Activity-Based Map Job Validation System
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Solution Overview
Problem
Service providers face challenges in validating crowd-sourced information for map databases, as traditional methods are cumbersome and unreliable, leading to outdated or erroneous data.
Innovation Solution
A system is introduced that processes map error data to generate map jobs, determines suitable devices for error resolution based on activity context, and transmits these jobs to devices for validation, ensuring accurate and efficient data updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional methods are used to validate crowd-sourced information, then the process is simpler, but the validation is cumbersome and unreliable
Solution Approach 1:
The patent introduces a validation platform as an intermediary system between crowd-sourced users and map database. This platform coordinates validation jobs, manages user devices, and ensures reliable validation through structured processes, thereby improving validation reliability while managing system complexity through modular architecture
Solution Approach 2:
The patent implements accelerated validation by actively recruiting and coordinating multiple user devices to validate map errors simultaneously. This parallel processing approach accelerates the validation process and improves reliability through multiple validation instances, rather than relying on slow sequential traditional methods
2Productivity
If manual verification methods are used, then the system is simpler, but the update speed is slower
Solution Approach 1:
The patent implements preliminary action by proactively identifying map errors through crowd-sourced reports and pre-processing validation jobs before they are assigned to users. This preparation work includes filtering, prioritizing, and organizing validation tasks, enabling faster processing when users participate and reducing overall validation time
Solution Approach 2:
The patent ensures continuous validation by maintaining an active pool of user devices that can immediately begin validation tasks when assigned. The system continuously monitors for new errors, assigns jobs without interruption, and processes validations in parallel, eliminating idle time and maintaining continuous productive action throughout the validation process
3Measurement precision
If comprehensive error checking is performed, then data accuracy improves, but resource consumption increases
Solution Approach 1:
The patent applies local quality by focusing validation resources on specific areas where errors have been reported rather than performing comprehensive checks across the entire map database. The system assigns validation jobs to users based on their location and the specific error context, concentrating processing resources only where needed to maintain data accuracy while reducing overall resource consumption
Solution Approach 2:
The patent implements partial action by performing validation only on specific map elements that have been flagged as potentially erroneous through crowd-sourced reports. Rather than validating all map data comprehensively, the system selectively validates only the portions that require verification, achieving necessary data accuracy with reduced processing resources
Data Source
AI summary
An approach is provided for validating crowd-sourced information. The approach includes processing and/or facilitating a processing of map error data to generate at least one map job and at least one activity context associated with the at least one map job, the map error data, or a combination thereof. The approach also includes determining one or more devices based, at least in part, on the at least one activity context. Further, the approach includes causing, at least in part, a transmission of the at least one map job to the one or more devices for resolving one or more map errors indicated in the at least one map job, the map error data, or a combination thereof.