining employee work conditions in claim 1 is no more than generally linking the use of a judicial exception to a particular technological environment or field of use, as discussed in MPEP § 2106.05(h).These additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
In accordance with Step 2B, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. In accordance with Step 2A, Prong 2, the judicial exception is not integrated into a practical application. In particular, the claim 1, 15 and 19 recites the additional elements of processing, via a computer-aided design application being executed by a processor is a mere instruction to implement an abstract idea on a generic computer, as discussed in MPEP § 2106.05(f) or they merely linked the use of the abstract idea to a particular technological environment (i.e., "implementation via computers"). Also, the displaying via, GUI a comparison also falls under insignificant extra solution activity and is well known, routine and conventional (see MPEP 2106.05(g) iii. Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016)). The additional element of a computer system, comprising: a memory storing instructions; and one or more processors for executing the instructions in claim 19 and one or more non-transitory computer readable media storing instructions that, when executed by one or more processors, cause the one or more processors to perform the step in claim 15 is mere instructions to implement an abstract idea on a computer, as discussed in MPEP § 2106.05(f). Thus, a computer-implemented method for computationally determining employee work conditions in claim 1 is no more than generally linking the use of a judicial exception to a particular technological environment or field of use, as discussed in MPEP § 2106.05(h). As such, considering the claim limitations as an ordered combination, claims 1, 15 and 19 does not include significantly more than the abstract idea.
Claims 2, 16 and 20 further recites determining a building type associated with the workplace, wherein selecting the one or more work condition elements is further based on the building type associated with the workplace. With the broadest reasonable interpretation, the cited features contains steps people go through in their minds since it involves evaluation or judgement or using pen and paper. (MPEP 2106.04(a)(2)(III)) For example, a person could mentally, or using pen and paper, determine a building type associated with the workplace and select the work condition elements based on certain information. So it falls under the mental process of abstract ideas. The claim does not include any additional element, thus, it does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception.
Claims 3 and 17 further recites determining one or more types of workers associated with the workplace, wherein selecting the one or more work condition elements is further based on the one or more types of worker associated with the workplace. With the broadest reasonable interpretation, the cited features contains steps people go through in their minds since it involves evaluation or judgement, or using pen and paper. (MPEP 2106.04(a)(2)(III)) For example, a person could mentally, or using pen and paper, determine types of workers associated with the workplace and select the work condition elements based on certain information. So it falls under the mental process of abstract ideas. The claim does not include any additional element, thus, it does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception.
Claims 4 and 18 further recites determining one or more operations associated with the workplace, wherein selecting the one or more work condition elements is further based on the one or more operations associated with the workplace. With the broadest reasonable interpretation, the cited features contains steps people go through in their minds since it involves evaluation or judgement, or using pen and paper. (MPEP 2106.04(a)(2)(III)) For example, a person could mentally, or using pen and paper, determine operations related information associated with the workplace and select the work condition elements based on operation related information. So it falls under the mental process of abstract ideas. The claim does not include any additional element, thus, it does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception.
Claim 5 recites “wherein, for a given work condition element, evaluating the plurality of workspaces based on the work condition element includes: generating, for each workspace of the plurality of workspaces, a workspace value corresponding to the workspace, wherein generating the element value corresponding to the work condition element is further based on workspace values corresponding to the plurality of workspaces” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(III)). For example, a person could make a mental evaluation for the workspaces and generate workspace value and element value based on certain information. Therefore, this claim limitation does not recite additional elements that are sufficient to amount to significantly more than the abstract idea. Therefore, claim 5 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea.
Claim 6 recites “wherein, for a given work condition element, evaluating the plurality of workspaces based on the work condition element includes determining, for each workspace of the plurality of workspaces, whether the workspace satisfies the work condition element” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(III)). For example, a person could make a mental evaluation for the workspaces and determine if the workspace satisfies the work condition element based on certain information. Therefore, this claim limitation does not recite additional elements that are sufficient to amount to significantly more than the abstract idea. Therefore, claim 6 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea.
Claim 7 recites “wherein, for a second work condition element indicating views to outside of the building, evaluating the plurality of workspaces based on the second work condition element includes generating a plurality of view rays from the plurality of workspaces to a target destination” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(III)). For example, a person could make a mentally evaluation for the workspaces and generates paths or view rays. Therefore, this claim limitation does not recite additional elements that are sufficient to amount to significantly more than the abstract idea. Therefore, claim 7 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea.
Claim 8 recites “identifying a subset of view rays of the plurality of view rays, wherein each view ray of the subset of view rays is unobstructed, wherein generating a second element value corresponding to the second work condition element is based on the subset of view rays” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(III)). For example, a person could make a mental identification or observation for the view rays which are obstructed and generate the element value. Therefore, this claim limitation does not recite additional elements that are sufficient to amount to significantly more than the abstract idea. Therefore, claim 8 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea.
Claim 10 recites “identifying a subset of rays of the plurality of rays, wherein each ray of the subset of rays is unobstructed, wherein generating the particular element value corresponding to the particular work condition element is further based on the subset of rays” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(III)). For example, a person could make a mental identification or observation for the view rays which are obstructed and generate the element value. Therefore, this claim limitation does not recite additional elements that are sufficient to amount to significantly more than the abstract idea. Therefore, claim 10 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea.
Claim 11 recites “wherein evaluating the plurality of workspaces based on the work condition element includes generating a plurality of paths from the plurality of workspaces to a target destination” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(III)). Therefore, this claim limitation does not recite additional elements that are sufficient to amount to significantly more than the abstract idea. Therefore, claim 11 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea.
Claim 12 recites “calculating, for each path of the plurality of paths, a length of the path; and identifying a subset of paths of the plurality of paths, wherein the length of each path in the subset of paths is within a threshold value, wherein generating the element value corresponding to the work condition element is further based on the subset of paths” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(III)). For example, a person could mentally, or using pen and paper, calculate travel time associate with the path and evaluate if the subsets within a threshold value based on certain information. Therefore, this claim limitation does not recite additional elements that are sufficient to amount to significantly more than the abstract idea. Therefore, claim 12 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea.
Claim 13 recites “calculating, for each path of the plurality of paths, a travel time associated with the path; and identifying a subset of paths of the plurality of paths, wherein the travel time associated with each path in the subset of paths is within a threshold value, wherein generating the element value corresponding to the work condition element is further based on the subset of paths” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(III)). For example, a person could mentally, or using pen and paper, calculate travel time associate with the path and evaluate if the subsets within a threshold value based on certain information. Therefore, this claim limitation does not recite additional elements that are sufficient to amount to significantly more than the abstract idea. Therefore, claim 13 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea.
Claim 14 recites “normalizing the overall work condition value, based on the one or more work condition elements, to generate a normalized overall work condition value” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(III)). For example, a person could mentally, or using pen and paper, normalize the overall work condition value to a building design based on certain information. Therefore, this claim limitation does not recite additional elements that are sufficient to amount to significantly more than the abstract idea. Therefore, claim 14 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea.
Claim 21 recites “wherein the direction of the target source is further determined based on at least one of an orientation of the building or a location of the building.” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(III)). Therefore, this claim limitation does not recite additional elements that are sufficient to amount to significantly more than the abstract idea. Therefore, claim 21 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea.
Claim 24 recites “wherein the direction of the target source is further determined based on location data or landmark information from a map location database” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(III)). Therefore, this claim limitation does not recite additional elements that are sufficient to amount to significantly more than the abstract idea. Therefore, claim 24 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea.
Claim 25 recites “identifying a subset of rays of the plurality of rays, wherein each ray of the subset of rays is unobstructed, wherein generating the particular element value corresponding to the particular work condition element is based on a first total number of rays in the subset of rays compared to a second total number of rays in the plurality of rays” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(III)). Therefore, this claim limitation does not recite additional elements that are sufficient to amount to significantly more than the abstract idea. Therefore, claim 25 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea.
Claim 27 recites “wherein the site data further includes one or more locations of fixed equipment within the site”. It is recited at a high level of generality (i.e., as a general means of gathering data), and amounts to mere data gathering and is found as the insignificant extra-solution activity and cannot contribute an inventive concept. (See MPEP 2106.05(g)) and is well-understood, routine or conventional. ((See MPEP 2106.05 (d)(i))) Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745
(Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788
F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives
and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245,
1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014). Therefore, claim 27 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea.
Claim 28 recites “identifying a subset of rays of the plurality of rays, wherein each ray of the subset of rays is unobstructed, wherein the particular element value corresponding to the particular work condition element is equal to the first total number of rays in the subset of rays divided by a second total number of rays in the plurality of rays” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(III)). Therefore, this claim limitation does not recite additional elements that are sufficient to amount to significantly more than the abstract idea. Therefore, claim 25 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea.
Claim Rejections - 35 USC § 103
7. 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 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.
8. 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
9. Claims 1-8, 10-12, 14-21, 24 and 27 are rejected under 35 U.S.C. 103 as being unpatentable over BENJAMIN et al. (PUB NO: US 20180137214 A1) in view of Harrison et al. (PUB NO: US 20200060007 A1) and further in view of Marceau et al. (PUB NO: US 20150234945 A1)
Regarding claim 1
BENJAMIN teaches a computer-implemented method for computationally determining employee work conditions, (see para 002-Embodiments of the present invention relate generally to computer-aided design and manufacturing and, more specifically, to generative design for architecture. see para 41-FIG. 2 is a more detailed illustration of the design engine of FIG. 1, according to various embodiments of the present invention. As shown, design engine 120 includes a survey module 200, a geometry module 210, and a metric module 220. Survey module 200 is configured to conduct a survey to gather input 202 from potential occupants of the structure being designed. The survey conducted by survey module 200 includes inquiries concerning the working preferences of potential occupants)
processing, via a computer-aided design (CAD) application being executed by a processor, (see para 002 and fig 1-Embodiments of the present invention relate generally to computer-aided design and manufacturing and, more specifically, to generative design for architecture.)
a building layout comprising a three-dimensional (3D) model of a building, (See para 52 and fig 5- FIG. 5 illustrates how the mesh generator of FIG. 4 generates an initial geometrical mesh for a given design option, according to various embodiments of the present invention. Design area 510 defines a region within initial layout 500 where the structure being designed is meant to reside, while open area 520 defines an area that is separate from that structure, such as a parking lot or courtyard. Mesh generator 400 is configured to process initial layout 500, design area 510 and open area 520 and then generate a mesh 512. Mesh 512 defines a coordinate system according to which additional geometrical constructions can be defined. Mesh 512 may be a two-dimensional grid (2D) representing a single floor of a structure, a stack of 2D grids representing multiple floors of a multi-story structure, or a 3D grid representing a volume of space associated with the structure.)
the building layout specifying, for each workspace of a plurality of workspaces included in a workplace, a respective location of the workspace, (see para 55-FIG. 8 illustrates how the neighborhood generator of FIG. 4 generates neighborhoods from different subdivisions, according to various embodiments of the present invention. As shown, neighborhood generator 420 shifts each neighborhood seed point 700 to generate a neighborhood center 800. Each neighborhood center 800 corresponds to a different neighborhood 802. A given neighborhood 802 is a communal workspace that can be occupied by a team or workgroup of potential occupants. see para 57-58- FIG. 9 illustrates how the fixture generator of FIG. 4 generates amenity zones within different neighborhoods, according to various embodiments of the present invention. As shown, fixture generator 430 identifies an edge of each neighborhood 802 and then designates an adjacent zone 900 for an amenity cluster. An amenity cluster may include a variety of different types of fixtures. In the context of a workplace, those fixtures may include a kitchen, a lounge, a coffee bar, a bathroom, a private office, a conference room, a workstation, and so forth. In other design contexts, fixtures may include factory equipment, stadium seating, serving stations, self-checkout machines, and so forth. FIG. 10 illustrates how the fixture generator of FIG. 4 populates different neighborhoods with fixtures, according to various embodiments of the present invention. As shown, fixture generator 430 populates zones 900 with specific amenity clusters 1000 and also places groups of desks 1010 adjacent to those clusters. For example, as mentioned above, fixture generator 430 could populate the various neighborhoods 802 with factory equipment when the structure being designed is a factory. Fixture generator 430 may distribute fixtures according to a variety of different techniques, although generally fixture generator 430 allocates an appropriate, and possibly predefined, amount of space to each fixture. Once those fixtures are distributed, the geometry of design option 214 is complete. See para 67-Graph analyzer 1400 is configured to analyze a design option 214 and then generate layout graph 1300. Layout graph 1300 is a mathematical graph of nodes and edges. Each node of the graph represents a location where a potential occupant may be stationary for some amount of time. For example, a given node could be the desk of a potential occupant. Each edge of the graph represents a path a potential occupant may traverse. For example, a given edge could represent a path from a stairwell to conference room.)
