Charge Station Location Merging for Duplicate Data Removal
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Solution Overview
Problem
Existing electric vehicle charging station location applications often suffer from redundancies and inaccuracies, making it difficult for drivers to find nearby charging stations efficiently.
Innovation Solution
A system and method that collect and merge charging station location data by matching it with operators and providers, using geohash or radius-based merging to eliminate redundancies and provide a reduced set of accurate locations to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If charge station location applications use crowd-sourced data from multiple sources, then the quantity of charging locations increases, but data redundancies and conflicts increase making it difficult to locate charging stations
Solution Approach 1:
The patent merges charge station location data from multiple sources (crowd-sourced data, operator-provided data, third-party data) by matching locations within a predetermined distance threshold. Duplicate or redundant locations are consolidated into single entries, eliminating conflicts while preserving comprehensive coverage from all data sources.
Solution Approach 2:
The patent introduces an intermediary processing system that acts as a mediator between multiple data sources and the user. This intermediary matches and merges location data from various providers, operators, and crowd-sourced sources before presenting the consolidated information to users, simplifying the complexity of handling multiple raw data sources.
2Adaptability or versatility
If charge station location applications include data from multiple providers and operators, then the coverage of charging locations improves, but data inaccuracies and conflicts increase
Solution Approach 1:
The patent combines location data from multiple providers, operators, and crowd-sourced sources by matching locations within a predetermined distance. This merging process consolidates redundant entries and resolves conflicts through systematic comparison, maintaining comprehensive coverage while improving data reliability through verification against multiple sources.
Solution Approach 2:
The patent implements a feedback mechanism where location data is continuously matched, merged, and verified against existing databases. The system compares new data with established locations, identifies discrepancies, and resolves conflicts through iterative matching processes, improving overall data accuracy through continuous validation.
3Loss of information
If charge station location applications process raw data from multiple sources, then the completeness of charging location information improves, but the time required to locate charging stations increases
Solution Approach 1:
The patent performs preliminary matching and merging of charge station location data in advance, before users need to locate charging stations. By pre-processing and consolidating data from multiple sources ahead of time, the system reduces the time required for users to find charging locations while maintaining complete and accurate information.
Solution Approach 2:
The patent merges location data from multiple sources through systematic matching within predetermined distances, consolidating comprehensive information into a unified format. This merging process organizes complete data from various providers into a streamlined structure that can be quickly queried and presented to users, reducing search time while maintaining information completeness.
Data Source
AI summary
The disclosure is generally directed to a method and system for charge station management including collecting data related to a plurality of charge stations, the data identifying location data, an operator, and a data provider for each of the plurality of charge stations; collating the data to match the location data with the operators of each of the plurality of charge stations; and sequentially merging the location data based on a set of criteria including the data from each of the data providers within a predetermined configurable radius defining a perimeter surrounding each data provider-identified location. Collecting raw data includes receiving the raw data from crowd-sourced data providers; receiving the raw data from the operators of the plurality of charge stations; and organizing the raw data as batch data. Sequentially merging includes setting the predetermined configurable radius about a data provider as a pivot point for a predetermined circumference; and merging location data within the predetermined circumference to remove redundant locations based on the set of criteria, including criteria identifying a same operator within the predetermined circumference.