NAWARI NAWARI O (US)
US20190347751A1 | 2019-11-14 |
CLAIMS What is claimed is: 1. A method comprising: performing, using at least one hardware processor, design model validation, wherein design model validation comprises entering land development permit application file information and checking the land development permit application file information against relevant land development codes, ordinances, and regulations; performing, using the at least one hardware processor, exchange model code checking using a plurality of exchange models; performing, using the at least one hardware processor, conformance checking, wherein the conformance checking comprises receiving a request from the exchange models and passing the land development permit application file information to design checking modules configured to check land development code, ordinance, and regulation provisions and one or more codes, ordinances, and regulations per local, state, national or international requirements; and performing, using at least one hardware processor, compliance reporting based on input provided from the design checking modules. 2. The method of claim 1, wherein the design checking modules are configured to check all land development code, ordinance, and regulatory provisions per local, state, national or international requirements. 3. The method of claim 1, further comprising transforming, by the hardware processor, a land development code, ordinance, and regulation into a computable record. 4. The method of claim 3, wherein the land development code, ordinance, and regulation defines a land use code, ordinance, and regulation. 5. The method of claim 4, wherein the land use code, ordinance, and regulation comprises a zoning rule. 6. The method of claim 3, wherein a semantic structure of the land development code, ordinance, and regulation is translated into object rules or parametric models and associated with the land development permit application file information being examined. 7. The method of claim 3, wherein the land development code, ordinance, regulation is transformed using a Transformation Logic Algorithm (TLA), neural Natural Language Processing (NLP) techniques, or artificial intelligence. 8. The method of claim 1, wherein the compliance reporting comprises superimposing a CAD drawing or BIM model or PDF file of a proposed development of a piece of property on a GIS map of a geographic area having applicable zoning conditions illustrated. 9. The method of claim 1, further comprising graphically displaying, by the hardware processor, a semi-transparent interface embedded with one or more buttons for initiating an action of code conformance checking. 10. A system comprising: at least one hardware processor; and one or more software modules that are configured to, when executed by the at least one hardware processor: perform design model validation, wherein design model validation comprises entering land development permit application file information and checking the land development permit application file information against relevant codes and regulations, using a taxonomy or neural Natural Language Processing (NLP) or artificial intelligence; perform exchange model code checking, wherein exchange model code checking comprises using a plurality of exchange models; perform code, ordinance, and regulation conformance checking, wherein the code, ordinance, and regulation conformance checking comprises receiving a request from the exchange models and passing the land development permit application file information to design checking modules configured to check land development code, ordinance, and regulation provisions and one or more regulations per local, state, national or international requirements; and perform compliance reporting based on input provided from the design checking modules. 11. The system of claim 10, wherein the one or more software modules are configured to, when executed by the at least one hardware processor, to transform a land development code, ordinance, and regulation into a computable record. 12. The system of claim 11, wherein the land development code, ordinance, and regulation defines a drainage rule for the land development code, ordinance, and regulation. 13. The system of claim 11, wherein the land development code, ordinance, and regulation defines a sanitation rule for the land development code, ordinance, and regulation. 14. The system of claim 11, wherein a semantic structure of the land development code, ordinance, and regulation is translated into object rules or parametric models and associated with the land development permit application file information being examined. 15. The system of claim 11, wherein the land development code, ordinance, and regulation is transformed using a Transformation Logic Algorithm (TLA), the neural Natural Language Processing (NLP) techniques, or the artificial intelligence. 16. The system of claim 10, wherein the design checking modules are configured to check land development code, ordinance, and regulatory provisions per local, state, national or international requirements. 17. The system of claim 10, wherein the compliance reporting comprises superimposing a CAD drawing of a proposed development of a piece of property on a GIS map of a geographic area having applicable zoning conditions illustrated. 