Spatial Footprint Index Computation via User Clustering
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Solution Overview
Problem
Location-based service providers face challenges in enabling users to be aware of their overall spatial footprint due to the dynamic nature of populations and the vast amount of information required for accurate computation, which often becomes outdated and inaccurate.
Innovation Solution
A system that computes a spatial footprint index by receiving information about physical items associated with users, determining spatial data indicating the physical space occupied by these items, and providing a quantified representation of this space as an output.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive spatial data is collected for all users to compute accurate spatial footprints, then measurement precision is improved, but device complexity and processing requirements increase significantly
Solution Approach 1:
The patent segments the spatial footprint computation by dividing the user base into clusters based on similar spatial behaviors and characteristics. Each cluster is processed independently with representative samples, reducing the overall computational complexity while maintaining measurement precision through cluster-based aggregation rather than individual processing of all users.
Solution Approach 2:
The system performs preliminary actions by pre-computing spatial clusters and representative profiles before the actual footprint measurement is needed. This allows the computation system to have pre-organized data structures and aggregated statistics ready, reducing the complexity of real-time processing while maintaining accuracy.
2Loss of information
If real-time spatial footprint computation is performed for dynamic populations, then information freshness is improved, but processing time and computational resources increase
Solution Approach 1:
The patent implements periodic action by updating spatial footprint computations at scheduled intervals rather than continuously in real-time. The system periodically re-computes clusters and footprints based on accumulated data changes, balancing information freshness with reduced computational time and resource usage compared to continuous real-time processing.
Solution Approach 2:
The system maintains continuity of useful action by continuously accumulating spatial data in the background while performing computations periodically. This ensures that when computation does occur, the most current accumulated data is used, maintaining information freshness without requiring continuous intensive processing.
3Measurement precision
If detailed information about all physical items and users is processed, then spatial footprint accuracy is improved, but data processing complexity and costs increase
Solution Approach 1:
The patent applies taking out by extracting only the essential and representative features from detailed user and physical item data. Instead of processing all raw data points, the system extracts key spatial characteristics, behaviors, and attributes that are sufficient for accurate footprint computation, reducing data processing complexity while maintaining measurement precision.
Solution Approach 2:
The system uses partial action by processing a representative subset of data within each cluster rather than all individual data points. By computing footprints based on cluster representatives and aggregated statistics rather than exhaustive individual processing, the patent achieves sufficient accuracy with reduced processing complexity.
Data Source
AI summary
An approach is disclosed for computing a spatial footprint index. The approach involves, for example, receiving, by one or more processors, information indicating that one or more physical items are associated with a user, a set of users, or a combination thereof. The approach also involves determining, by the one or more processors, spatial data indicating a physical space occupied by the one or more physicals items. The approach further involves computing, by the one or more processors, a spatial footprint index for the user, the set of users, or a combination thereof based on the spatial data, wherein the spatial footprint index is a quantified representation of the physical space occupied by the one or more physical items. The approach further involves providing, by the one or more processors, the spatial footprint index as an output.