Methods and systems for rendering and modifying three-dimensional models for interior design
A system for rendering and modifying three-dimensional models for interior design includes receiving a current design of an interior space, generating a data structure representing the interior space, wherein generating the data structure further comprises generating a first three-dimensional model of a first portion of the interior space based on the current design, wherein the first three-dimensional model comprises a first feature having a first attribute, receiving at least a command to modify the first attribute, modifying the first three-dimensional model as a function of the at least a command to modify the first attribute and the plurality of degrees of importance, displaying a modified three-dimensional model, and generating a smart contract, wherein the smart contract is associated with the modified three-dimensional model.
1 . A method of rendering and modifying three-dimensional models for interior design, the method comprising:
receiving, using a modeling device, a current design of an interior space;
generating, using the modeling device, a data structure representing the interior space, wherein generating the data structure further comprises generating a first three-dimensional model of a first portion of the interior space based on the current design, wherein the first three-dimensional model comprises a first feature having a first attribute, wherein generating the first three-dimensional model comprises:
receiving at least one image of the first portion of the interior space;
detecting objects within the at least one image using a machine-learning classification algorithm and matching the detected objects to feature identifiers stored in a feature database;
classifying the detected objects to a plurality of features;
determining a global style attribute of the first three-dimensional model;
associating at least one of the plurality of features with the current design, wherein the at least one associated feature includes at least one attribute matching the global style attribute; and
generating the first three-dimensional model using the plurality of features;
receiving, using the modeling device, at least a command to modify the first attribute, wherein receiving the at least a command comprises:
receiving a plurality of user goals comprising an energy consumption goal specifying a level of electrical energy which should be consumed by the first feature, wherein receiving the plurality of user goals further comprises receiving a plurality of degrees of importance corresponding to the plurality of user goals;
modifying, using the modeling device, the first three-dimensional model as a function of the at least a command to modify the first attribute and the plurality of degrees of importance;
displaying, using a user display device, a modified three-dimensional model; and
generating a smart contract, wherein the smart contract is associated with the modified three-dimensional model.
2 . The method of claim 1 , wherein displaying at a user device, a plurality of event handlers permits user entry of degrees of importance, wherein each of the plurality of event handlers corresponds to a user goal of the plurality of user goals.
3 . The method of claim 1 , wherein the method is further configured to execute the smart contract, wherein executing the smart contract comprises:
receiving, a digital signature from a plurality of stakeholders; and
validating the digital signature from the plurality of stakeholders.
4 . The method of claim 1 , wherein generating the smart contract comprises generating a serial identifier, wherein the serial identifier is assigned to each instance of the smart contract.
5 . The method of claim 4 , wherein the serial identifier includes entries to be verified using an immutable sequential listing.
6 . The method of claim 3 , wherein the method further utilizes a cryptographic system wherein the cryptographic system validates the digital signature of the plurality of stakeholders.
7 . The method of claim 1 , wherein the method comprises a machine learning model, wherein the machine learning model is trained using a plurality of executed smart contracts.
8 . The method of claim 1 , wherein the first feature is associated with a financial variable, wherein the financial variable corresponds to a spatial datum.
9 . The method of claim 8 , further comprising calculating a financial variable, wherein calculating the financial variable comprises:
training a locality machine-learning model using locality training data, wherein the locality training data comprises first features and locality data correlated to financial variables; and
generating the financial variable using the trained locality machine-learning model.
10 . The method of claim 8 , wherein the financial variable comprises a plurality of cost components.
11 . A system for rendering and modifying three-dimensional models for interior design, the system comprising:
at least a computing device, wherein the at least a computing device comprises:
a memory; and
at least a processor communicatively connected to the memory, wherein the memory contains instructions configuring the at least a processor to:
receive a current design of an interior space;
generate a data structure representing the interior space, wherein generating the data structure further comprises generating a first three-dimensional model of a first portion of the interior space based on the current design, wherein the first three-dimensional model comprises a first feature having a first attribute, wherein generating the first three-dimensional model comprises:
receiving at least one image of the first portion of the interior space;
detecting objects within the at least one image using a machine-learning classification algorithm and matching the detected objects to feature identifiers stored in a feature database;
classifying the detected objects to a plurality of features;
determining a global style attribute of the first three-dimensional model;
associating at least one of the plurality of features with the current design, wherein the at least one associated feature includes at least one attribute matching the global style attribute; and
generating the first three-dimensional model using the plurality of features;
receive, using the at least a computing device, at least a command to modify the first attribute, wherein receiving the at least a command comprises:
receiving a plurality of user goals comprising an energy consumption goal specifying a level of electrical energy which should be consumed by the first feature, wherein receiving the plurality of user goals further comprises receiving a plurality of degrees of importance corresponding to the plurality of user goals;
modify, using the modeling device, the first three-dimensional model as a function of the at least a command to modify the first attribute and the plurality of degrees of importance;
display, using a user display device, a modified three-dimensional model; and
generate a smart contract, wherein the smart contract is associated with the modified three-dimensional model.
12 . The system of claim 11 , wherein displaying at a user device, a plurality of event handlers permits user entry of degrees of importance, wherein each of the plurality of event handlers corresponds to a user goal of the plurality of user goals.
13 . The system of claim 11 , wherein the system is further configured to execute the smart contract, wherein executing the smart contract comprises:
receiving, a digital signature from a plurality of stakeholders; and
validating the digital signature from the plurality of stakeholders.
14 . The system of claim 13 , wherein the system further utilizes a cryptographic system wherein the cryptographic system validates the digital signature of the plurality of stakeholders.
15 . The system of claim 11 , wherein generating the smart contract comprises generating a serial identifier, wherein the serial identifier is assigned to each instance of the smart contract.
16 . The system of claim 15 , wherein the serial identifier includes entries to be verified using an immutable sequential listing.
17 . The system of claim 11 , wherein the system comprises a machine learning model, wherein the machine learning model is trained using a plurality of executed smart contracts.
18 . The system of claim 11 , wherein the first feature is associated with a financial variable, wherein the financial variable corresponds to a spatial datum.
19 . The system of claim 18 , further comprising calculating a financial variable, wherein calculating the financial variable comprises:
training a locality machine-learning model using locality training data, wherein the locality training data comprises first features and locality data correlated to financial variables; and
generating the financial variable using the trained locality machine-learning model.
20 . The system of claim 18 , wherein the financial variable comprises a plurality of cost components.