Examiner note: Examiner consider fixtures (such as amenities 1000, desks 1010, workstation) in neighborhood 802 are the plurality of workspaces in a building layout.
wherein the CAD application processes the building layout by:
selecting one or more work condition elements from a plurality of work condition elements based at least on the plurality of workspaces; (see para 41-The survey conducted by survey module 200 includes inquiries concerning the working preferences of potential occupants. For example, the survey could request that a potential occupant select a desired noise level for a workstation to be assigned to the occupant. The survey could also request that the potential occupant select a desired proximity to different amenities, such as a kitchen or bathroom, or desired proximity to different co-occupants. see para 57-60- In the context of a workplace, those fixtures may include a kitchen, a lounge, a coffee bar, a bathroom, a private office, a conference room, a workstation, and so forth. FIG. 11 illustrates how the team distributor of FIG. 4 distributes teams within a given design option, according to various embodiments of the present invention. As discussed above in conjunction with FIG. 2, criteria 204 reflects the working preferences of each potential occupant. Those working preferences may include desired distances to various amenities, centrality within the overarching workspace, exposure to traffic or other distractions, and so forth. Criteria 204 also indicates team membership for each potential occupant, as mentioned. In the context of this disclosure, a “team” simply refers to a group of potential occupants who should be assigned to the same neighborhood. In the context of a typical office, a team could refer to a department, such as “accounting” or “engineering,” as shown in FIG. 11, for example. Team distributor 440 is configured to analyze the geometry of design option 214 and then distribute different teams of potential occupants across each neighborhood 802 in a manner that optimally addresses the specific working preferences of each occupant. Team distributor 440 may also assign potential occupants to specific neighborhoods 802 based on overall team preferences aggregated across team members. Team distributor 440 may implement a “best fit” algorithm in order to generate a team distribution that matches teams to neighborhoods 802. Team distributor 440 may determine the degree to which any particular criteria 204 is met based on the set of metrics 222 computed by metric module 220)
Examiner note: Team distributor distributes one or more types of workers or personnel associated with the building by selecting one or more work condition elements that reflect the working preference of potential occupants. Those working preferences may include desired noise level for a workstation, desired distances to various amenities, centrality within the overarching workspace, exposure to traffic or other distractions, and so forth which is the working condition element for each occupant.
for each work condition element of the one or more work condition elements: evaluating the plurality of workspaces based on the work condition element including, for a particular work condition element indicating at least one of an amount of natural light exposure or an amount of glare from a target source, (See [0071] -View grid 1442 indicates the number of view to the outside from each desk within design option 214. See also [0080]-0082- View analyzer 1440 constructs a different set of visual zones for each desk in design option 214 in order to determine the number of views to outward facing windows 1820 from each desk. View analyzer 1440 also determines the number of views to outward facing windows 1830 from high circulation nodes 1630. View analyzer 1440 then computes, for each potential occupant, the number of views the occupant has from the desk assigned to that occupant, as well as the number of views the occupant has from any high circulation nodes the occupant traverses. View analyzer 1440 then computes view metric 1444 to reflect these values. View analyzer 1440 aggregates the per-occupant view metrics across all occupants and floors of design option 214 to generate an overall view metric for design option 214. View analyzer 214 may then average this metric across all desks to create a per-desk view metric. FIG. 19 is a more detailed illustration of the daylight grid of FIG. 14, according to various embodiments of the present invention. As shown, exemplary daylight grid 1900 includes high flux nodes 1910, medium flux nodes 1920, and low flux nodes 1930. High flux nodes 1910 receive the most natural sunlight, averaged across each day of the year. Medium flux nodes 1920 receive a moderate amount of sunlight on average, and low flux nodes 1930 receive the least amount of natural sunlight during the year. Daylight analyzer 1450 generates daylight grid 1900 using a daylight simulator program. Daylight analyzer 1450 may then identify nodes that meet certain recommended criteria, and group these nodes into different categories, such as high flux, medium flux, and low flux, for example. Daylight analyzer 1450 then generates daylight metric 1454 to indicate the overall amount of natural light expected to flow through design option 214 per grid square. Daylight metric 1454 may also indicate the number of grid squares that meet a given daylight flux standard. A given workstyle metric 1464 generated for any particular occupant indicates the degree to which the desk assigned to that occupant provides (i) a preferred amount of natural lighting and (ii) preferred exposure to high circulation nodes and other sources of activity, noise, and/or distractions.)
based on the evaluating the plurality of workspaces, generating an element value corresponding to the work condition element including generating a particular element value corresponding to the particular work condition element; (see also [0082]-A given workstyle metric 1464 generated for any particular occupant indicates the degree to which the desk assigned to that occupant provides (i) a preferred amount of natural lighting and (ii) preferred exposure to high circulation nodes and other sources of activity, noise, and/or distractions. These preferences are indicated in criteria 204 per occupant. Workstyle analyzer 1460 aggregates individual workstyle metrics across teams within neighborhoods 802 and across floors in design option 214 to generate an overall workstyle metric 1464. Workstyle analyzer 1460 may also average this global metric based on the number of desks assigned in design option 214)
computing, based on element values corresponding to the one or more work condition elements, an overall work condition value associated with the building layout; (see para 82-Based on daylight grid 1900, and also based on circulation grid 1600 shown in FIG. 16, workstyle analyzer 1460 is configured to generate a separate workstyle metric 1464 for each potential occupant. A given workstyle metric 1464 generated for any particular occupant indicates the degree to which the desk assigned to that occupant provides (i) a preferred amount of natural lighting and (ii) preferred exposure to high circulation nodes and other sources of activity, noise, and/or distractions. These preferences are indicated in criteria 204 per occupant. Workstyle analyzer 1460 aggregates individual workstyle metrics across teams within neighborhoods 802 and across floors in design option 214 to generate an overall workstyle metric 1464. Workstyle analyzer 1460 may also average this global metric based on the number of desks assigned in design option 214. See also para 87- Metric module 220 may also combine the metrics for any given design option 214 into a single metric indicating how closely the design option 214 meets criteria 204.) and
modifying the building layout of the building based on the overall work condition value to generate an additional building layout of the building. (see para 53- Generative regions 600 represent portions of design area 510 where geometry module 210 generates and modifies geometry during a generative design process. see para 87- Metric module 220 implements the method 2000 iteratively across all design options 214 to generate a different set of metrics 222 for each such design option. Metric module 220 may implement each step of the method 2000 in parallel for improved computational throughput. Metric module 220 may also combine the metrics for any given design option 214 into a single metric indicating how closely the design option 214 meets criteria 204. Metric module 220 may also display the metrics for any given design option 214 separately in a format such as a radial graph. These approaches provide a quantifiable means to rate each design option, allowing those options to be readily analyzed by interested parties. In addition, these metrics provide objective functions that can be optimized via the generative design process performed by geometry engine 210. See also para 108-18. The non-transitory computer-readable medium of any of clauses 11, 12, 13, 14, 15, 16, and 17, further comprising the step of generating a spectrum of varied design options by iteratively: generating varied geometry by modifying a previous design option, separating the varied geometry into alternative subdivisions based on modified construction parameters, generating one or more neighborhoods based on the alternative subdivisions, and distributing a group of potential occupants across the one or more neighborhoods based on a set of design criteria to generate a given design option.)
processing, via the CAD application, the additional building layout comprising an additional 3D model of the building by computing an additional overall work condition value associated with the additional building layout; (see para 002 and fig 1-Embodiments of the present invention relate generally to computer-aided design and manufacturing and, more specifically, to generative design for architecture. See para 52 and fig 5- FIG. 5 illustrates how the mesh generator of FIG. 4 generates an initial geometrical mesh for a given design option, according to various embodiments of the present invention. Design area 510 defines a region within initial layout 500 where the structure being designed is meant to reside, while open area 520 defines an area that is separate from that structure, such as a parking lot or courtyard. Mesh generator 400 is configured to process initial layout 500, design area 510 and open area 520 and then generate a mesh 512. Mesh 512 defines a coordinate system according to which additional geometrical constructions can be defined. Mesh 512 may be a two-dimensional grid (2D) representing a single floor of a structure, a stack of 2D grids representing multiple floors of a multi-story structure, or a 3D grid representing a volume of space associated with the structure. see para 82-Based on daylight grid 1900, and also based on circulation grid 1600 shown in FIG. 16, workstyle analyzer 1460 is configured to generate a separate workstyle metric 1464 for each potential occupant. A given workstyle metric 1464 generated for any particular occupant indicates the degree to which the desk assigned to that occupant provides (i) a preferred amount of natural lighting and (ii) preferred exposure to high circulation nodes and other sources of activity, noise, and/or distractions. These preferences are indicated in criteria 204 per occupant. Workstyle analyzer 1460 aggregates individual workstyle metrics across teams within neighborhoods 802 and across floors in design option 214 to generate an overall workstyle metric 1464. Workstyle analyzer 1460 may also average this global metric based on the number of desks assigned in design option 214. See also para 87- Metric module 220 may also combine the metrics for any given design option 214 into a single metric indicating how closely the design option 214 meets criteria 204.) and
displaying, via a graphical user interface, (see para 35- I/O devices 114 may include devices configured to receive input, including, for example, a keyboard, a mouse, and so forth. I/O devices 114 may also include devices configured to provide output, including, for example, a display device, a speaker, and so forth. see para 87-Metric module 220 may also display the metrics for any given design option 214 separately in a format such as a radial graph)a comparison between the overall work condition value of the building layout and the additional overall work condition value of the additional building layout that indicates the additional overall work condition value of the additional building layout is improved relative to the overall work condition value of the building layout; (see para 32-The design engine analyzes each design option and then generates, for any given design option, a set of metrics that indicates how well the given design option meets the multiple design criteria. The design engine may then generate additional spectrums of design options in an evolutionary manner to improve the metrics for any given design option. Advantageously, designers can generate a multitude of design options that addresses a range of design criteria in a quantifiable and metric-based manner. See para 44-45- Metric module 220 is configured to process criteria 204 and design options 214 to generate a set of metrics 222. Metrics 222 rate the degree to which each design option 214 meets criteria 204. Geometry module 210 is configured to process metrics 222 to generate additional sets of design options 214. Metric module 220 then generates additional sets of metrics based on the additional sets of design options. This process may repeat iteratively across numerous cycles. Geometry module 210 generates design options 214 in a manner that may improve metrics 222 across many such cycles.)
and identifying the additional building layout as an optimal building layout for implementation in the building. (see para 40-As described in greater detail below in conjunction with FIG. 2, design engine 120 is configured to collect design criteria and design constraints associated with an architectural design project, and then generate a spectrum of design options for a structure being designed. Design engine 120 then analyzes those design options to identify the degree to which each design option meets the various design criteria. The design engine implements an evolutionary approach to generate additional spectrums of design options based on how closely previous design options meet the design criteria. see para 88-In sum, a design engine includes a geometry module and a metric module that interoperate to generate optimal design options. The geometry module then generates additional design options in an evolutionary manner to improve the metrics generated for subsequent design options.)
