Digital Map Accuracy via Automated Discrepancy Detection
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Solution Overview
Problem
Maintaining accurate digital maps of physical spaces, such as retail stores, is challenging due to inefficiencies and human errors in updating changes, leading to discrepancies between the physical space and its digital representation.
Innovation Solution
Automated and semi-automated techniques are employed to identify and correct discrepancies between digital maps and physical spaces using location information from users and devices, aggregating data to update map coordinates and fixture layouts without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual updating processes are used to maintain digital maps, then human control and decision-making are preserved, but efficiency is reduced and human errors occur
Solution Approach 1:
The system automatically detects changes in physical space using sensors and devices, and self-updates the digital map without requiring manual human intervention. The map maintenance system autonomously compares detected changes with existing map data, identifies discrepancies, and updates the map accordingly, allowing the system to service itself.
Solution Approach 2:
The patent replaces manual mechanical updating processes with automated electronic detection and update mechanisms. Sensors, mobile devices, and computing systems electronically detect physical changes and automatically update digital map data, substituting human manual operations with automated technological systems.
2Measurement precision
If frequent manual updates are performed to maintain map accuracy, then map accuracy is improved, but time consumption and operational complexity increase
Solution Approach 1:
The system continuously and automatically monitors physical space changes through sensors and devices, maintaining constant update capability without interruption. The automated detection and update process operates continuously, eliminating gaps between updates that would occur with manual processes.
Solution Approach 2:
The system performs preliminary automatic detection of changes in physical space before manual update processes would be needed. By continuously monitoring and pre-identifying changes, the system is ready to update maps immediately when discrepancies are detected, eliminating delays associated with manual discovery and initiation of updates.
3Speed
If automated detection systems are deployed to identify discrepancies, then update speed is improved, but system complexity increases
Solution Approach 1:
The system uses multi-functional sensors and mobile devices that can detect various types of changes (fixtures, layout, objects) and perform multiple operations (detection, data collection, discrepancy identification). These universal components handle diverse detection tasks, reducing the need for specialized dedicated devices for each function.
Solution Approach 2:
The patent introduces a map maintenance system as an intermediary layer between detection devices and the digital map. This intermediary automatically processes detected changes, compares them with existing map data, identifies discrepancies, and manages updates, simplifying the overall system architecture by centralizing the coordination function.
Data Source
AI summary
In some implementations, a method performed by data processing apparatuses includes receiving stored map data corresponding to a digital map, identifying a discrepancy between the digital map and a physical space which the digital map represents, updating the digital map to correct the identified discrepancy, storing the updated digital map, and optionally providing the updated digital may for presentation on a device display.