Point of Interest Database Maintenance via Time-Dependent Confidence Decay
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Solution Overview
Problem
Existing systems for maintaining databases of points of interest, such as speed limit enforcement devices, face challenges in ensuring the accuracy and freshness of data due to the reliance on user reports, often resulting in false positives and outdated information.
Innovation Solution
A method and system that assign a time-dependent confidence value to each point of interest, which adjusts based on user reports and decays over time, determining when data is no longer reliable and should be removed from alerts, ensuring only accurate information is provided to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If user reports are used to maintain database accuracy, then data freshness is improved, but false positives and outdated information increase
Solution Approach 1:
The patent applies dynamics by making the confidence value time-dependent and continuously adjusting it based on both user reports and elapsed time. The confidence value is not static but evolves dynamically, increasing with positive reports and decreasing with negative reports or passage of time, thereby adaptively managing data reliability.
Solution Approach 2:
The system implements feedback mechanisms where user reports (positive or negative) directly influence the confidence value of database entries. This feedback loop allows the system to learn from user experiences and continuously improve data accuracy by adjusting confidence values based on reported accuracy, thereby reducing false positives.
2Reliability
If all points of interest are continuously monitored, then data freshness is improved, but system complexity and resource consumption increase
Solution Approach 1:
The patent applies local quality by differentiating the monitoring intensity and confidence decay rates for different types of points of interest. Instead of uniformly monitoring all entries, the system assigns specific confidence decay functions and thresholds tailored to each POI type, thereby reducing overall system complexity while maintaining data freshness where most needed.
Solution Approach 2:
The system changes parameters by introducing time-dependent confidence values that automatically decay over time and can be adjusted based on POI characteristics. This parameter change approach allows the system to prioritize monitoring of high-confidence or time-sensitive entries while reducing attention to stable, low-risk entries, thereby managing system complexity.
3Reliability
If confidence values decay over time, then outdated information is reduced, but false negatives increase as valid information is discarded
Solution Approach 1:
The system performs preliminary action by proactively managing confidence values before information becomes completely outdated. The time-dependent decay function predictively reduces confidence for aging entries, allowing the system to prioritize updates or removals before false positives occur, thereby maintaining freshness without abrupt information loss.
Solution Approach 2:
The feedback mechanism allows user reports to counteract or accelerate confidence decay. When users report positive experiences with older entries, the confidence value can be increased despite time passage, preventing valid information from being discarded. This feedback loop ensures that time-dependent decay does not automatically discard valid information that remains accurate.
Data Source
AI summary
A method of processing data at a server 302 for maintenance of a database 516 of points of interest, such as speed limit enforcement devices. Each of the devices represented in the database has at least one attribute and a confidence value indicative of the accuracy of the at least one attribute associated therewith. The confidence value is time dependent and varies according to a predefined decay function. A report 500 relating to an attribute of a speed limit enforcement device is received at the server 302 from a mobile device 200. The confidence value associated with the speed limit enforcement device is adjusted in accordance with the received report, and information relating to the speed limit enforcement device 520, 522 is selectively transmitted to the or another mobile device 200 based on the confidence value.