18. A non-transitory computer-readable medium having instructions stored therein, wherein the instructions, when executed by a processor, cause the processor to: perform design model validation, wherein design model validation comprises entering land development permit application file information and checking the land development permit application file information against relevant codes, ordinances, and regulations, with or without a taxonomy; perform exchange model code checking using a plurality of exchange models; perform conformance checking, wherein the conformance checking comprises receiving a request from the exchange models and passing the land development permit application file information to design checking modules configured to check land development code, ordinance, and regulatory provisions and any regulations per local, state, national or international requirements; and perform compliance reporting based on input provided from the design checking modules. 19. The non-transitory computer-readable medium of claim 18, wherein the instructions, when executed by a processor, cause the processor to transform a land development code, ordinance, and regulation into a computable record. 20. The non-transitory computer-readable medium of claim 19, wherein the compliance reporting comprises superimposing a CAD drawing or BIM model or PDF file of a proposed development of a piece of property on a GIS map of a geographic area having applicable zoning conditions illustrated. |
Prov (PE) ∈ Conditional; ∀ x (PE(x) → Permitted (x, approve design)) ∀ x (┐ PE(x) ∀ x┐Permitted (x, approve design)) . [0066] Additional illustrative TLA examples (Nawari, 2012) are shown below: (i) An object is a member of a category: 4x8 S4S ∈ Wood Beams; (ii) A category is a subclass of another category: Wood Beams ^ Beams (iii) All members of a category have some properties: x ∈ Wood Beams → Rectangular (x). [0067] Members of a category can be recognized by some properties: DouglasFir(x) ^ Square(x) ^ Side(x) = 9.25” ^ x ∈ Beams → x ∈ Wood Beams. [0068] The syntax used in the above statements has similar definitions as in first- order logic calculus. The definitions of the syntax used are summarized in Table 1 (Syntax of Transformation Logic Algorithm (TLA)) (below). [0069] This TLA algorithm can be illustrated further by considering an exemplary and non-limiting Regulation Code – Residential 2020 (FBC 2020). FIG.5 depicts parts of section 304 from the FBC 2020-Residential. [0070] The provision shown in FIG. 5 can be transformed into computable representation using the TRA as follows: Let REG i = “Section R304”; Where i varies from 1 to n number of code provisions. Then we have (1) where the subscript i stands for the counts of the code sections being processed and varies from 1 to n sections; P i designates that this is a provisory clause, and describes the minimum room area (Yi) which is given by Xi that expresses the various Rules describing Yi: X i = {R 1 , R 2 , …R m }, (2) where R 1 , R 2 , …R m are the rules defining X i ; Let Z 1j = {z 11 …z 1q }; (3) z = IfcSpace; z11 = “R304.1”; and z 12 ::= Floor area >=70 ft 2 (6.5m 2 ); (4) R 2 : ∀ z (REG i (z) o MinimumArea(z, Z 1j ) Λ┐ SpaceName(z, KITCHEN;) (5) Z 2j = {z 21 …z 2q }; (6) where z 21 = “R304.2”; and z 22 ::= least horizontal dimension of any habitable room >= 7 ft (2.134 m); R 3: ∀ z (REG i (z) → MinimumDimension(z, Z 2j ) Λ┐ SpaceName(z, KITCHEN);(7) Z 3j = {z 31 …z 3q }; (8) where Z 31 = “R304.3”; z 32 ::= Ceiling height > 5 ft for sloped ceiling; and z 33 ::= Ceiling height > 7 ft for furred ceiling; R 4: ∀ z (REG i (z) o CeilingHeightLimitation(z, Z 3j ); and (9) X i = {R 1 Λ R 2 Λ R 3 Λ R 4 }. (10) [0071] Equation 10 then represents the knowledge transformation process to generate a computable model for the code specifications expressed in FBC 2020- Residential, section R304. Thus, all of the rules and regulations can be similarly translated into equations using the TLA. Again, this can be done on platform 110 or the equations can be uploaded thereto, depending on the embodiment. [0072] Conditional clauses, such as the ones above, can be transformed directly from the textual format into set of rules. Examples of these are very common and typical features include rules with specific values. An illustrative and non-limiting regulatory example is provided by provision (3.2.1) for computing lateral pressure in the ASCE 7-10 Standard for minimum design loads for buildings and other structure. Contents clauses cannot be translated into a TRUE or FALSE statement. Instead of advising, these clauses are usually used for definitions, such as the definition of firewall, fire rate, smoke evacuation, high-rise building, etc. Ambiguous clauses are the subjective provisions. They normally include words such as: approximately, about, relatively, close to, far from, maybe, etc. An example is the footnote of the design lateral soil pressure for the clause given in provision (3.2.1), ASCE 7-10: “For relatively rigid walls, as when braced by floors, the design lateral soil load shall be increased for sand and gravel type soils to 60 psf (9.43 kN/m2) per foot (meter) of depth. Basement walls extending not more than 8 ft (2.44 m) below grade and supporting light floor systems are not considered as being relatively rigid walls.” Dependent clauses indicate that one clause is dependent upon one or more other clauses. They represent deep hierarchies and massive cross-referencing among provisions in code regulations. This means some provisions are only suitable for a particular condition when other clauses are met. These are often difficult to convert into sets of rules and may require manual verification for compliance. [0073] Referring back to FIG.3, the higher-Order Level II