Geographic Database Search Using Cell Grid Segmentation
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Solution Overview
Problem
Conventional geographic database search methods often require repeating searches in expanded areas, including previously searched regions, which can be inefficient and yield redundant results.
Innovation Solution
A method that uses a grid of cells to identify neighborhoods around a central point, allowing subsequent searches to exclude previously searched cells, enabling incremental and iterative retrieval of points of interest (POIs) by expanding the search area in new, unsearched regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If conventional search methods expand the search area by increasing radius while including previously searched regions, then the search area coverage is improved, but the search efficiency deteriorates due to redundant searches
Solution Approach 1:
The search space is segmented into discrete cells within a grid structure. Each cell can be independently identified, searched, and marked as searched. This segmentation allows the system to track which specific cells have been searched and avoid re-searching them, thereby eliminating redundancy while maintaining comprehensive area coverage.
Solution Approach 2:
The grid of cells is pre-established and cell coordinates are predetermined before the search begins. This preliminary structuring enables efficient tracking of searched cells through simple coordinate comparison, allowing the system to quickly determine whether a cell has already been searched without requiring complex spatial calculations during the search process.
2Reliability
If the search area is expanded to include previously searched regions, then the completeness of POI retrieval is improved, but the time consumption increases due to repeated searches
Solution Approach 1:
By dividing the search area into discrete cells, the system can maintain a complete record of searched regions. When expanding the search area, the system only processes new cells that fall outside the previously searched boundaries, ensuring no POIs are missed while avoiding time-wasting re-searches of already-covered areas.
Solution Approach 2:
The system maintains feedback information in the form of searched cell coordinates. Before searching a cell, the system checks whether its coordinates are already in the searched set. This feedback mechanism ensures that the search expands comprehensively to cover all required areas while efficiently skipping already-processed regions, thus balancing completeness with time efficiency.
Data Source
AI summary
Disclosed herein is a method and apparatus for use in searching a geographic database to retrieve geographic objects one cell from a neighborhood of cells at a time. A cell neighborhood can be defined using a grid of cells and an initial, or center, point. A first neighborhood is identified based on its proximity to the initial search point, and corresponds to a first geographic area defined using the initial point and a distance from the initial search point in a number of directions. In a case that more than one cell neighborhood is used, each subsequent cell neighborhood is defined so that it excludes cells belonging to a previously-searched cell neighborhood. A subsequent neighborhood corresponds to a geographic area that is a distance from the initial point greater than the distance associated with a previously-searched neighborhood.