BENJAMIN does not teach determining a direction of the target source based on site data that describes a site that includes the building, wherein the site data includes a location of the site, an orientation of the site, an elevation of the site, a topography of the site, a location of an adjacent site, an orientation of the adjacent site, and elevation of the adjacent site, and a topography of the adjacent site and generating based on the direction of the target source, a plurality of rays from a target source to the plurality of workspaces, wherein the plurality of rays represents natural light and the plurality of workspaces are further evaluated based on the plurality of rays.
In the related field of invention, Harrison teaches determining a direction of the target source based on site data that describes a site that includes building; (see para 203-The lighting space objects 220 may also include natural light sources, such as coming from windows. see para 302- IES files may include a two-dimensional characterization I (θ, φ), which may represent the luminous flux in a given direction defined by θ and φ. In embodiments, this data may be gathered using a goniophotometer to measure light at different angles and at large distances relative to the size of a lighting fixture such as more than 10× the size of a lighting fixture object 230. The approach may include rotating a lighting fixture object 230 to measure the luminance of a lighting fixture object 230 at all angles. see para 404 In embodiments, design of lighting in an environment may be configured to emulate natural light effects, such as sunrise, sunset, and the like. Additionally, lighting design may emulate other natural light effects, such as sunlight impacting a window or skylight and the like. Control of lights that coordinate with a time of day (e.g., the path of the sun through the sky), a weather forecast (e.g., clouds, full sunshine, partial sunshine, and the like), and the like may further enhance emulating a natural effect of exterior sunlight. See para 413- In embodiments, lighting design may further be enhanced through integration of data sources, such as architectural plans, including material choices, line of sight aspects, building orientation, impacts on natural light from nearby buildings and the like may be combined with light source specific information such lighting as near field characterization data and the like to develop a multi-dimensional understanding of factors that impact a lighting design plan for a space.)
Examiner note: Integrating building orientation into lighting design is about leveraging natural light by understanding its path and behavior within the building space, which in turn, impacts lighting design decisions like window placement, shading strategies, and the overall integration of natural and artificial lighting.
generating based on the direction of target source, a plurality of rays from the target source to the plurality of workspaces, wherein the plurality of rays represents natural light and the plurality of workspaces are further evaluated based on the plurality of rays. (see para 203-The lighting space objects 220 may also include natural light sources, such as coming from windows. see para 265- Relevant properties may include lighting properties, such as the distribution of light on the lighting space objects 220 (such as the distribution of light on tables, desks, or workspaces). see fig 43 and para 342-ray traces 4304, reflections 4306, and interactions among ray traces and reflections 4308 for light being transmitted from a light source 4301 in an environment including features such as a desk 4310, wall 4312 and the like. See para 290- In embodiments, the platform may store a space utilization data structure that indicates, over time, how people use the space of the lighting installation, such as indicating what hallways are more trafficked, and the like. This may inform understanding of a space, such as indicating what is an entry, what is a passage, what is a workspace, and the like, which may be used to suggest changes or updates to a lighting design. See also para 442- Model-based rendering may include modeling of light source emissions as a set of direction-specific light ray-traces.)
Therefore, 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 method of generating and evaluating optimal architectural designs as disclosed by BENJAMIN to include determining a direction of the target source based on site data that describes a site that includes building and generating based on the direction of the target source, a plurality of rays from the target source to the plurality of workspaces, wherein the plurality of rays represents natural light and the plurality of workspaces are further evaluated based on the plurality of rays as taught by Harrison in the system of BENJAMIN for enhancing a lighting design through integration of data sources, such as architectural plans, including material choices, line of sight aspects, building orientation, impacts on natural light from nearby buildings and the like with light source specific information such as near field characterization data and the like to develop a multi-dimensional understanding of factors that impact a lighting design plan for a workspace. (See para 0413, Harrison)
The combination of BENJAMIN and Harrison does not teach wherein the site data includes a location of the site, an orientation of the site, an elevation of the site, a topography of the site, a location of an adjacent site, an orientation of the adjacent site, an elevation of the adjacent site, and a topography of the adjacent site.
However, Marceau further teaches wherein the site data includes a location of the site, (see para 83-a location for the subject architectural structure is determined. In some instances, the geographic location may be a specific latitude and longitude of the building site) an orientation of the site, an elevation of the site, a topography of the site. (see para 83-85- These can include, for example, external reflecting surfaces (e.g., lakes, oceans, other bodies of water, reflective buildings adjacent to the proposed site, and so on), external sources of shading (e.g., large building or structures, adjacent mountains or other geographic features, large trees, and so on), as well as internal reflecting surfaces or sources of shading (e.g., walls, ceilings, floors, and so on). see para 90- In other words, factors such as window and door placement, building orientation, building height, glazing, and other like design options can all contribute to the daylighting analysis and hence the spatial daylight autonomy of the structure.)
a location of an adjacent site, an orientation of the adjacent site, an elevation of the adjacent site, and a topography of the adjacent site. (See para 83-85 Likewise other structures adjacent to a particular building site may impact the daylighting analysis. For example, a building site surrounded by skyscrapers or other tall structures can be shaded by the structures, especially on the lower floors, and this can impact the daylighting analysis of an architectural structure on that site. Likewise, highly reflective surfaces on adjacent buildings (e.g. highly reflective glazing) can also impact the daylighting analysis of an architectural structure on that site. These can include, for example, external reflecting surfaces (e.g., lakes, oceans, other bodies of water, reflective buildings adjacent to the proposed site, and so on), external sources of shading (e.g., large building or structures, adjacent mountains or other geographic features, large trees, and so on), as well as internal reflecting surfaces or sources of shading (e.g., walls, ceilings, floors, and so on). In some embodiments, these external and/or internal contributors can be part of the sky model used to calculate the luminance of the sky and surrounding environment At operation 1604, the architectural structure analysis system parameterizes the architectural structure for the daylighting analysis. In some embodiments, the same set of parameter values that are used for the energy impact analysis can also be used for the daylighting analysis. In other words, factors such as window and door placement, building orientation, building height, glazing, and other like design options can all contribute to the daylighting analysis and hence the spatial daylight autonomy of the structure.)
Therefore, 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 method of generating and evaluating optimal architectural designs as disclosed by BENJAMIN and Harrison to include wherein the site data includes a location of the site, an orientation of the site, an elevation of the site, a topography of the site, a location of an adjacent site, an orientation of the adjacent site, an elevation of the adjacent site, and a topography of the adjacent site as taught by Marceau in the system of BENJAMIN and Harrison in order to compute the impact of daylighting on an architectural structure, simulations based on hourly local weather data in the designated geographic location of the architectural structure are performed to estimate the annual daylight availability at that location. This, in turn, is applied to the architectural structure to reduce the amount of electricity needed to provide sufficient worksurface lighting by fluorescent, incandescent, or other artificial light sources. (See para 0006-0007, Marceau)
Regarding claim 15 and 19
BENJAMIN teaches one or more non-transitory computer readable media storing instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of claim 15(see fig 1)
a computer system, comprising: a memory storing instructions; and one or more processors for executing the instructions of claim 19 (see fig 1)
processing, via a computer-aided design (CAD) application being executed by a processor, (see para 002 and fig 1-Embodiments of the present invention relate generally to computer-aided design and manufacturing and, more specifically, to generative design for architecture.)
a building layout comprising a three-dimensional (3D) model of a building, (See para 52 and fig 5- FIG. 5 illustrates how the mesh generator of FIG. 4 generates an initial geometrical mesh for a given design option, according to various embodiments of the present invention. Design area 510 defines a region within initial layout 500 where the structure being designed is meant to reside, while open area 520 defines an area that is separate from that structure, such as a parking lot or courtyard. Mesh generator 400 is configured to process initial layout 500, design area 510 and open area 520 and then generate a mesh 512. Mesh 512 defines a coordinate system according to which additional geometrical constructions can be defined. Mesh 512 may be a two-dimensional grid (2D) representing a single floor of a structure, a stack of 2D grids representing multiple floors of a multi-story structure, or a 3D grid representing a volume of space associated with the structure.)
the building layout specifying, for each workspace of a plurality of workspaces included in a workplace, a respective location of the workspace, (see para 55-FIG. 8 illustrates how the neighborhood generator of FIG. 4 generates neighborhoods from different subdivisions, according to various embodiments of the present invention. As shown, neighborhood generator 420 shifts each neighborhood seed point 700 to generate a neighborhood center 800. Each neighborhood center 800 corresponds to a different neighborhood 802. A given neighborhood 802 is a communal workspace that can be occupied by a team or workgroup of potential occupants. see para 57-58- FIG. 9 illustrates how the fixture generator of FIG. 4 generates amenity zones within different neighborhoods, according to various embodiments of the present invention. As shown, fixture generator 430 identifies an edge of each neighborhood 802 and then designates an adjacent zone 900 for an amenity cluster. An amenity cluster may include a variety of different types of fixtures. In the context of a workplace, those fixtures may include a kitchen, a lounge, a coffee bar, a bathroom, a private office, a conference room, a workstation, and so forth. In other design contexts, fixtures may include factory equipment, stadium seating, serving stations, self-checkout machines, and so forth. FIG. 10 illustrates how the fixture generator of FIG. 4 populates different neighborhoods with fixtures, according to various embodiments of the present invention. As shown, fixture generator 430 populates zones 900 with specific amenity clusters 1000 and also places groups of desks 1010 adjacent to those clusters. For example, as mentioned above, fixture generator 430 could populate the various neighborhoods 802 with factory equipment when the structure being designed is a factory. Fixture generator 430 may distribute fixtures according to a variety of different techniques, although generally fixture generator 430 allocates an appropriate, and possibly predefined, amount of space to each fixture. Once those fixtures are distributed, the geometry of design option 214 is complete. See para 67-Graph analyzer 1400 is configured to analyze a design option 214 and then generate layout graph 1300. Layout graph 1300 is a mathematical graph of nodes and edges. Each node of the graph represents a location where a potential occupant may be stationary for some amount of time. For example, a given node could be the desk of a potential occupant. Each edge of the graph represents a path a potential occupant may traverse. For example, a given edge could represent a path from a stairwell to conference room.)
