N-Dimensional Asset Identifiers for Spatial Data Integration
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Solution Overview
Problem
Traditional methods for identifying and tracking assets, such as buildings, are inefficient due to address duplicates, computationally taxing data structures, and disparate identification schemes, making it difficult to join data from disparate sources and compare large sets of building data.
Innovation Solution
The use of n-dimensional asset identifiers that encode a center-of-mass position and center-of-mass-to-bounding-polytope extents into a single, non-opaque code string, allowing for unique, standardized, and scalable identification of assets with a spatial and temporal aspect, enabling efficient cross-referencing across different data sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional address systems or GPS coordinates are used to identify assets, then assets can be located, but address duplicates and multiple buildings per address make data joining difficult and computationally inefficient
Solution Approach 1:
The patent transitions from traditional 2D address systems or point-based GPS coordinates to a 3D spatial grid system. Each asset is identified by its position in three-dimensional space (latitude, longitude, elevation) combined with a temporal component, creating a unique spatio-temporal identifier that resolves ambiguities of traditional systems where multiple buildings share the same address or coordinate point.
Solution Approach 2:
The patent segments the continuous spatial space into discrete grid cells or volumetric zones. By dividing space into manageable segments and assigning identifiers based on these segments rather than continuous coordinates, the system creates discrete, comparable units that can be efficiently joined and cross-referenced across different data sources.
2Adaptability or versatility
If disparate identification schemes are used across different data sources, then each source can maintain its own format, but joining and comparing data from multiple sources becomes difficult or impossible
Solution Approach 1:
The patent creates a universal spatio-temporal identifier system that can represent any physical asset regardless of its original identification scheme. The standardized format incorporating spatial coordinates, temporal information, and optional attribute fields serves multiple functions: unique identification, spatial indexing, temporal tracking, and data integration, replacing multiple specialized identification systems with one versatile standard.
Solution Approach 2:
The patent transforms diverse asset identifiers into a standardized parameter structure consisting of spatial components (latitude, longitude, elevation), temporal components (timestamp, duration), and optional attribute parameters. This parameter transformation allows data from different sources with varying original formats to be converted into a common structure that enables efficient joining and comparison operations.
3Measurement precision
If detailed asset geometry is encoded into identifiers, then precise asset representation is achieved, but identifier length and processing complexity increase
Solution Approach 1:
The patent extracts only the essential spatial and temporal parameters needed for identification and comparison, separating these from detailed geometric information. Instead of encoding complete asset geometry, the system extracts key parameters (position coordinates, time stamp, duration) that capture the essential spatio-temporal characteristics while keeping identifiers compact and computationally efficient.
Solution Approach 2:
The patent represents asset position and extent not through detailed geometric descriptions but through simplified dimensional parameters in a standardized coordinate system. By using discrete spatial dimensions (latitude, longitude, elevation) combined with temporal dimensions, the system achieves precise representation without the complexity of full geometric encoding.
Data Source
AI summary
Described herein are methods, systems, and storage media having computer-processable instructions for cross-referencing in a computationally efficient manner different data sets each having pluralities of n-dimensional identifiers of physical assets. The disclosed cross-referencing approach can be used to determine relationships between different assets and their respective asset identifier strings. The relationships can be established based on user-selected heuristics. For example, at least two asset identifier strings can be compared, and user-defined heuristics can be applied to determine whether “a match” exists. A match can be defined according to the particular heuristic. In one instance, the comparison and heuristic can be applied to determine if two different asset identifier strings refer to a single physical asset.