Geoencoded Image Analysis for Precise Demographic Profiling

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Solution Overview

Problem

Existing methods for extracting demographic information from geoencoded images are inefficient and imprecise, often relying on manual analysis or coarse statistical approximations.

Innovation Solution

A system utilizing AI image analysis, specifically convolutional neural networks, to extract demographic data such as age groups, gender distribution, and socioeconomic status from geoencoded imagery like satellite and street view images, integrating this data with GIS for precise location-based demographic profiling.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual analysis or coarse statistical approximations are used to extract demographic information from geoencoded images, then the system complexity is reduced, but the measurement precision and productivity deteriorate

Engineering Contradiction:

Improvedemographic information precisionVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent replaces manual analysis (mechanical human processing) with automated AI image analysis systems that use machine learning algorithms to extract demographic information from geoencoded images, achieving both higher precision and reduced operational complexity

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent introduces an intermediary AI processing layer between geoencoded images and demographic data extraction, using machine learning models as mediators to automatically transform visual data into structured demographic information with high precision

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If AI image analysis with convolutional neural networks is used to extract demographic data, then the productivity and measurement precision improve, but the device complexity and energy consumption increase

Engineering Contradiction:

Improvedemographic data extraction efficiencyVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent segments the AI image analysis process into distinct functional modules including image acquisition, feature extraction using convolutional neural networks, demographic inference, and data integration with GIS systems, making the complex system manageable and scalable

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent develops a universal AI processing framework that can extract multiple types of demographic information (age, gender, socioeconomic status) from various types of geoencoded images (satellite, street view), making the system versatile and reducing overall system complexity through multi-functionality

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Loss of time

If AI image analysis is applied to extract demographic information, then the processing time is reduced, but the energy consumption increases

Engineering Contradiction:

Improveprocessing timeVSAvoidenergy consumption

Core Design Contradiction:

Loss of timeVSUse of energy by moving object

Solution Approach 1:

The patent performs preliminary actions by pre-processing images and training machine learning models in advance, so that when actual demographic extraction is needed, the system can quickly process images without requiring high computational resources during the extraction phase, reducing real-time energy consumption

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20250335473A1Geoencoded image tools that associate textural data and objects with location through image analysis

Publication Date: 2025.10.30 NRBY INC

AI summary

Geoencoded image tool that infers demographic information for a particular location from images, such as satellite images, street view images, and/or other geoencoded images. Aspects may include receiving a request from a user for demographic information for a geographic location, inferring the demographic information based on one or more images of the geographic location, and sending a response to the user with the inferred demographic information.