Spatial Planning System with Hierarchical Visualization

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Solution Overview

Problem

Existing planning systems struggle to effectively organize and analyze complex, multi-dimensional planning data, particularly in contexts where data is varied, spatially sensitive, and requires dynamic visualization and comparison.

Innovation Solution

A computer-implemented spatial planning system that includes a database storing diverse data formats, a processor executing a program to construct visual overlays and analytical frameworks, and smart planning units that facilitate data collection, analysis, and presentation, enabling dynamic and spatially sensitive visualization and comparison.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If traditional planning systems are used to organize complex multi-dimensional data, then data storage is simple, but the ability to analyze and visualize spatial patterns deteriorates

Engineering Contradiction:

Improveability to analyze and visualize spatial patternsVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent transitions from traditional flat data storage to a hierarchical organizing framework with multiple dimensions (project level, community section level, and planning unit level). This dimensional transformation enables complex spatial pattern analysis while maintaining manageable system complexity through structured organization.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

Solution Approach 2:

The system segments complex planning data into hierarchical units (projects → community sections → planning units), allowing analysis of spatial patterns at different levels of granularity. This segmentation enables versatile analysis capabilities without overwhelming system complexity.

Inventive Principle:

Principle #1Segmentation

2Measurement precision

If detailed spatial data is visualized at high resolution, then analysis precision improves, but processing time and computational resources increase

Engineering Contradiction:

Improvespatial analysis precisionVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The hierarchical segmentation of spatial data into planning units allows the system to process and visualize data at appropriate levels of detail. Users can analyze specific planning units with high precision without requiring the entire dataset to be processed at the same resolution, reducing overall processing time.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system applies different levels of detail and visualization quality to different spatial units based on their importance and scale. High-resolution visualization is applied locally to specific planning units requiring detailed analysis, while broader areas use aggregated views, optimizing processing efficiency.

Inventive Principle:

Principle #3Local quality

3Quantity of substance

If multiple data formats and sources are integrated, then data comprehensiveness improves, but system complexity and difficulty of integration increase

Engineering Contradiction:

Improvedata comprehensivenessVSAvoidintegration complexity

Core Design Contradiction:

Quantity of substanceVSDevice complexity

Solution Approach 1:

The organizing framework structure serves multiple functions simultaneously: it organizes diverse data types (spatial data, attributes, observations), enables hierarchical navigation, supports various analysis operations, and facilitates visualization. This multi-functionality integrates comprehensive data without proportionally increasing system complexity.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The hierarchical organizing framework acts as an intermediary layer between raw diverse data sources and analysis tools. It standardizes and structures incoming data from multiple formats and sources, making them compatible and accessible without requiring complex direct integration between all data sources.

Inventive Principle:

Principle #24Intermediary (Mediator)

4Speed

If dynamic visualization updates are implemented in real-time, then responsiveness to changes improves, but computational load and energy consumption increase

Engineering Contradiction:

Improveresponsiveness to data changesVSAvoidcomputational energy consumption

Core Design Contradiction:

SpeedVSUse of energy by moving object

Solution Approach 1:

The system updates visualizations dynamically at the level of individual planning units or community sections where changes occur, rather than refreshing entire datasets. This localized update approach maintains real-time responsiveness while significantly reducing computational energy consumption compared to global updates.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

By segmenting the visualization system into hierarchical units, the patent enables independent updating of specific segments without affecting the entire system. When data changes occur, only the relevant planning units or community sections are refreshed, improving responsiveness while minimizing energy consumption.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS20250173649A1Planning system using spatial-based visualization aids

Publication Date: 2025.05.29 SERAGELDIN MONA

AI summary

A presentation, organizational and analytical system comprises includes an information database component that allows project specific ability to organize data and observations. A computer system constructs visual overlays of spatially mapped features, quantitative and qualitative attributes and produces an analytical framework where the attributes of any spatial location change in response to changes in the features of a context.