phase of the exemplary GAF centers on the development of IDM (Information Delivery Manual) and MVD (Model View Definitions) that allows the land development permit application file data to be compared to the relevant codes and regulations. The development of IDM for land development code specifications starts with a description of data exchange functional requirements and workflow situations for interactions between land development permit application file data (e.g., BIM model data) and the conditions specified in land development codes. This is demonstrated in the process map of FIG. 6. An exemplary system uses neural NLP techniques and/or deep neural network- style machine learning/ Artificial Intelligence. [0074] The process map is generated using a standard Business Process Modeling Notation (BPMN) as part of the IDM specifications (Nawari and Kuenstle, 2018) to define the MVDs and how to exchange data related to the MVDs. In the process map depicted in FIG. 6, the following tasks and processes are identified: design model validation 610, exchange code checking 620, code conformance checking 630, verification reporting 640, and results reporting 650. The main tasks can have various sub-processes that can also be defined using process maps and IDMs. [0075] For example, the design model validation 610 task comprises entering BIM model information in step 612, which is then checked against the relevant codes and regulations, using the taxonomy described above, for conformance in step 614. If the BIM model is validated in step 614, then such can be reported, in task 650. But if the code is not initially validated, then the process can move to the exchange code checking task 620. Task 620 can comprise several code checking models. The IDM employs notation for information exchanges between activities called Exchange Models (EM). Each exchange model is distinctively recognized across all use cases. The EMs can include, as non-limiting examples, CODE_Z_EM: Zoning Code Regulations case exchange model(s) (621); CODE_L_EM: Landscaping Code Regulations case exchange model(s) (622); CODE_D_EM: Drainage Code Regulations case exchange model(s) (623); CODE_S_EM: Sanitation Code Regulations case exchange models (624); CODE_T_EM: Transportation Code Regulations case exchange model(s) (625), etc. [0076] The Code Conformance Checking task 630 can involve receiving a request from the exchange models (EMs) in step 631 and then passing the BIM or CAD or PDF data to the design checking modules, which can include the zoning checking module 632, landscaping checking module 633, Drainage checking module 634, and module 635 that can check for any other requirements, such as transportation, sanitation, etc. Outputs of the respective design checking modules can be supplied as inputs to a verification report model 640 for compiling such that this information can be supplied as input to a results reporting engine 650. The results reporting engine 650 can an output a report that is provided to a user system 130 and/or an external system 140. For example, the results or findings of the review (e.g., any issue flagged) can be presented as output, e.g., to user system 130. Further, the results can be used to preliminarily approve the permit, e.g., the results will have to be briefly reviewed by a government staff, and the results can be sent and reported to the government authority, which can be one of the external systems 140. [0077] In each of these processes, the BIM or CAD or PDF requirements have to be established and stated according to the BIM or CAD or PDF standard procedure. In order to develop the IDM, the source regulation information needs to be classified. In one illustrative and non-limiting example, Florida Building Code (FBC 2020) is considered as the source example for an implementation of the exemplary framework, as illustrated in Table 2 (below). FBC is, typically, updated every 3 years. Table 2 [0078] The IFC schema encompasses a wide range of data objects. Thus, it is recommended that each discipline domain should only consider a subset of the full IFC schema to avoid processing an overwhelming amount of data. A Model View Definition (MVD) is developed as the tool for creating model subsets that are pertinent to the specific data exchange between domain application types. MVD diagram describes the concepts and attributes that will be used in the data exchange, as well as the schema and relationships between these concepts and attributes. In general, the exchange models are transformed from the IDM into various concepts. Each concept, in turn, is described with several attributes and relationships. The concluding phase is the translation of the MVD into implementation IFC entities, attributes, relationships and properties as required by the IFC schema.
[0079] The process of developing the MVDs counts on the description of the information exchange models (EMs) in the IDM and how they will be utilized, both with respect to domain users and software developers. From this information, the MVD is established for each attribute and describes how it is to be handled in the IFC schema.
In essence, MVD offers the specification for IFC based data exchange implementation. [0080] In various embodiments, a MVD can represent part of the exchanges for code checking and the land development plan. An exemplary MVD can provide the basis for developing MVD covering other parts of land development regulations and standards, which will enable high-quality IFC implementations that satisfy a design review process.