Examiner note: Examiner consider fixtures (such as amenities 1000, desks 1010, workstation) in neighborhood 802 are the plurality of workspaces in a building layout.
wherein the CAD application processes the building layout by:
selecting one or more work condition elements from a plurality of work condition elements based at least on the plurality of workspaces; (see para 41-The survey conducted by survey module 200 includes inquiries concerning the working preferences of potential occupants. For example, the survey could request that a potential occupant select a desired noise level for a workstation to be assigned to the occupant. The survey could also request that the potential occupant select a desired proximity to different amenities, such as a kitchen or bathroom, or desired proximity to different co-occupants. see para 57-60- In the context of a workplace, those fixtures may include a kitchen, a lounge, a coffee bar, a bathroom, a private office, a conference room, a workstation, and so forth. FIG. 11 illustrates how the team distributor of FIG. 4 distributes teams within a given design option, according to various embodiments of the present invention. As discussed above in conjunction with FIG. 2, criteria 204 reflects the working preferences of each potential occupant. Those working preferences may include desired distances to various amenities, centrality within the overarching workspace, exposure to traffic or other distractions, and so forth. Criteria 204 also indicates team membership for each potential occupant, as mentioned. In the context of this disclosure, a “team” simply refers to a group of potential occupants who should be assigned to the same neighborhood. In the context of a typical office, a team could refer to a department, such as “accounting” or “engineering,” as shown in FIG. 11, for example. Team distributor 440 is configured to analyze the geometry of design option 214 and then distribute different teams of potential occupants across each neighborhood 802 in a manner that optimally addresses the specific working preferences of each occupant. Team distributor 440 may also assign potential occupants to specific neighborhoods 802 based on overall team preferences aggregated across team members. Team distributor 440 may implement a “best fit” algorithm in order to generate a team distribution that matches teams to neighborhoods 802. Team distributor 440 may determine the degree to which any particular criteria 204 is met based on the set of metrics 222 computed by metric module 220)
Examiner note: Team distributor distributes one or more types of workers or personnel associated with the building by selecting one or more work condition elements that reflect the working preference of potential occupants. Those working preferences may include desired noise level for a workstation, desired distances to various amenities, centrality within the overarching workspace, exposure to traffic or other distractions, and so forth which is the working condition element for each occupant.
for each work condition element of the one or more work condition elements: evaluating the plurality of workspaces based on the work condition element including, for a particular work condition element indicating at least one of an amount of natural light exposure or an amount of glare, (See [0071] -View grid 1442 indicates the number of view to the outside from each desk within design option 214. See also [0080]-0082- View analyzer 1440 constructs a different set of visual zones for each desk in design option 214 in order to determine the number of views to outward facing windows 1820 from each desk. View analyzer 1440 also determines the number of views to outward facing windows 1830 from high circulation nodes 1630. View analyzer 1440 then computes, for each potential occupant, the number of views the occupant has from the desk assigned to that occupant, as well as the number of views the occupant has from any high circulation nodes the occupant traverses. View analyzer 1440 then computes view metric 1444 to reflect these values. View analyzer 1440 aggregates the per-occupant view metrics across all occupants and floors of design option 214 to generate an overall view metric for design option 214. View analyzer 214 may then average this metric across all desks to create a per-desk view metric. FIG. 19 is a more detailed illustration of the daylight grid of FIG. 14, according to various embodiments of the present invention. As shown, exemplary daylight grid 1900 includes high flux nodes 1910, medium flux nodes 1920, and low flux nodes 1930. High flux nodes 1910 receive the most natural sunlight, averaged across each day of the year. Medium flux nodes 1920 receive a moderate amount of sunlight on average, and low flux nodes 1930 receive the least amount of natural sunlight during the year. Daylight analyzer 1450 generates daylight grid 1900 using a daylight simulator program. Daylight analyzer 1450 may then identify nodes that meet certain recommended criteria, and group these nodes into different categories, such as high flux, medium flux, and low flux, for example. Daylight analyzer 1450 then generates daylight metric 1454 to indicate the overall amount of natural light expected to flow through design option 214 per grid square. Daylight metric 1454 may also indicate the number of grid squares that meet a given daylight flux standard. A given workstyle metric 1464 generated for any particular occupant indicates the degree to which the desk assigned to that occupant provides (i) a preferred amount of natural lighting and (ii) preferred exposure to high circulation nodes and other sources of activity, noise, and/or distractions.)
based on the evaluating the plurality of workspaces, generating an element value corresponding to the work condition element including generating a particular element value corresponding to the particular work condition element; (see also [0082]-A given workstyle metric 1464 generated for any particular occupant indicates the degree to which the desk assigned to that occupant provides (i) a preferred amount of natural lighting and (ii) preferred exposure to high circulation nodes and other sources of activity, noise, and/or distractions. These preferences are indicated in criteria 204 per occupant. Workstyle analyzer 1460 aggregates individual workstyle metrics across teams within neighborhoods 802 and across floors in design option 214 to generate an overall workstyle metric 1464. Workstyle analyzer 1460 may also average this global metric based on the number of desks assigned in design option 214)
computing, based on element values corresponding to the one or more work condition elements, an overall work condition value associated with the building layout; (see para 82-Based on daylight grid 1900, and also based on circulation grid 1600 shown in FIG. 16, workstyle analyzer 1460 is configured to generate a separate workstyle metric 1464 for each potential occupant. A given workstyle metric 1464 generated for any particular occupant indicates the degree to which the desk assigned to that occupant provides (i) a preferred amount of natural lighting and (ii) preferred exposure to high circulation nodes and other sources of activity, noise, and/or distractions. These preferences are indicated in criteria 204 per occupant. Workstyle analyzer 1460 aggregates individual workstyle metrics across teams within neighborhoods 802 and across floors in design option 214 to generate an overall workstyle metric 1464. Workstyle analyzer 1460 may also average this global metric based on the number of desks assigned in design option 214. See also para 87- Metric module 220 may also combine the metrics for any given design option 214 into a single metric indicating how closely the design option 214 meets criteria 204.) and
processing, via the CAD application, the additional building layout comprising an additional 3D model of the building by computing an additional overall work condition value associated with the additional building layout; (see para 002 and fig 1-Embodiments of the present invention relate generally to computer-aided design and manufacturing and, more specifically, to generative design for architecture. See para 52 and fig 5- FIG. 5 illustrates how the mesh generator of FIG. 4 generates an initial geometrical mesh for a given design option, according to various embodiments of the present invention. Design area 510 defines a region within initial layout 500 where the structure being designed is meant to reside, while open area 520 defines an area that is separate from that structure, such as a parking lot or courtyard. Mesh generator 400 is configured to process initial layout 500, design area 510 and open area 520 and then generate a mesh 512. Mesh 512 defines a coordinate system according to which additional geometrical constructions can be defined. Mesh 512 may be a two-dimensional grid (2D) representing a single floor of a structure, a stack of 2D grids representing multiple floors of a multi-story structure, or a 3D grid representing a volume of space associated with the structure. see para 82-Based on daylight grid 1900, and also based on circulation grid 1600 shown in FIG. 16, workstyle analyzer 1460 is configured to generate a separate workstyle metric 1464 for each potential occupant. A given workstyle metric 1464 generated for any particular occupant indicates the degree to which the desk assigned to that occupant provides (i) a preferred amount of natural lighting and (ii) preferred exposure to high circulation nodes and other sources of activity, noise, and/or distractions. These preferences are indicated in criteria 204 per occupant. Workstyle analyzer 1460 aggregates individual workstyle metrics across teams within neighborhoods 802 and across floors in design option 214 to generate an overall workstyle metric 1464. Workstyle analyzer 1460 may also average this global metric based on the number of desks assigned in design option 214. See also para 87- Metric module 220 may also combine the metrics for any given design option 214 into a single metric indicating how closely the design option 214 meets criteria 204.) and
displaying, via a graphical user interface, (see para 35- I/O devices 114 may include devices configured to receive input, including, for example, a keyboard, a mouse, and so forth. I/O devices 114 may also include devices configured to provide output, including, for example, a display device, a speaker, and so forth. see para 87-Metric module 220 may also display the metrics for any given design option 214 separately in a format such as a radial graph)a comparison between the overall work condition value of the building layout and the additional overall work condition value of the additional building layout that indicates the additional overall work condition value of the additional building layout is improved relative to the overall work condition value of the building layout; (see para 32-The design engine analyzes each design option and then generates, for any given design option, a set of metrics that indicates how well the given design option meets the multiple design criteria. The design engine may then generate additional spectrums of design options in an evolutionary manner to improve the metrics for any given design option. Advantageously, designers can generate a multitude of design options that addresses a range of design criteria in a quantifiable and metric-based manner. See para 44-45- Metric module 220 is configured to process criteria 204 and design options 214 to generate a set of metrics 222. Metrics 222 rate the degree to which each design option 214 meets criteria 204. Geometry module 210 is configured to process metrics 222 to generate additional sets of design options 214. Metric module 220 then generates additional sets of metrics based on the additional sets of design options. This process may repeat iteratively across numerous cycles. Geometry module 210 generates design options 214 in a manner that may improve metrics 222 across many such cycles.)
and identifying the additional building layout as an optimal building layout for implementation in the building. (see para 40-As described in greater detail below in conjunction with FIG. 2, design engine 120 is configured to collect design criteria and design constraints associated with an architectural design project, and then generate a spectrum of design options for a structure being designed. Design engine 120 then analyzes those design options to identify the degree to which each design option meets the various design criteria. The design engine implements an evolutionary approach to generate additional spectrums of design options based on how closely previous design options meet the design criteria. see para 88-In sum, a design engine includes a geometry module and a metric module that interoperate to generate optimal design options. The geometry module then generates additional design options in an evolutionary manner to improve the metrics generated for subsequent design options.)
BENJAMIN does not teach determining a direction of the target source based on site data that describes a site that includes building, wherein the site data includes a location of the site, an orientation of the site, an elevation of the site, a topography of the site, a location of an adjacent site, an orientation of the adjacent site, an elevation of the adjacent site, and a topography of the adjacent site. and generating based on the direction of the target source, a plurality of rays from a target source to the plurality of workspaces, wherein the plurality of rays represents natural light and the plurality of workspaces are further evaluated based on the plurality of rays.
In the related field of invention, Harrison teaches determining a direction of the target source based on site data that describes a site that includes building; (see para 203-The lighting space objects 220 may also include natural light sources, such as coming from windows. see para 302- IES files may include a two-dimensional characterization I (θ, φ), which may represent the luminous flux in a given direction defined by θ and φ. In embodiments, this data may be gathered using a goniophotometer to measure light at different angles and at large distances relative to the size of a lighting fixture such as more than 10× the size of a lighting fixture object 230. The approach may include rotating a lighting fixture object 230 to measure the luminance of a lighting fixture object 230 at all angles. see para 404 In embodiments, design of lighting in an environment may be configured to emulate natural light effects, such as sunrise, sunset, and the like. Additionally, lighting design may emulate other natural light effects, such as sunlight impacting a window or skylight and the like. Control of lights that coordinate with a time of day (e.g., the path of the sun through the sky), a weather forecast (e.g., clouds, full sunshine, partial sunshine, and the like), and the like may further enhance emulating a natural effect of exterior sunlight. See para 413- In embodiments, lighting design may further be enhanced through integration of data sources, such as architectural plans, including material choices, line of sight aspects, building orientation, impacts on natural light from nearby buildings and the like may be combined with light source specific information such lighting as near field characterization data and the like to develop a multi-dimensional understanding of factors that impact a lighting design plan for a space.)
Examiner note: Integrating building orientation into lighting design is about leveraging natural light by understanding its path and behavior within the building space, which in turn, impacts lighting design decisions like window placement, shading strategies, and the overall integration of natural and artificial lighting.
generating based on the direction of target source, a plurality of rays from the target source to the plurality of workspaces, wherein the plurality of rays represents natural light and the plurality of workspaces are further evaluated based on the plurality of rays. (see para 203-The lighting space objects 220 may also include natural light sources, such as coming from windows. see para 265- Relevant properties may include lighting properties, such as the distribution of light on the lighting space objects 220 (such as the distribution of light on tables, desks, or workspaces). see fig 43 and para 342-ray traces 4304, reflections 4306, and interactions among ray traces and reflections 4308 for light being transmitted from a light source 4301 in an environment including features such as a desk 4310, wall 4312 and the like. See para 290- In embodiments, the platform may store a space utilization data structure that indicates, over time, how people use the space of the lighting installation, such as indicating what hallways are more trafficked, and the like. This may inform understanding of a space, such as indicating what is an entry, what is a passage, what is a workspace, and the like, which may be used to suggest changes or updates to a lighting design. See also para 442- Model-based rendering may include modeling of light source emissions as a set of direction-specific light ray-traces.)
