Map Generation System Combining Multiple Data Sources
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Solution Overview
Problem
Conventional map technologies often lack sufficient detail, accuracy, or comprehensiveness for representing specific regions or locations, leading to inefficient and ineffective map generation.
Innovation Solution
The system identifies and combines map portions from multiple data sources to generate a comprehensive map, using similarity scores and feature comparisons to select the most suitable map data sets and blend graphical qualities while matching styles within an allowable deviation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If map data from a single map data source is used, then the map generation process is simple, but the map detail and accuracy are insufficient
Solution Approach 1:
The patent segments the map data acquisition process by dividing the region into multiple portions and selecting different map data sources for different portions. This allows the system to achieve high accuracy in each specific region by using the most suitable data source for that area, while maintaining manageable system complexity through modular data selection.
Solution Approach 2:
The patent merges map portions from multiple different map data sources into a single comprehensive map. By combining data from multiple sources, the system achieves superior map detail and accuracy that cannot be obtained from a single source, while the automated selection and blending processes manage the inherent complexity.
2Loss of information
If map data from multiple map data sources is combined, then the map detail and accuracy improve, but the data processing complexity increases
Solution Approach 1:
The patent performs preliminary actions by pre-identifying and selecting the most appropriate map data source for each region portion before actual map generation. The system calculates similarity scores and evaluates data sources in advance, which reduces the processing complexity during runtime and ensures comprehensive information is captured from the start.
Solution Approach 2:
The patent changes parameters by dynamically adjusting the selection criteria and similarity thresholds based on the specific region being mapped. This allows the system to optimize the balance between comprehensiveness and processing complexity for different geographic areas, using more stringent parameters where needed and more relaxed parameters elsewhere.
3Measurement precision
If multiple map portions from different sources are selected, then the regional representation quality improves, but the time to generate the map increases
Solution Approach 1:
The patent performs preliminary selection of map data sources and calculation of similarity scores before actual map rendering. By pre-identifying the best data sources for each region and caching the selection results, the system reduces the time required during actual map generation while maintaining high regional representation quality.
Solution Approach 2:
The patent applies partial action by selecting only the necessary map portions from multiple sources based on similarity scores and regional requirements, rather than processing all available data. This selective approach maintains high representation quality by focusing on the most relevant data while reducing overall processing time.
Data Source
AI summary
Systems, methods, and non-transitory computer-readable media can acquire a request for a map of a particular region. A first set of one or more map portions for representing a first portion of the particular region can be identified based on the particular region. The first set can be associated with a first map data source. A second set of one or more map portions for representing a second portion of the particular region can be identified based on the particular region. The second set can be associated with a second map data source. The map of the particular region can be generated based on a combination of the first set and the second set.