[0081] The development of the MVDs and EMs allows for certain objective aspects of the codes and regulations of the extracted and encoded in the High-order Level III phase. The Lower Order Level phase of an exemplary GAF framework introduces the method of transforming (step 506) ambiguous provisions into rules by applying an algorithm for partial transformation using first order logic (FOL), fuzzy logic, integration, decomposition, and approximate reasoning methods. Fuzzy logic offers ways of modeling linguistic rules in such a format that they can be integrated into a coherent logical schema (Nawari, 2019).
[0082] An illustrative and non-limiting example of vague design regulations can be found in Florida Building Code 2020-Residential (FBC 2020-R) section R322.1 In this provision, the regulations states:
Buildings and structures constructed in whole or in part in flood hazard areas, including A or V Zones and Coastal A Zones, as established in Table R301.2(1 ), and substantial improvement and restoration of substantial damage of buildings and structures in flood hazard areas, shall be designed and constructed in accordance with the provisions contained in this section.
The word substantial is never defined precisely. Using an exemplary approach, then we have
REG 1 = "Section R 322.1"; then we have REG 1 ∈ (C 1 ∩ A 1 ) ) (11 )
24 where REG1 is a variable for the regulation section, (C1 ^ A1) designates that this is a content clause with ambiguous statements describing flood resistance construction. Now let where, R 1 , R 2 , …Rm are the rules defining REG1. Next let (13) [0083] Now using logic notations, we have [0084] In terms of the conceptualization of the expression “substantial damage”, fuzzy logic and predicates will be employed to translate the concepts into a computable model. A fuzzy set is defined as (Zadeh, 1965): A is a fuzzy subset of the universe of discourse U, is characterized by a membership function μ A : U→ [0…1] which associates with each element u of U a number P A (u) in the interval [0,1]. This description can be utilized to express fuzzy predicate (Nawari, 2018). The truth-value of any proposition can be estimated as the degree of membership of the corresponding fuzzy relation. Consequently, a fuzzy predicate can be described as the membership function of a fuzzy relation over individual variables' universe of discourse. Each fuzzy predicate signifies a concept in the GAF. For instance, the building damage described in section R322 of the FBC 2020-R can be modeled as a fuzzy variable. These involve small damage, medium damage, and substantial damage. Next, let z i2 = a fuzzy variable described as where 0 < μ A (u) ≤ 1. [0085] Finally, section R322 of the FBC 2020-Residential is transformed into the following rule: [0086] Engineering design codes do have quite often such vague terms to describe certain conditions. Table 5 (below) summarizes some of these terms and their transformation using a fuzzy predicate.
Table 5 [0087] The fuzzy predicate may be defined as a relation with arguments, and the arguments may be constants or variable: Rel(u, A), where A is fuzzy set, Rel is a relation, and u is an element in the Universe of discourse U. For instance, “Building X damage is substantial.” The fuzzy predicate is given by Damage(Building X, substantial) where “substantial” is fuzzy set, “Damage” is a relation and “Building X” is an individual element. [0088] By integrating land development permit applications and related documents with building information modeling concepts, exemplary methods and systems can be employed to evaluate and check for compliance with such documents with applicable land development codes and regulations. Accordingly, in various embodiments, land development codes and regulations can be transformed into equivalent logic rules by which an input file can be assessed using artificial intelligence and machine learning via one or more artificial neural networks. An exemplary system uses neural NLP techniques and/or deep neural network-style machine learning / artificial intelligence. In various embodiments, the framework software can be installed on a central server that can be made available to various local municipalities to provide code compliance review and related services for the land development plans and related documents involving the municipalities and their constituents. In some embodiments, the framework software comprises a plug-in piece of software for an existing computer program. In accordance with the present disclosure, a land development permit application file standard can be established for the development of land development permit applications and computable records of land development code regulations. As such, a rule-based system, implemented via an artificial intelligence (AI) system or neural network, can be established to automatically check land development code conformance and other regulations. In various embodiments, the neural network can output prediction confidence data for its compliance review and/or classification of land development plan details. Any inaccurate prediction of code conformance can be fed back to the AI system for improved prediction in the future. To do so, the neural network may use supervised or unsupervised or other learning methods to improve accuracy of land development code conformance review of land development projects. [0089] Next, FIG.7 shows an exemplary land development plan review process, in accordance with various embodiments of the present disclosure. To start this process, an applicant can upload a land development permit application, in step 702, which can be prescreened, in step 704, to verify that the application is in the correct format, to verify contact information is provided for the applicant, or to verify other information that does not require detailed analysis or expert analysis of the contents of the application file. After the prescreening review is approved and completed, then in step 706, the land development permit application file can begin to be analyzed via an embodiment of an exemplary automated determination of land development code performance framework of the present disclosure. As part of this analysis, a previously stored version of the land development permit application