Therefore, 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 method of generating and evaluating optimal architectural designs as disclosed by BENJAMIN to include determining a direction of the target source based on site data that describes a site that includes building and generating based on the direction of the target source, a plurality of rays from the target source to the plurality of workspaces, wherein the plurality of rays represents natural light and the plurality of workspaces are further evaluated based on the plurality of rays as taught by Harrison in the system of BENJAMIN for enhancing a lighting design through integration of data sources, such as architectural plans, including material choices, line of sight aspects, building orientation, impacts on natural light from nearby buildings and the like with light source specific information such as near field characterization data and the like to develop a multi-dimensional understanding of factors that impact a lighting design plan for a workspace. (See para 0413, Harrison)
The combination of BENJAMIN and Harrison does not teach wherein the site data includes a location of the site, an orientation of the site, an elevation of the site, a topography of the site, a location of an adjacent site, an orientation of the adjacent site, an elevation of the adjacent site, and a topography of the adjacent site.
However, Marceau further teaches wherein the site data includes a location of the site, (see para 83-a location for the subject architectural structure is determined. In some instances, the geographic location may be a specific latitude and longitude of the building site) an orientation of the site, an elevation of the site, a topography of the site. (see para 83-85- These can include, for example, external reflecting surfaces (e.g., lakes, oceans, other bodies of water, reflective buildings adjacent to the proposed site, and so on), external sources of shading (e.g., large building or structures, adjacent mountains or other geographic features, large trees, and so on), as well as internal reflecting surfaces or sources of shading (e.g., walls, ceilings, floors, and so on). see para 90- In other words, factors such as window and door placement, building orientation, building height, glazing, and other like design options can all contribute to the daylighting analysis and hence the spatial daylight autonomy of the structure.)
a location of an adjacent site, an orientation of the adjacent site, an elevation of the adjacent site, and a topography of the adjacent site. (See para 83-85 Likewise other structures adjacent to a particular building site may impact the daylighting analysis. For example, a building site surrounded by skyscrapers or other tall structures can be shaded by the structures, especially on the lower floors, and this can impact the daylighting analysis of an architectural structure on that site. Likewise, highly reflective surfaces on adjacent buildings (e.g. highly reflective glazing) can also impact the daylighting analysis of an architectural structure on that site. These can include, for example, external reflecting surfaces (e.g., lakes, oceans, other bodies of water, reflective buildings adjacent to the proposed site, and so on), external sources of shading (e.g., large building or structures, adjacent mountains or other geographic features, large trees, and so on), as well as internal reflecting surfaces or sources of shading (e.g., walls, ceilings, floors, and so on). In some embodiments, these external and/or internal contributors can be part of the sky model used to calculate the luminance of the sky and surrounding environment At operation 1604, the architectural structure analysis system parameterizes the architectural structure for the daylighting analysis. In some embodiments, the same set of parameter values that are used for the energy impact analysis can also be used for the daylighting analysis. In other words, factors such as window and door placement, building orientation, building height, glazing, and other like design options can all contribute to the daylighting analysis and hence the spatial daylight autonomy of the structure.)
Therefore, 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 method of generating and evaluating optimal architectural designs as disclosed by BENJAMIN and Harrison to include wherein the site data includes a location of the site, an orientation of the site, an elevation of the site, a topography of the site, a location of an adjacent site, an orientation of the adjacent site, an elevation of the adjacent site, and a topography of the adjacent site as taught by Marceau in the system of BENJAMIN and Harrison in order to compute the impact of daylighting on an architectural structure, simulations based on hourly local weather data in the designated geographic location of the architectural structure are performed to estimate the annual daylight availability at that location. This, in turn, is applied to the architectural structure to reduce the amount of electricity needed to provide sufficient worksurface lighting by fluorescent, incandescent, or other artificial light sources. (See para 0006-0007, Marceau)
Regarding claim 2, 16 and 20
Benjamin, Harrison and Marceau further teach the method of claim 1, the one of more transitory computer readable media of claim 15, the computer system of claim 19. Claims 2, 16, 20 are rejected over Claim 1, 15 and 19 (rejected based on Benjamin, Harrison and Marceau) in view of Benjamin. Benjamin further teaches determining a building type associated with the workplace, wherein selecting the one or more work condition elements is further based on the building type associated with the workplace. (See para 59-60-FIG. 11 illustrates how the team distributor of FIG. 4 distributes teams within a given design option, according to various embodiments of the present invention. As discussed above in conjunction with FIG. 2, criteria 204 reflects the working preferences of each potential occupant. Those working preferences may include desired distances to various amenities, centrality within the overarching workspace, exposure to traffic or other distractions, and so forth. Criteria 204 also indicates team membership for each potential occupant, as mentioned. In the context of this disclosure, a “team” simply refers to a group of potential occupants who should be assigned to the same neighborhood. In the context of a typical office, a team could refer to a department, such as “accounting” or “engineering,” as shown in FIG. 11, for example. Team distributor 440 is configured to analyze the geometry of design option 214 and then distribute different teams of potential occupants across each neighborhood 802 in a manner that optimally addresses the specific working preferences of each occupant. Team distributor 440 may also assign potential occupants to specific neighborhoods 802 based on overall team preferences aggregated across team members. Team distributor 440 may implement a “best fit” algorithm in order to generate a team distribution that matches teams to neighborhoods 802. Team distributor 440 may determine the degree to which any particular criteria 204 is met based on the set of metrics 222 computed by metric module 220)
Examiner note: Team distributor distributes one or more types of workers or personnel associated with the building type by selecting one or more work condition elements that reflect the working preference. Those working preferences may include desired noise level for a workstation, desired distances to various amenities, centrality within the overarching workspace, exposure to traffic or other distractions, and so forth which is the working condition element for each occupant. See fig 11 selecting one or more types of workers based on working preference of potential occupants on different building department (payroll, reception, design, engineering, executive, sales, IT)
Regarding claim 3 and 17
Benjamin, Harrison and Marceau further teach the method of claim 1, the one of more transitory computer readable media of claim 15. Claims 3 and 17 are rejected over Claim 1 and 15 (rejected based on Benjamin, Harrison and Marceau) in view of Benjamin. Benjamin further teaches determining one or more types of workers associated with the workplace, wherein selecting the one or more work condition elements is further based on the one or more types of worker associated with the workplace. (see para 59-60- FIG. 11 illustrates how the team distributor of FIG. 4 distributes teams within a given design option, according to various embodiments of the present invention. As discussed above in conjunction with FIG. 2, criteria 204 reflects the working preferences of each potential occupant. Those working preferences may include desired distances to various amenities, centrality within the overarching workspace, exposure to traffic or other distractions, and so forth. Criteria 204 also indicates team membership for each potential occupant, as mentioned. In the context of this disclosure, a “team” simply refers to a group of potential occupants who should be assigned to the same neighborhood. In the context of a typical office, a team could refer to a department, such as “accounting” or “engineering,” as shown in FIG. 11, for example. Team distributor 440 is configured to analyze the geometry of design option 214 and then distribute different teams of potential occupants across each neighborhood 802 in a manner that optimally addresses the specific working preferences of each occupant.)
Regarding claim 4 and 18
Benjamin, Harrison and Marceau further teach the method of claim 1, the one of more transitory computer readable media of claim 15. Claims 4 and 18 are rejected over Claim 1 and 15 (rejected based on Benjamin, Harrison and Marceau) in view of Benjamin. Benjamin further teaches determining one or more operations associated with the workplace, wherein selecting the one or more work condition elements is further based on the one or more operations associated with the workplace. (see para 59- FIG. 11 illustrates how the team distributor of FIG. 4 distributes teams within a given design option, according to various embodiments of the present invention. Criteria 204 reflects the working preferences of each potential occupant. Those working preferences may include desired distances to various amenities, centrality within the overarching workspace, exposure to traffic or other distractions, and so forth. see para 79- Distraction analyzer 1430 then computes a separate distraction metric 1434 for the corresponding assigned desk by determining the number of other desks and the number of high circulation nodes included in each of the long range and short range visual zones Distraction analyzer 1430 may weight the count of each distraction based on the particular visual zone where the distraction is found. Distraction metric 1434 thus indicates the distraction level associated with a particular desk. This metric can be aggregated over design option 214 as a whole to provide an overall distraction level for that design option, and then averaged over the number of desks to provide an average per-desk distraction level. See para 68-Adjacency grid 1412 includes, for any given potential occupant, a set of paths between a desk assigned to that potential occupant and any specific amenities selected by that occupant via the above-discussed survey and indicated within criteria 204. )
Regarding claim 5
Benjamin, Harrison and Marceau disclose the method of claim 1. Benjamin further discloses the method, wherein, for a given work condition element, evaluating the plurality of workspaces based on the work condition element includes: generating, for each workspace of the plurality of workspaces, a workspace value corresponding to the workspace, wherein generating the element value corresponding to the work condition element is further based on workspace values corresponding to the plurality of workspaces. ( see para 72-73- Based on daylight grid 1452 and criteria 204, daylight analyzer 1450 generates daylight metric 1450, as described in greater detail below in conjunction with FIG. 19. Workstyle analyzer 1460 is configured to analyze the design option 214 in conjunction with circulation grid 1422 and daylight grid 1452 to generate workstyle metric 1462. see para 82-Based on daylight grid 1900, and also based on circulation grid 1600 shown in FIG. 16, workstyle analyzer 1460 is configured to generate a separate workstyle metric 1464 for each potential occupant. Workstyle analyzer 1460 aggregates individual workstyle metrics across teams within neighborhoods 802)
Examiner note: Workstyle metrics of an individual within neighborhoods 802 is an element value. Daylight metric is the workspace value of the workspace.
Regarding claim 6
Benjamin, Harrison and Marceau disclose the method of claim 1. Benjamin further discloses the method, wherein, for a given work condition element, evaluating the plurality of workspaces based on the work condition element includes determining, for each workspace of the plurality of workspaces, whether the workspace satisfies the work condition element. (see para 81-As shown, exemplary daylight grid 1900 includes high flux nodes 1910, medium flux nodes 1920, and low flux nodes 1930. High flux nodes 1910 receive the most natural sunlight, averaged across each day of the year. Medium flux nodes 1920 receive a moderate amount of sunlight on average, and low flux nodes 1930 receive the least amount of natural sunlight during the year. Daylight analyzer 1450 generates daylight grid 1900 using a daylight simulator program. Daylight analyzer 1450 may then identify nodes that meet certain recommended criteria, and group these nodes into different categories, such as high flux, medium flux, and low flux, for example. Daylight analyzer 1450 then generates daylight metric 1454 to indicate the overall amount of natural light expected to flow through design option 214 per grid square. Daylight metric 1454 may also indicate the number of grid squares that meet a given daylight flux standard)
Regarding claim 7
Benjamin, Harrison and Marceau disclose the method of claim 1. Benjamin further discloses the method, wherein, for a second work condition element indicating views to outside of the building, evaluating the plurality of workspaces based on the second work condition element. (see para 71- Adjacency analyzer 1410 constructs paths 1510 and then computes a separate adjacency metric 1414 for each potential occupant based on the distances of those paths. The adjacency metric 1414 for any given potential occupant generally represents the distance the potential occupant must travel, on average, to reach any desired destination. See [0071] -View grid 1442 indicates the number of view to the outside from each desk within design option 214. See also [0080]- View analyzer 1440 constructs a different set of visual zones for each desk in design option 214 in order to determine the number of views to outward facing windows 1820 from each desk. View analyzer 1440 also determines the number of views to outward facing windows 1830 from high circulation nodes 1630. View analyzer 1440 then computes, for each potential occupant, the number of views the occupant has from the desk assigned to that occupant, as well as the number of views the occupant has from any high circulation nodes the occupant traverses. View analyzer 1440 then computes view metric 1444 to reflect these values. View analyzer 1440 aggregates the per-occupant view metrics across all occupants and floors of design option 214 to generate an overall view metric for design option 214. View analyzer 214 may then average this metric across all desks to create a per-desk view metric.)
