Commercial District Block Generation With 3D AI Scheme Validation

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Solution Overview

Problem

Conventional AI-based urban design methods generate an excessively large quantity of invalid schemes, failing to meet the actual requirements of urban design, and are inefficient in terms of labor and time consumption.

Innovation Solution

An AI-based method for generating a building block in a commercial district involves data collection, spatial matching, three-dimensional building block generation, and optimization using machine learning, followed by human-computer interaction for scheme display and output, utilizing a surveying and mapping UAV, geographic information platform, and machine learning models like CNN and GAN to ensure scheme validity.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If conventional AI-based automatic generation method is used, then generation speed is improved, but scheme validity deteriorates (excessively large quantity of invalid schemes are generated)

Engineering Contradiction:
Improvegeneration speedVSAvoidscheme validity
Core Design Contradiction:
ProductivityVSReliability

Solution Approach 1:

The patent implements feedback mechanisms by evaluating generated schemes against design requirements and using the evaluation results to guide subsequent generation iterations. The system learns from valid and invalid schemes to improve generation quality, ensuring that productivity gains do not compromise scheme validity.

Inventive Principle:
Principle #23Feedback

Solution Approach 2:

The patent dynamically adjusts generation parameters based on feedback from scheme evaluation. By changing parameters such as generation constraints, sampling rates, and validation thresholds, the system maintains high productivity while ensuring that generated schemes meet validity requirements.

Inventive Principle:
Principle #35Parameter changes

2Reliability

If manual generation from development indexes to three-dimensional form is used, then scheme validity is improved, but labor consumption and time consumption worsen (a lot of people and time are required)

Engineering Contradiction:
Improvescheme validityVSAvoiddesign time
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The patent replaces the manual mechanical design process with an AI-based automated generation system. The system uses machine learning models and algorithms to automatically generate three-dimensional building forms from development indexes, substituting human manual work with computational processes that are both faster and capable of producing valid schemes through integrated validation mechanisms.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

3Extent of automation

If conventional AI-based generation method is used, then automation level is improved, but scheme quality deteriorates (cannot meet the actual requirements of the current urban design)

Engineering Contradiction:
Improveautomation levelVSAvoidscheme quality
Core Design Contradiction:
Extent of automationVSManufacturing precision

Solution Approach 1:

The patent incorporates feedback loops where generated schemes are evaluated against urban design requirements, and evaluation results are fed back to adjust generation parameters and improve subsequent scheme quality. This ensures high automation level while maintaining scheme quality that meets actual urban design requirements.

Inventive Principle:
Principle #23Feedback

Solution Approach 2:

The patent performs preliminary validation and constraint checking during the generation process itself, rather than only after complete generation. By applying design requirements and constraints early in the generation process, the system ensures higher scheme quality while maintaining automation efficiency.

Inventive Principle:
Principle #10Preliminary action

Data Source

PatentUS12536344B2AI-based method for generating building block in commercial district
Publication Date: 2026.01.27 SOUTHEAST UNIV
  • US12536344B2 patent drawing
  • US12536344B2 patent drawing
  • US12536344B2 patent drawing

AI summary

In an artificial intelligence (AI)-based method for generating a building block in a commercial district, geographic information data of a target district and surrounding districts is acquired to construct a three-dimensional space sand table, then design conditions in various planning files and local legal regulations are translated and extracted to generate a three-dimensional building block of the district, and then a training sample library of three-dimensional contour lines of the district is constructed, a machine learning model is loaded to generate three-dimensional building heights of the district and optimize building forms, to generate a plurality of schemes for the building block of the district, and finally simulated display of the schemes and display of scheme indexes are performed by using a holographic display device, and the schemes are outputted.