file may be retrieved and compared against an updated version of the land development application file. Upon completion of the review and analysis, the applicant may be notified of the results, in step 710, such that corrections may be required and additional information may need to be reviewed or the applicant may be granted a land development permit if corrections are not required. [0090] The present disclosure provides various systems and methods of automated determination of land development code, ordinances, and regulatory compliance checking process. One such method among others comprises receiving, by a computing device, a land development permit application file for a land development site plan, wherein the land development permit application file includes a BIM or CAD or PDF file of the land development site plan; checking, by the computing device, the land development permit application file for land development code, ordinances, and regulatory compliance checking with computable files defining applicable land development codes, ordinances, and regulations; generating, by the computing device, a land development code, ordinances, and regulatory compliance checking report indicating whether the land development permit application file has passed a check for the land development code, ordinances, and regulatory conformance; and transmitting, by the computing device, the land development code, ordinances, and regulations’ conformance report to a client device of an applicant associated with the land development permit application file. [0091] As discussed, the present disclosure also provides systems of automated determination of land development code ordinances, and regulations conformance. One such system comprises at least one processor; and memory configured to communicate with the at least one processor, wherein the memory stores instructions that, in response to execution by the at least one processor, cause the at least one processor to perform operations comprising: receiving a land development permit application file, wherein the land development permit application file includes a BIM or CAD or PDF file of a land development site plan; checking the land development permit application file for land development code conformance with computable files defining land development codes, ordinances, and regulations; generating a land development code, ordinances, and regulations conformance report indicating whether the land development permit application file has passed a check for the land development code, ordinances, and regulations conformance; and transmitting the land development code, ordinances, and regulations compliance checking or conformance report to a client device of an applicant associated with the land development permit application file. [0092] In one or more aspects, an exemplary system/method may further comprise acquiring land use details from the BIM or CAD or PDF file of the land development site plan, wherein the checking for land development code, ordinances, and regulations compliance comprises checking the land use details of the land development site plan for conformance with land use codes, ordinances, and regulations as defined with the computable files; retrieving a stored land development code, ordinances, and regulations conformance review report of the applicant for the land development site plan; acquiring zoning details of the land development site plan from the BIM or CAD or PDF file of the land development site plan; wherein the checking for land development code compliance comprises checking the land use details of the land development site plan for conformance with zoning codes, ordinances, and/or regulations as defined with the computable files; storing the land development code, ordinances, and regulations conformance report to a database of the computing device; and/or transforming or converting, by the computing device, a land development code, ordinance, and regulation into a computable record that defines a rule for the land development code, ordinance, and regulation. [0093] In one or more aspects of the system/method, the computing device executes a neural network to perform tasks associated with the land development permit review; the neural network outputs prediction confidence data for a land development code, ordinance, and regulation conformance review of the land development site plan; the neural network undergoes supervised training to improve accuracy of land development code, ordinances, and regulations conformance review of land development site plans; and/or the neural network undergoes unsupervised training to improve accuracy of land development code, ordinances, and regulations conformance review of land development site plans. [0094] Referring now to FIG. 8A, an overview is provided for an exemplary computing system in accordance with embodiments of the present disclosure. In this illustrative example, the computing system is referred to as a Code, Ordinance, and Regulatory Code Checking System. The Regulatory Code, Ordinance, and Regulatory Checking System receives as input a land development permit application, which is also referred to as a General Development Plan, in the form of or containing CAD drawings or BIM Model or PDF file in addition to a legal description of a piece of property and general notes associated with the development plan. After receipt of the land development permit application, the Regulatory Code Checking System evaluates or analyzes the plan against computable land development records of zoning code regulations. As such, a rule-based system, implemented via an artificial intelligence system or neural network, can be performed by the Regulatory Code Checking System to automatically check zoning code, ordinance, and regulation conformance, as one possible example. In various embodiments, the neural network can output prediction confidence data for its compliance review and/or classification of land development plan details. After analysis of the land development is completed, the Regulatory Code Checking System prepares one or more land development code conformance reports. In the illustrative example of FIG. 8A, a detailed zoning compliance report and a development compliance report are generated. For the