BENJAMIN does not teach generating a plurality of view rays from the plurality of workspaces to a target destination.
However, Harrison further teaches generating a plurality of view rays from the plurality of workspaces to a target destination. (See para 203-The lighting space objects 220 may also include natural light sources, such as coming from windows. see para 265- Relevant properties may include lighting properties, such as the distribution of light on the lighting space objects 220 (such as the distribution of light on tables, desks, or workspaces). see fig 43 and para 342-ray traces 4304, reflections 4306, and interactions among ray traces and reflections 4308 for light being transmitted from a light source 4301 in an environment including features such as a desk 4310, wall 4312 and the like. See para 290- In embodiments, the platform may store a space utilization data structure that indicates, over time, how people use the space of the lighting installation, such as indicating what hallways are more trafficked, and the like. This may inform understanding of a space, such as indicating what is an entry, what is a passage, what is a workspace, and the like, which may be used to suggest changes or updates to a lighting design)
Therefore, 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 method of generating and evaluating optimal architectural designs as disclosed by BENJAMIN to include generating a plurality of view rays from the plurality of workspaces to a target destination as taught by Harrison in the system of BENJAMIN for enhancing a lighting design through integration of data sources, such as architectural plans, including material choices, line of sight aspects, building orientation, impacts on natural light from nearby buildings and the like with light source specific information such as near field characterization data and the like to develop a multi-dimensional understanding of factors that impact a lighting design plan for a workspace. (See para 0413, Harrison)
Regarding claim 8
Benjamin, Harrison and Marceau disclose the method of claim 1 and 7. Benjamin further discloses the method, wherein generating a second element value corresponding to the second work condition element is based on the subset of view rays. ((See para 81-82 FIG. 19 is a more detailed illustration of the daylight grid of FIG. 14, according to various embodiments of the present invention. As shown, exemplary daylight grid 1900 includes high flux nodes 1910, medium flux nodes 1920, and low flux nodes 1930. High flux nodes 1910 receive the most natural sunlight, averaged across each day of the year. Medium flux nodes 1920 receive a moderate amount of sunlight on average, and low flux nodes 1930 receive the least amount of natural sunlight during the year. Daylight analyzer 1450 generates daylight grid 1900 using a daylight simulator program. Daylight analyzer 1450 may then identify nodes that meet certain recommended criteria, and group these nodes into different categories, such as high flux, medium flux, and low flux, for example. Daylight analyzer 1450 then generates daylight metric 1454 to indicate the overall amount of natural light expected to flow through design option 214 per grid square. Daylight metric 1454 may also indicate the number of grid squares that meet a given daylight flux standard. Based on daylight grid 1900, and also based on circulation grid 1600 shown in FIG. 16, workstyle analyzer 1460 is configured to generate a separate workstyle metric 1464 for each potential occupant. A given workstyle metric 1464 generated for any particular occupant indicates the degree to which the desk assigned to that occupant provides (i) a preferred amount of natural lighting. See para 86-87 - Metric module 220 implements the method 2000 iteratively across all design options 214 to generate a different set of metrics 222 for each such design option. Metric module 220 may implement each step of the method 2000 in parallel for improved computational throughput. Metric module 220 may also combine the metrics for any given design option 214 into a single metric indicating how closely the design option 214 meets criteria 204)
BENJAMIN does not teach identifying a subset of view rays of the plurality of view rays, wherein each view ray of the subset of view rays is unobstructed.
However, Harrison further teaches identifying a subset of view rays of the plurality of view rays, wherein each view ray of the subset of view rays is unobstructed. (see para 204- In embodiments, the light intensity may be calculated as a set of ray-traces from each light source to the intersecting element, and the light transparency, absorption, and reflection characteristics of each the intersecting object may be accounted for, such as to model intensity and color of each ray (including transmitted and reflected rays) in the overall 3D rendering environment. See para 211- In such a situation, the LEDs on the end will be completely obstructed but the LEDs toward the middle will be unobstructed. See para 333-The modeled light emission set of ray-traces may represent light that travels from a light source disposed relative to the three-dimensional space and that travels through the three-dimensional space to an element in the three-dimensional space, such as a wall and the like. The modeling may further include reflections of the light off elements in the space. The reflections may be modeled based on a set of ray-traces and at least one reflection characteristic of the element in the three-dimensional space. In this way, if the surface is rough or matte, the reflection characteristic will result in a different effect of the light than would a shiny, smooth surface. The modeled ray-trace data (emissions and reflections) may be converted and/or captured as light volume data. Any data in the volume that may be missing may be interpolated based on, for example, nearby light ray-trace data values and/or nearby converted volume data values. The modeled data may then be processed to determine interactions among the ray-traces and reflections in the three-dimensional space. The interpolated data may be added to the volume data, the ray-tracing data, and the like so that the rendering facility may render the composite volume data, interpolated data, and interactions among the ray traces in the three-dimensional space. see para 203-The lighting space objects 220 may also include natural light sources, such as coming from windows. see para 265- Relevant properties may include lighting properties, such as the distribution of light on the lighting space objects 220 (such as the distribution of light on tables, desks, or workspaces). see fig 43 and para 342-ray traces 4304, reflections 4306, and interactions among ray traces and reflections 4308 for light being transmitted from a light source 4301 in an environment including features such as a desk 4310, wall 4312 and the like)
Therefore, 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 method of generating and evaluating optimal architectural designs as disclosed by BENJAMIN to include identifying a subset of view rays of the plurality of view rays, wherein each view ray of the subset of view rays is unobstructed as taught by Harrison in the system of BENJAMIN for enhancing a lighting design through integration of data sources, such as architectural plans, including material choices, line of sight aspects, building orientation, impacts on natural light from nearby buildings and the like with light source specific information such as near field characterization data and the like to develop a multi-dimensional understanding of factors that impact a lighting design plan for a workspace. (See para 0413, Harrison)
Regarding claim 10
Benjamin, Harrison and Marceau disclose the method of claim 1. Benjamin further discloses the method, wherein generating the particular element value corresponding to the particular work condition element is further based on the subset of rays. (See para 81-82 FIG. 19 is a more detailed illustration of the daylight grid of FIG. 14, according to various embodiments of the present invention. As shown, exemplary daylight grid 1900 includes high flux nodes 1910, medium flux nodes 1920, and low flux nodes 1930. High flux nodes 1910 receive the most natural sunlight, averaged across each day of the year. Medium flux nodes 1920 receive a moderate amount of sunlight on average, and low flux nodes 1930 receive the least amount of natural sunlight during the year. Daylight analyzer 1450 generates daylight grid 1900 using a daylight simulator program. Daylight analyzer 1450 may then identify nodes that meet certain recommended criteria, and group these nodes into different categories, such as high flux, medium flux, and low flux, for example. Daylight analyzer 1450 then generates daylight metric 1454 to indicate the overall amount of natural light expected to flow through design option 214 per grid square. Daylight metric 1454 may also indicate the number of grid squares that meet a given daylight flux standard. Based on daylight grid 1900, and also based on circulation grid 1600 shown in FIG. 16, workstyle analyzer 1460 is configured to generate a separate workstyle metric 1464 for each potential occupant. A given workstyle metric 1464 generated for any particular occupant indicates the degree to which the desk assigned to that occupant provides (i) a preferred amount of natural lighting See para 86-87 - Metric module 220 implements the method 2000 iteratively across all design options 214 to generate a different set of metrics 222 for each such design option. Metric module 220 may implement each step of the method 2000 in parallel for improved computational throughput. Metric module 220 may also combine the metrics for any given design option 214 into a single metric indicating how closely the design option 214 meets criteria 204))
BENJAMIN does not teach identifying a subset of rays of the plurality of rays, wherein each ray of the subset of rays is unobstructed.
However, Harrison further teaches identifying a subset of view rays of the plurality of rays, wherein each ray of the subset of rays is unobstructed. (See para 203-In embodiments, the light intensity may be calculated as a set of ray-traces from each light source to the intersecting element, and the light transparency, absorption, and reflection characteristics of each the intersecting object may be accounted for, such as to model intensity and color of each ray (including transmitted and reflected rays) in the overall 3D rendering environment. See para 211- In such a situation, the LEDs on the end will be completely obstructed but the LEDs toward the middle will be unobstructed. See para 333-The modeled light emission set of ray-traces may represent light that travels from a light source disposed relative to the three-dimensional space and that travels through the three-dimensional space to an element in the three-dimensional space, such as a wall and the like. The modeling may further include reflections of the light off elements in the space. The reflections may be modeled based on a set of ray-traces and at least one reflection characteristic of the element in the three-dimensional space. In this way, if the surface is rough or matte, the reflection characteristic will result in a different effect of the light than would a shiny, smooth surface. The modeled ray-trace data (emissions and reflections) may be converted and/or captured as light volume data. Any data in the volume that may be missing may be interpolated based on, for example, nearby light ray-trace data values and/or nearby converted volume data values. The modeled data may then be processed to determine interactions among the ray-traces and reflections in the three-dimensional space. The interpolated data may be added to the volume data, the ray-tracing data, and the like so that the rendering facility may render the composite volume data, interpolated data, and interactions among the ray traces in the three-dimensional space.)
Therefore, 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 method of generating and evaluating optimal architectural designs as disclosed by BENJAMIN to include identifying a subset of view rays of the plurality of rays, wherein each ray of the subset of rays is unobstructed as taught by Harrison in the system of BENJAMIN for enhancing a lighting design through integration of data sources, such as architectural plans, including material choices, line of sight aspects, building orientation, impacts on natural light from nearby buildings and the like with light source specific information such as near field characterization data and the like to develop a multi-dimensional understanding of factors that impact a lighting design plan for a workspace. (See para 0413, Harrison)
Regarding claim 11
Benjamin, Harrison and Marceau disclose the method of claim 1. Benjamin further discloses the method, wherein evaluating the plurality of workspaces based on the work condition element includes generating a plurality of paths from the plurality of workspaces to a target destination. (See para 76- Adjacency analyzer 1410 constructs paths 1510 and then computes a separate adjacency metric 1414 for each potential occupant based on the distances of those paths. The adjacency metric 1414 for any given potential occupant generally represents the distance the potential occupant must travel, on average, to reach any desired destination.)
