Predicted Delivery Pins Using Transporter Trajectory Data
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Solution Overview
Problem
Existing navigation systems face challenges in accurately determining and updating location pins for delivery and retrieval points, particularly in densely populated areas like shopping malls, apartment complexes, and office complexes, leading to inefficiencies and increased support requests due to inaccurate pin locations.
Innovation Solution
A system that utilizes location measurements from transporter devices to automatically correct pin locations by determining a central value, such as a median or mean, based on actual retrieval and delivery points, and updates these locations in a database to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pin locations are manually set or use default positions, then device complexity is reduced, but location accuracy deteriorates leading to navigation inefficiency
Solution Approach 1:
The system automatically determines pin locations by analyzing transporter device trajectories and calculating central values without manual intervention. The database is self-updating based on collected location data, eliminating the need for manual pin setting while maintaining high accuracy
Solution Approach 2:
The system continuously collects location data from transporter devices, compares it with existing pin locations, and updates the database when improvements are detected. This feedback loop ensures pin locations progressively improve in accuracy based on actual delivery patterns
2Measurement precision
If pin locations are frequently updated based on new data, then location accuracy is improved, but data processing time and computational resources increase
Solution Approach 1:
The system performs partial updates by only recalculating pin locations when new data indicates an improvement is possible. It compares central values against existing pins and only updates when the new location provides better accuracy, avoiding unnecessary processing
Solution Approach 2:
The system pre-calculates central values from collected trajectory data before committing updates to the database. By preparing updates in advance and validating them against improvement criteria, it minimizes processing overhead during active operations
3Productivity
If accurate pin locations are maintained through manual correction, then navigation efficiency is improved, but labor requirements and operational costs increase
Solution Approach 1:
The system automatically maintains accurate pin locations through self-learning from transporter trajectories. No manual correction is needed as the system autonomously identifies and implements location improvements, eliminating labor requirements while maintaining high navigation efficiency
Solution Approach 2:
The patent replaces manual mechanical processes of pin location correction with automated computational analysis of trajectory data. Algorithms calculate central values and determine optimal pin locations, substituting human effort with automated data processing
4Speed
If pin locations are determined from limited data points, then system responsiveness is improved, but location accuracy deteriorates
Solution Approach 1:
The system performs preliminary calculations of central values as data points are collected, preparing potential pin location updates in advance. When sufficient data is available, it validates these pre-calculated values against improvement criteria and commits updates efficiently
Solution Approach 2:
The system dynamically adjusts its data collection and processing based on the accumulation of trajectory points. It continuously refines central value calculations as more data becomes available, allowing pin locations to evolve from initial estimates to highly accurate positions over time
Data Source
AI summary
Techniques are provided for determining and updating locations in databases for providing to transport user devices to facilitate picking up (retrieving) an item and delivery. Location points (e.g., for retrieval or delivery) can be measured by transporter devices when an item is retrieved, and a central value can be determined from the measured location points. The central value can be used to update a pin location in a database for a destination, e.g., when more paths by the transport user devices cross a boundary (geofence) around then central value than a boundary around an existing pin location.