development compliance report, areas where the land development plan conforms with the applicable codes, ordinances, and regulations are listed and/or areas where the land development plan do not conform with the applicable codes, ordinances, and regulations are listed. For the detailed report (also shown in FIG.8B), the foregoing information may be provided in addition to a map showing a drawing of the proposed development superimposed on a GIS (geographic information system) map of the geographic area having the applicable zoning conditions illustrated. Accordingly, in various embodiments, a CAD drawing or BIM model or PDF file can be processed and formatted so that it can be accurately positioned on a GIS map. In one such embodiment, processes displayed in FIGS.9A-9B can be executed by the Regulatory Code Checking System or other computing device. [0095] Additionally, in various embodiments, imaging data of the piece of property under consideration for the land development site plan may be captured using an unmanned aerial vehicle or drone to aid in identification of and/or confirmation of information provided in the land development permit application. Imaging data can include photographs, videos, thermal images, LIDAR images of the site. In accordance with various embodiments, artificial intelligence (AI) algorithms can be implemented by the Regulatory Code Checking System to identify the site’s main features and compare them with corresponding features submitted in a CAD or BIM or PDF file for validation. Accordingly, imaging data can be stored in one or more databases 114. [0096] In some embodiments, the framework software comprises a plug-in piece of software for an existing computer program. In some embodiments, the plug-in software installed as an external program (sometimes referred to as “addin”) allows the user of the software program to (a) perform real time code checking and/or compliance of individual building and site elements or components as the site design model is being developed/ modeled in the software platform; (b) perform real time code checking and/or compliance of whole site as the site design model is being developed/ modeled in the software platform; (c) perform real time display of relevant codes for individual site elements or components as the site design model is being developed/ modeled in the software platform; (d) perform real time display of relevant codes for the whole site as the site design model is being developed/ modeled in the software platform; and (d) perform real time display and interactive training materials or site elements or components or whole site as the site design model is being developed/modeled in the software platform. In some embodiments, the plug-in software shows a semi-transparent interface embedded with buttons for enabling the above listed actions, as illustrated in FIG.9C. This interface is moveable (rotate, move, translate, scale) and can be pinned to the software program. In some embodiments, the plug-in software can run in the cloud-computing environment or in a desktop application. [0097] FIGS.10A-10C show exemplary reports of application items that have been noted or flagged for not conforming with or violating applicable zone regulations or indicating errant items in the application file. Namely, FIG.10A shows land use flagged items, FIG. 10B shows transportation flagged items, and FIG. 10C shows flagged general notes items. Accordingly, individual reports can be output for different parts of a land development permit application asides zoning, such as those involving transportation infrastructures, utilities, parking, landscaping, drainage, sanitation, street lights, water lines, power lines, other infrastructure elements, etc. An exemplary CAD drawing that can be used with a land development permit application is provided in FIG. 11. Here, the CAD file contains a landscape design that can be examined against the relevant landscape codes, ordinances, and regulations for the landscape review. For instance, this includes determining the percentage of lawn to the impervious areas, number, types, and locations of shrubs and trees. The same approach can also be implemented for drainage and sanitary sewers, utility lines, culvert, roads, bridges, erosion controls, wetland controls, and other infrastructure elements. [0098] Exemplary systems and methods of the present disclosure involves site layout design which includes processing data provided by engineers, surveyors, attorneys, and planners to ensure that land is developed in accordance with the relevant codes, such as development code, comprehensive plan, landscape code, and utility code of each country or city and propose a layout design of parcels, roads, sewers, and other utilities needed for the site. An exemplary algorithm of the present disclosure , based on artificial intelligence technologies, such as machine learning, neural network(s), fuzzy logic, and/or genetic algorithms, can automate the site layout process and provide multiple layout options that comply with relevant codes and regulations. With this type of tool, designers can set optimization criteria (such as maximizing the number of parcels) and be provided various site layout options. Via optimization tools, layout criteria can be integrated to add up to a desired site plan, such as connecting residents to parks and other commercial destinations by designing for pedestrian flow and laying out parcels to maximize view corridors and setbacks of backyards to property boundaries and front yards to the street, while complying with the applicable codes and regulations. In this way, all details of the site can be incorporated, such as stormwater systems, trail systems, parks, community centers, or any other shared site feature. Additionally, in various embodiments, artificial intelligence visualization tools allows users to experience a newly developed site before the site is constructed and navigate site spaces before having to make any investment or purchases. Accordingly, real-time feedback (e.g., visual computer simulation of site layout) can be obtained by changing site variables or criteria. Thus, a site plan can be optimized to obtain the most suitable arrangement of properties by adjusting multiple variables or