Regarding claim 12
Benjamin, Harrison and Marceau disclose the method of claim 1. Benjamin further discloses the method further comprising, calculating, for each path of the plurality of paths, a length of the path; (see para 75-76-Adjacency analyzer 1410 constructs a different set of paths 1510 for each potential occupant assigned to a desk based on criteria 204. For example, adjacency analyzer 1410 constructs paths 1510(0) and 1510(1) coupling assigned desk 1520(0) to amenity clusters 1000(4) and 1000(3), respectively, because the potential occupant assigned to those desks indicated a preferential proximity to amenity clusters 1000(4) and 1000(3). Adjacency analyzer 1410 constructs paths 1510 and then computes a separate adjacency metric 1414 for each potential occupant based on the distances of those paths)
and identifying a subset of paths of the plurality of paths, wherein the length of each path in the subset of paths is within a threshold value, (see para 68-Adjacency grid 1412 includes, for any given potential occupant, a set of paths between a desk assigned to that potential occupant and any specific amenities selected by that occupant via the above-discussed survey and indicated within criteria 204. See para 86-87 -As shown in FIG. 20B, at step 2014, adjacency analyzer 1410 generates adjacency metric 1414 based on adjacency grid 1412 and criteria 204. Adjacency metric 1414 represents the average proximity to locations of interest for each potential occupant. Metric module 220 implements the method 2000 iteratively across all design options 214 to generate a different set of metrics 222 for each such design option. Metric module 220 may implement each step of the method 2000 in parallel for improved computational throughput. Metric module 220 may also combine the metrics for any given design option 214 into a single metric indicating how closely the design option 214 meets criteria 204.)
wherein generating the element value corresponding to the work condition element is further based on the subset of paths. (see para 76- Adjacency analyzer 1410 constructs paths 1510 and then computes a separate adjacency metric 1414 for each potential occupant based on the distances of those paths.)
Regarding claim 14
Benjamin, Harrison and Marceau disclose the method of claim 1. Benjamin further discloses the method, further comprising normalizing the overall work condition value, based on the one or more work condition elements, to generate a normalized overall work condition value. (see para 82- Workstyle analyzer 1460 aggregates individual workstyle metrics across teams within neighborhoods 802 and across floors in design option 214 to generate an overall workstyle metric 1464. Workstyle analyzer 1460 may also average this global metric based on the number of desks assigned in design option 214.
Regarding claim 21
Benjamin, Harrison and Marceau disclose the method of claim 1. Benjamin does not teach wherein the direction of the target source is further determined based on at least one of an orientation of the building or a location of the building.
However, Harrison further teaches wherein the direction of the target source is further determined based on at least one of an orientation of the building or a location of the building. (See para 203-The lighting space objects 220 may also include natural light sources, such as coming from windows. see para 302- IES files may include a two-dimensional characterization I (θ, φ), which may represent the luminous flux in a given direction defined by θ and φ. In embodiments, this data may be gathered using a goniophotometer to measure light at different angles and at large distances relative to the size of a lighting fixture such as more than 10× the size of a lighting fixture object 230. The approach may include rotating a lighting fixture object 230 to measure the luminance of a lighting fixture object 230 at all angles. see para 404 In embodiments, design of lighting in an environment may be configured to emulate natural light effects, such as sunrise, sunset, and the like. Additionally, lighting design may emulate other natural light effects, such as sunlight impacting a window or skylight and the like. Control of lights that coordinate with a time of day (e.g., the path of the sun through the sky), a weather forecast (e.g., clouds, full sunshine, partial sunshine, and the like), and the like may further enhance emulating a natural effect of exterior sunlight. See para 413- In embodiments, lighting design may further be enhanced through integration of data sources, such as architectural plans, including material choices, line of sight aspects, building orientation, impacts on natural light from nearby buildings and the like may be combined with light source specific information such lighting as near field characterization data and the like to develop a multi-dimensional understanding of factors that impact a lighting design plan for a space.)
Therefore, 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 method of generating and evaluating optimal architectural designs as disclosed by BENJAMIN to include wherein the direction of the target source is further determined based on at least one of an orientation of the building or a location of the building as taught by Harrison in the system of BENJAMIN for enhancing a lighting design through integration of data sources, such as architectural plans, including material choices, line of sight aspects, building orientation, impacts on natural light from nearby buildings and the like with light source specific information such as near field characterization data and the like to develop a multi-dimensional understanding of factors that impact a lighting design plan for a workspace. (See para 0413, Harrison)
Regarding claim 24
Benjamin, Harrison and Marceau disclose the method of claim 1. Benjamin does not teach wherein the direction of the target source is further determined based on location data or landmark information from a map location database.
However, Harrison further teaches wherein the direction of the target source is further determined based on location data or landmark information from a map location database. (See para 184- embodiments, one of the elements of the platform 100 that may interact with design, marketplace and implementation is an understanding of the lighting design environments 238 that products are being deployed in, allowing the user of the platform 100 to build a database of types of lighting design environments 238, regions of the country and the like, such as regarding how people are deploying and using light in predetermined regions or environments. See para 283- The lighting objects 226 and their locations may be associated with a map, such as the map of the lighting space in the design environment. The map may be provided from the lighting design environment 238 to one or more other location or navigation systems, such that locations of lights may be used as known locations or points of interest within a space. See also para 436)
Therefore, 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 method of generating and evaluating optimal architectural designs as disclosed by BENJAMIN to include wherein the direction of the target source is further determined based on location data or landmark information from a map location database as taught by Harrison in the system of BENJAMIN for enhancing a lighting design through integration of data sources, such as architectural plans, including material choices, line of sight aspects, building orientation, impacts on natural light from nearby buildings and the like with light source specific information such as near field characterization data and the like to develop a multi-dimensional understanding of factors that impact a lighting design plan for a workspace. (See para 0413, Harrison)
Regarding claim 27
Benjamin, Harrison and Marceau disclose the method of claim 1. The combination of Benjamin and Harrison does not teach wherein the site data further includes one or more locations of fixed equipment within the site.
However, Marceau further teaches wherein the site data further includes wherein the site data further includes one or more locations of fixed equipment within the site. (See para 90-92- Referring now to FIG. 16, at operation 1602, the architectural structure location is determined. As discussed above, this can be site-specific (e.g. latitude and longitude) or regionally defined (e.g. within a city, county, or other predetermined region of relative luminance uniformity). At operation 1606 sensor locations are defined for the workspace within the building. Depending on the desired resolution, any of a number of “sensors” can be defined and identified for the workspace is within the building. For instance, virtual sensors can be placed (e.g. defined in the simulation model) in the structure in locations of the building subject to receiving natural daylight from windows, skylights, openings, etc. The sensor locations can be at the floor level, at a predetermined workspace height (e.g. at a standard desktop height) or other heights on one or more floors of the architectural structure. At operation 1608 the skylight luminance patterns calculated from the sky model are applied and the sensors are used to determine the intensity of natural daylight impinging on the sensors at the identified discrete time intervals. For example, ray tracing or other like analysis can be used to determine the intensity (e.g., measured in Lux) of light from the various skylight sources (e.g. direct sunlight, indirect light from the sky, reflected light, and so on). The intensity from various sources can be combined to give a total value for each sensor. Because the sky luminance changes throughout the day, and on a larger scale throughout the year, the intensity values for each sensor can be computed at discrete intervals, and combined as appropriate to determine overall performance or the spatial daylight autonomy of the structure.)
Therefore, 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 method of generating and evaluating optimal architectural designs as disclosed by BENJAMIN and Harrison to include wherein the site data further includes wherein the site data further includes one or more locations of fixed equipment within the site as taught by Marceau in the system of BENJAMIN and Harrison in order to compute the impact of daylighting on an architectural structure, simulations based on hourly local weather data in the designated geographic location of the architectural structure are performed to estimate the annual daylight availability at that location. This, in turn, is applied to the architectural structure to reduce the amount of electricity needed to provide sufficient worksurface lighting by fluorescent, incandescent, or other artificial light sources. (See para 0006-0007, Marceau)
10. Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over BENJAMIN et al. (PUB NO: US 20180137214 A1) in view of Harrison et al. (PUB NO: US 20200060007 A1) and further in view of Marceau et al. (PUB NO: US20150234945A1) and still further in view of Soltani, A. R., and T. Fernando. "A fuzzy based multi-objective path planning of construction sites." Automation in construction 13.6 (2004): 717-734.
Regarding claim 13
Benjamin, Harrison and Marceau disclose the method of claim 1 and 11. Benjamin further teaches the method, further comprising identifying a subset of paths of the plurality of paths, wherein generating the element value corresponding to the work condition element is further based on the subset of paths. (see para 68-Adjacency grid 1412 includes, for any given potential occupant, a set of paths between a desk assigned to that potential occupant and any specific amenities selected by that occupant via the above-discussed survey and indicated within criteria 204. See para 86-87 -As shown in FIG. 20B, at step 2014, adjacency analyzer 1410 generates adjacency metric 1414 based on adjacency grid 1412 and criteria 204. Adjacency metric 1414 represents the average proximity to locations of interest for each potential occupant. Metric module 220 implements the method 2000 iteratively across all design options 214 to generate a different set of metrics 222 for each such design option. Metric module 220 may implement each step of the method 2000 in parallel for improved computational throughput. Metric module 220 may also combine the metrics for any given design option 214 into a single metric indicating how closely the design option 214 meets criteria 204. see para 76- Adjacency analyzer 1410 constructs paths 1510 and then computes a separate adjacency metric 1414 for each potential occupant based on the distances of those paths.)
However, the combination of BENJAMIN, Harrison and Marceau does not teach calculating, for each path of the plurality of paths, a travel time associated with the path and wherein the travel time associated with each path in the subset of paths is within a threshold value.
In the related field of invention, Soltani teaches calculating, for each path of the plurality of paths, a travel time associated with the path; (see page 728 and 732-The process times of manually transporting timbers from the access point, Di, to the storage location, SA1, for the two workplace layouts shown in Fig. 15a and b, are measured and compared. Table 4 shows the results obtained and indicates the amount of time that can be saved is nearly 3 h when the distance is only reduced by less than 3 m. Clearly, this process time evaluation technique can be applied to the other processes on the workplace and a quantitative measure of timesaving obtained.)
wherein the travel time associated with each path in the subset of paths is within a threshold value. (see page 725-The designers aim is to operate within a threshold that maximizes safety level that also allows for a compromise by which cost issues can be fulfilled. see page 732-In general, this multi-objective site path planning approach is capable of producing strategic paths for potentially complex site layouts, as well as providing the flexibility of tuning various path planning criteria, in order to offer useful and complementary option to manually defined site path)
Therefore, 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 method of generating and evaluating optimal architectural designs as disclosed by BENJAMIN to include calculating, for each path of the plurality of paths, a travel time associated with the path and wherein the travel time associated with each path in the subset of paths is within a threshold value as taught by Soltani in the system of BENJAMIN, Marceau and Harrison for supporting path planning analysis of construction sites based on multi-objective evaluation of transport cost, safety, and visibility. Th use of fuzzy-based multi-objective optimization approach in making a more informed strategic decisions regarding the movement path of people and vehicles on construction sites, and detailed decisions regarding travel distance and operational paths on workplaces, enabling site planners to examine paths scenarios that are subjected to a high degree of uncertainty and subjectivity. (See Abstract, Soltani)
11. Claims 25 and 28 are rejected under 35 U.S.C. 103 as being unpatentable over BENJAMIN et al. (PUB NO: US 20180137214 A1) in view of Harrison et al. (PUB NO: US 20200060007 A1) and further in view of Marceau et al. (PUB NO: US20150234945A1) and still further in view of Savioja, Lauri, and U. Peter Svensson. ("Overview of geometrical room acoustic modeling techniques." The Journal of the Acoustical Society of America 138.2 (2015): 708-730.)
