Tile-Based Location Search Using Precomputed Distance Matrices

Solution Overview

Problem

Traditional methods for determining distances between locations using longitude and latitude, such as the haversine formula, are computationally resource intensive, leading to inefficiencies in location-based services.

Innovation Solution

Implementing a database lookup system that associates geolocation data with tiles covering a geographical area, allowing for efficient location searches within a prescribed radius without the need for haversine calculations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If the haversine formula is used to calculate distances between locations, then measurement precision is improved, but computational resource consumption increases

Engineering Contradiction:

Improvedistance calculation accuracyVSAvoidcomputational resource consumption

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The patent pre-calculates and stores distance matrices for all tile pairs in a lookup table during system initialization. This preliminary action eliminates the need for real-time haversine calculations when processing location queries, as the distance between any two tiles can be retrieved instantaneously from the pre-computed matrix.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent creates a simplified copy of the geographical space by discretizing it into tiles and representing distances between them in a lookup table. Instead of working with continuous coordinate calculations, the system uses discrete tile identifiers and pre-stored distance values, significantly reducing computational complexity.

Inventive Principle:

Principle #26Copying

2Measurement precision

If the haversine formula is used to determine distances for multiple locations, then measurement precision is improved, but processing speed decreases

Engineering Contradiction:

Improvedistance calculation accuracyVSAvoidprocessing speed

Core Design Contradiction:

Measurement precisionVSSpeed

Solution Approach 1:

The patent pre-calculates and stores distance matrices for all tile pairs in a lookup table during system initialization. This preliminary action eliminates the need for real-time haversine calculations when processing location queries, as the distance between any two tiles can be retrieved instantaneously from the pre-computed matrix.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent replaces the mathematical computation mechanism (haversine formula requiring trigonometric operations) with a data retrieval mechanism (lookup table). This substitution transforms a computationally intensive operation into a simple memory access operation, dramatically improving processing speed.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Measurement precision

If traditional location search methods are used, then measurement precision is improved, but productivity decreases

Engineering Contradiction:

Improvelocation search accuracyVSAvoidsearch efficiency

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The patent divides the continuous geographical space into discrete tiles, each with a unique identifier. This segmentation allows the system to work with simplified tile indices rather than continuous coordinates, enabling efficient database queries and lookup operations while maintaining sufficient location accuracy for practical applications.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent pre-calculates and stores distance matrices for all tile pairs in a lookup table during system initialization. This preliminary action eliminates the need for real-time haversine calculations when processing location queries, as the distance between any two tiles can be retrieved instantaneously from the pre-computed matrix.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20250077598A1Localized Recommendation Systems based on Discovery Radius Optimization

Publication Date: 2025.03.06 RENYOOIT LLC

AI summary

An example method for a localized recommendation search based on discovery radius optimization is provided. The method involves displaying a map image of a geographical area. The method also involves receiving, from a user, a search query. The method further involves querying, based on the search query, a centralized database, wherein the centralized database comprises data indicative of a plurality of tiles covering the geographical area, wherein each tile of the plurality of tiles is associated with a respective list of points of interest associated with locations within the tile, and wherein the centralized database is configured to determine a particular tile associated with the search query. The method additionally involves receiving, from the centralized database, a particular list of points of interest associated with locations within the particular tile. The method also involves displaying a visual representation of the particular list of points of interest.