parameters, including solar gain, number of parcels, program, profit, project cost, backyard size, landscape variety, views, etc. [0099] In accordance with embodiments of the present disclosure, extraction of information from a land development permit can be developed based on specific site regulations per the zoning code. The site address can be automatically compared to the zoning code and regulations for the specific city/county with which the site address is associated. An exemplary algorithm takes the government entity’s codes and processes them through computational algorithms to provide the client with the answers to their site development plan. Project land use information is vital for a developer to show the government entity that they know the current code requirements and are willing to comply with them. After generating the attribute tables and understanding them, an exemplary algorithm can continue to show site planning possibilities through related algorithms, such as the site summary analysis, transportation analysis, and more. [00100] In an exemplary transportation analysis process, clients can submit a land development plan and an exemplary algorithm reviews the plan, including AutoCAD or Revit files that accompany the plan, and generates notes indicating what needs to be addressed or fixed and the reasons why the item(s) need correcting, all according to the applicable government entity standards and regulations. [00101] As such, an exemplary system provides developers the opportunity to get their plans reviewed prior to submitting them to the government entity. This enhances the developers’ chances of getting their site plan approval in the first review cycle. In an exemplary non-limiting implementation, the transportation review involves a review of over 144 local transportation requirements to improve a site. The transportation review is normally reviewed by multiple professionals in a government entity; these professionals could have different opinions with different approval conditions. [00102] An exemplary system removes all biases and references only to the code- specific requirements. The specific code requirements allow the developer to look at what should be fixed and why it should be resolved. After reviewing a submitted PDF, AutoCAD, or Revit file, an exemplary algorithm will give the client “Flag Notes.” The “Flag Notes” are created based on what corrections must be made on the submitted PDF, AutoCAD, or Revit file and why they need to be corrected. Flag Notes can include a report showing which specific sections in a site plan must be corrected based on the particular government entity code requirements. The Flag Notes can have a summary for every transportation attribute flagged and show the client any related code links to show specifically why the site plan must be corrected prior to approval. [00103] In an exemplary landscape review process, an exemplary algorithm ensures that client site plans comply with the applicable landscaping codes and standards, such as those related to Native Shade Trees, Native Accent Trees, Native Palm Species, Native Shrubs, Native Groundcover Species, Native Grass Species, Mulching, ROW Buffer, Interior Parking Guidelines, Street Trees, Buffers and Screening Requirements, Open Storage, Solid Waste Storage, Stormwater Evaluation, and/or Wheel Stops and Curbs. [00104] After an exemplary system reviews the PDF, CAD, or Revit file attributes of a landscaping plan, an exemplary algorithm can present results on what is needed to be fixed and why the item(s) need to be corrected before submitting them to a government entity, thereby reducing the amount of time a client would have to go back and forth to the city prior to the approval of their site plan. The results (“Flag Notes”) can provide the client with the information needed to adjust the applicable file in order to make sure that the site plan is up to code prior to submitting it to a government entity. Thus, Flag Notes are one way that an exemplary system can instruct a client on which code they are not complying with and how to correct this error. Flag Notes can show precisely how developers can adjust their plans to the approval requirements and give developers the specific municide links of where to refer to the code for that particular code requirement giving the client access to the specific landscape code, zoning code, or comprehensive plan links to understand the particular area that needs to be fixed and why it must be corrected prior to submission. [00105] Given that government entities have their own specific local landscaping code and land development code guidelines, an exemplary system can take all the local codes, states’ landscaping codes, and landscaping requirements to review a site plan and make sure that the plan is ready for submittal according to those specific code requirements. [00106] In various embodiments, an exemplary landscaping review process examines the proposed pervious structures and the placement of each species, where the applicable codes or regulations define distances of location and placement of the landscaping standards for the specific site. In an exemplary implementation, disclosed algorithms process thousands of lines of codes to make sure that the client has the support needed to show compliance with all government code requirements for the landscaping approval in addition to removing subjective biases from the landscaping review process and solely referring to the specific code requirements for that zone. In brief, there are many different land development possibilities with any site, and knowing what the site is composed of will help define how the site can be retrofitted. In an exemplary site summary review process, an analytical review report is generated that informs the client on what they can or cannot build with the specific parcel’s current zoning and future land use specifications. [00107] Knowing how many units could possibly be built on a property is vital for the buyer of any property. An exemplary site summary algorithm allows users to compare the local income and homestead/non-homestead properties to provide information about the estimated selling price of a single-family home. Furthermore, it enables users to review the property and analyze