Regarding claim 25
Benjamin, Harrison and Marceau disclose the method of claim 1. Benjamin further teaches the method, further comprising generating the particular element value corresponding to the particular work condition element based on daylight metric (See para 78-82 The circulation score 1424 for a given floor is computed by comparing the different paths 1510 across design area 510, as defined in adjacency grid 1500, to the number and type of the different circulation nodes traversed by those paths. For example, a particular path 1510 through a high circulation node 1630 would contribute to a higher circulation score, whereas another path 1510 through a low circulation node 1630 might contribute to a lower circulation score. FIG. 19 is a more detailed illustration of the daylight grid of FIG. 14, according to various embodiments of the present invention. As shown, exemplary daylight grid 1900 includes high flux nodes 1910, medium flux nodes 1920, and low flux nodes 1930. High flux nodes 1910 receive the most natural sunlight, averaged across each day of the year. Medium flux nodes 1920 receive a moderate amount of sunlight on average, and low flux nodes 1930 receive the least amount of natural sunlight during the year. Daylight analyzer 1450 generates daylight grid 1900 using a daylight simulator program. Daylight analyzer 1450 may then identify nodes that meet certain recommended criteria, and group these nodes into different categories, such as high flux, medium flux, and low flux, for example. Daylight analyzer 1450 then generates daylight metric 1454 to indicate the overall amount of natural light expected to flow through design option 214 per grid square. Daylight metric 1454 may also indicate the number of grid squares that meet a given daylight flux standard. Based on daylight grid 1900, and also based on circulation grid 1600 shown in FIG. 16, workstyle analyzer 1460 is configured to generate a separate workstyle metric 1464 for each potential occupant. A given workstyle metric 1464 generated for any particular occupant indicates the degree to which the desk assigned to that occupant provides (i) a preferred amount of natural lighting See para 86-87 - Metric module 220 implements the method 2000 iteratively across all design options 214 to generate a different set of metrics 222 for each such design option. Metric module 220 may implement each step of the method 2000 in parallel for improved computational throughput. Metric module 220 may also combine the metrics for any given design option 214 into a single metric indicating how closely the design option 214 meets criteria 204))
BENJAMIN does not teach identifying a subset of rays of the plurality of rays, wherein each ray of the subset of rays is unobstructed and further based on a first total number of rays in the subset of rays compared to a second total number of rays in the plurality of rays.
However, Harrison further teaches identifying a subset of rays of the plurality of rays, wherein each ray of the subset of rays is unobstructed. (See para 203-In embodiments, the light intensity may be calculated as a set of ray-traces from each light source to the intersecting element, and the light transparency, absorption, and reflection characteristics of each the intersecting object may be accounted for, such as to model intensity and color of each ray (including transmitted and reflected rays) in the overall 3D rendering environment. See para 211- In such a situation, the LEDs on the end will be completely obstructed but the LEDs toward the middle will be unobstructed. See para 333-The modeled light emission set of ray-traces may represent light that travels from a light source disposed relative to the three-dimensional space and that travels through the three-dimensional space to an element in the three-dimensional space, such as a wall and the like. The modeling may further include reflections of the light off elements in the space. The reflections may be modeled based on a set of ray-traces and at least one reflection characteristic of the element in the three-dimensional space. In this way, if the surface is rough or matte, the reflection characteristic will result in a different effect of the light than would a shiny, smooth surface. The modeled ray-trace data (emissions and reflections) may be converted and/or captured as light volume data. Any data in the volume that may be missing may be interpolated based on, for example, nearby light ray-trace data values and/or nearby converted volume data values. The modeled data may then be processed to determine interactions among the ray-traces and reflections in the three-dimensional space. The interpolated data may be added to the volume data, the ray-tracing data, and the like so that the rendering facility may render the composite volume data, interpolated data, and interactions among the ray traces in the three-dimensional space. see para 203-The lighting space objects 220 may also include natural light sources, such as coming from windows. see para 265- Relevant properties may include lighting properties, such as the distribution of light on the lighting space objects 220 (such as the distribution of light on tables, desks, or workspaces). see fig 43 and para 342-ray traces 4304, reflections 4306, and interactions among ray traces and reflections 4308 for light being transmitted from a light source 4301 in an environment including features such as a desk 4310, wall 4312 and the like)
Therefore, 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 method of generating and evaluating optimal architectural designs as disclosed by BENJAMIN to include identifying a subset of rays of the plurality of rays, wherein each ray of the subset of rays is unobstructed as taught by Harrison in the system of BENJAMIN for enhancing a lighting design through integration of data sources, such as architectural plans, including material choices, line of sight aspects, building orientation, impacts on natural light from nearby buildings and the like with light source specific information such as near field characterization data and the like to develop a multi-dimensional understanding of factors that impact a lighting design plan for a workspace. (See para 0413, Harrison)
The combination of BENJAMIN, Harrison and Marceau does no teach generating the particular element value further based on a first total number of rays in the subset of rays compared to a second total number of rays in the plurality of rays.
In the related field of invention, Savioja teaches generating the particular element value further based on a first total number of rays in the subset of rays compared to a second total number of rays in the plurality of rays. (See page 712-The scattering coefficient is the parameter that is often used to describe the roughness of a surface. The coefficient is defined as the ratio of nonspecularly reflected energy and total reflected energy, and it can be used to simply divide the reflected energy into two components, specular and diffuse, whereby a value of 1 corresponds to a fully diffuse reflection in which there is no specular reflection component. It can be noted that a value of 1 tells nothing of the distribution of this diffusely reflected sound. In contrast, a scattering coefficient with a value of 0 corresponds to an ideally specular reflection. See page 727-For example, the use of graphics processing units (GPUs) for ray tracing enables much higher ray counts and higher reflection orders compared to what is customary on current central processing units (CPUs).)
Therefore, 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 method of generating and evaluating optimal architectural designs as disclosed by BENJAMIN to include generating the particular element value further based on a first total number of rays in the subset of rays compared to a second total number of rays in the plurality of rays as taught by Savioja in the system of BENJAMIN, Marceau and Harrison in order to employ ray tracing or ray-based propagation in numerous other fields such as optics and underwater acoustics. (see Background Section D) This is especially important in concert halls and other challenging spaces, such as theaters and studios, but it is also important in classrooms, railway stations, and other public venues and even in homes of the space design. (See Introduction, Savioja)
Regarding claim 28
Benjamin, Harrison and Marceau disclose the method of claim 1 and 25. Benjamin does not teach the method, further comprising identifying a subset of rays of the plurality of rays, wherein each ray of the subset of rays is unobstructed, wherein the particular element value corresponding to the particular work condition element is equal to the first total number of rays in the subset of rays divided by a second total number of rays in the plurality of rays.
However, Harrison further teaches identifying a subset of rays of the plurality of rays, wherein each ray of the subset of rays is unobstructed. (See para 203-In embodiments, the light intensity may be calculated as a set of ray-traces from each light source to the intersecting element, and the light transparency, absorption, and reflection characteristics of each the intersecting object may be accounted for, such as to model intensity and color of each ray (including transmitted and reflected rays) in the overall 3D rendering environment. See para 211- In such a situation, the LEDs on the end will be completely obstructed but the LEDs toward the middle will be unobstructed. See para 333-The modeled light emission set of ray-traces may represent light that travels from a light source disposed relative to the three-dimensional space and that travels through the three-dimensional space to an element in the three-dimensional space, such as a wall and the like. The modeling may further include reflections of the light off elements in the space. The reflections may be modeled based on a set of ray-traces and at least one reflection characteristic of the element in the three-dimensional space. In this way, if the surface is rough or matte, the reflection characteristic will result in a different effect of the light than would a shiny, smooth surface. The modeled ray-trace data (emissions and reflections) may be converted and/or captured as light volume data. Any data in the volume that may be missing may be interpolated based on, for example, nearby light ray-trace data values and/or nearby converted volume data values. The modeled data may then be processed to determine interactions among the ray-traces and reflections in the three-dimensional space. The interpolated data may be added to the volume data, the ray-tracing data, and the like so that the rendering facility may render the composite volume data, interpolated data, and interactions among the ray traces in the three-dimensional space. see para 203-The lighting space objects 220 may also include natural light sources, such as coming from windows. see para 265- Relevant properties may include lighting properties, such as the distribution of light on the lighting space objects 220 (such as the distribution of light on tables, desks, or workspaces). see fig 43 and para 342-ray traces 4304, reflections 4306, and interactions among ray traces and reflections 4308 for light being transmitted from a light source 4301 in an environment including features such as a desk 4310, wall 4312 and the like)
Therefore, 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 method of generating and evaluating optimal architectural designs as disclosed by BENJAMIN to include identifying a subset of rays of the plurality of rays, wherein each ray of the subset of rays is unobstructed as taught by Harrison in the system of BENJAMIN for enhancing a lighting design through integration of data sources, such as architectural plans, including material choices, line of sight aspects, building orientation, impacts on natural light from nearby buildings and the like with light source specific information such as near field characterization data and the like to develop a multi-dimensional understanding of factors that impact a lighting design plan for a workspace. (See para 0413, Harrison)
The combination of BENJAMIN, Harrison and Marceau does no teach wherein the particular element value corresponding to the particular work condition element is equal to the first total number of rays in the subset of rays divided by a second total number of rays in the plurality of rays.
In the related field of invention, Savioja teaches wherein the particular element value corresponding to the particular work condition element is equal to the first total number of rays in the subset of rays divided by a second total number of rays in the plurality of rays. (See page 712-The scattering coefficient is the parameter that is often used to describe the roughness of a surface. The coefficient is defined as the ratio of nonspecularly reflected energy and total reflected energy, and it can be used to simply divide the reflected energy into two components, specular and diffuse, whereby a value of 1 corresponds to a fully diffuse reflection in which there is no specular reflection component. It can be noted that a value of 1 tells nothing of the distribution of this diffusely reflected sound. In contrast, a scattering coefficient with a value of 0 corresponds to an ideally specular reflection. See page 727-For example, the use of graphics processing units (GPUs) for ray tracing enables much higher ray counts and higher reflection orders compared to what is customary on current central processing units (CPUs).)
Therefore, 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 method of generating and evaluating optimal architectural designs as disclosed by BENJAMIN to include wherein the particular element value corresponding to the particular work condition element is equal to the first total number of rays in the subset of rays divided by a second total number of rays in the plurality of rays as taught by Savioja in the system of BENJAMIN, Marceau and Harrison in order to employ ray tracing or ray-based propagation in numerous other fields such as optics and underwater acoustics.(see Background Section D) This is especially important in concert halls and other acoustically challenging spaces, such as theaters and studios, but it is also important in classrooms, railway stations, and other public venues and even in homes of the space design. (See Introduction, Savioja)
Relevant prior art
12. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Plewe US 20100198563 A1
Discussing a method for providing component-based architecture design generated from a plurality of pre-designed room components. For example, a need exists for facilitating the design of a home with similar costs as the tract housing system while offering considerable gains in customization.
Holm-Petersen et al. US 20100218131 A1
Discussing a method that includes generation and manipulation of a multi-dimensional visualization (e.g., top-down) of a physical layout of a warehouse or other structure where item placement and movement is tracked for optimum processing. The visualization provides a graphical user interface (GUI) for representing the virtual warehouse physical layout, aisles, racks on the aisles, bins in the racks, and products in the bins.
Conclusion
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.
13. All claims are rejected.
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/PURSOTTAM GIRI/Examiner, Art Unit 2186
/RENEE D CHAVEZ/Supervisory Patent Examiner, Art Unit 2186