the possibilities of developing single-family homes, multifamily homes, duplexes, condos, apartments, etc. An exemplary algorithm has density calculations using trained AI to analyze the property and inform the client within seconds, what they can build on the property, how high they can build, minimum lot requirements, and more. [00108] Informative decision-making in investing in vacant land can help the land buyers understand property analytics. The site summary can tell the buyer or investor precisely what the land is composed of, such as soil types and the current species on the land. Identifying what the land is composed of is vital to site plan development, showing the buyer what they can currently use on the property and what they will need to buy for landscaping requirements conserving the site’s current state as much as possible and enhancing the existing site features through the site plan design suggestions. [00109] An exemplary site summary algorithm can also inform the client about the local demographics of the area, such as the local languages spoken, income per household, spending categories per household, families with disability ratings, and more. For example, demographic analysis can inform who the neighborhood is and who the developer would have as potential clients, thereby creating a summarized plan on a possible approach for site development for any specific address point. [00110] In an exemplary implementation, the site summary analysis includes a location map of the site and a local neighborhood report, which can include data analyzing the local neighborhood to show the developer rent to own ratios, or the community amenities such as local restaurants. An exemplary system can collect this information to show exactly what the community surrounding a site is like by using a buffer zone analysis (e.g., 0.5 mi buffer zone, 1 mile buffer, 3 mile, and 5 mile buffer zones). [00111] In an exemplary implementation, the site summary analysis includes a zoning regulations report, which can include site features and GIS maps such as, but not limited to, Location Map, Bodies of Water Map, Wetland Location Map, Elevations, Contours, and Depression Map, FEMA Flood Zone (Federal Emergency Management Agency) Map, and/or Soil Map. Thus, the zoning regulations report can show the zoning regulations that apply to a specific area and allow a developer to understand the buildable possibilities for that specific area or zone, along with minimum lot requirements. For example, the wetland location map can show wetland zones that are classified as environmentally sensitive areas that are near a site. If a wetland area is classified as a conservation area, then a certain setback may be required (e.g., 30 feet). Correspondingly, if the wetland area is classified as a preservation area, then a larger setback may be required (e.g., 50 feet), in accordance with applicable land use codes or regulations. When building near wetlands sites, land development plan will generally need to comply with applicable wetlands regulations and will need to show the protection of the wildlife habitat (e.g., plan can show that no roadway is to be built near the wetland habitat). [00112] In an exemplary implementation, the site summary analysis can include an elevations map showing buildable opportunities with the elevation’s sources shown. In an exemplary implementation, the site summary analysis can include a FEMA Flood Zone map showing possibilities for flooding through heavy rains or poor drainage at a site. The flood map characterizes or categorizes the flood zone risk as: high-risk, low-risk, or moderate risk. [00113] In an exemplary implementation, the site summary analysis includes a sample soil survey for a site and the related goals as prescribed by applicable coding and regulations. As an example, the goals described in the coding regulations may involve the minimization of impact to land alteration in unnecessary removal of existing vegetation or alteration of the topographic land surface features. Correspondingly, the site summary analysis may recommend that land development of a site there should be sodded, plugged, sprigged, seeded, or covered vegetation in ordinance with the applicable codes and regulations. [00114] In an exemplary implementation, the site summary analysis includes a landscaping report that specify landscaping requirements. For example, design standards according to applicable development codes may be related to requirements for energy conservation, water conservation and quality, vehicular and pedestrian safety, aesthetically pleasing and functional living environment, transitional interface between development and uncomplimentary and/or incompatible land uses, compliance with future land uses, etc. [00115] The above description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles described herein can be applied to other embodiments without departing from the spirit or scope of the invention. Thus, it is to be understood that the description and drawings presented herein represent embodiments of the invention and are therefore representative of the subject matter which is broadly contemplated by the present invention. It is further understood that the scope of the present invention fully encompasses other embodiments that may become obvious to those skilled in the art and that the scope of the present invention is accordingly not limited. [00116] Combinations, described herein, such as “at least one of A, B, or C,” “one or more of A, B, or C,” “at least one of A, B, and C,” “one or more of A, B, and C,” and “A, B, C, or any combination thereof” include any combination of A, B, and/or C, and may include multiples of A, multiples of B, or multiples of C. Specifically, combinations such as “at least one of A, B, or C,” “one or more of A, B, or C,” “at least one of A, B, and C,” “one or more of A, B, and C,” and “A, B, C, or any combination thereof” may be A only, B only, C only, A and B, A and C, B and C, or A and B and C, and any such combination may contain one or more members of its constituents A, B, and/or C. For example, a combination of A and B may comprise one A and multiple B’s, multiple A’s and one B, or multiple A’s and multiple B’s.
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