Handwriting Recognition for Virtualized Mail Services
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current mail management services face increased costs and decreased competitiveness due to the need for human review of handwritten address information on physical mail, which can be time-consuming and inefficient.
Innovation Solution
A computerized method for dynamic location-based virtualized mail services that uses handwriting recognition (HWR) and machine learning to automatically identify and process handwritten information on physical mail, integrating with GPS-based location services to optimize mail delivery and management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human review is used to process handwritten address information, then accuracy of mail delivery is improved, but processing time and cost increase
Solution Approach 1:
The patent replaces the mechanical system of human visual inspection and manual data entry with an optical character recognition (OCR) system that uses image processing algorithms to automatically recognize and extract handwritten address information from mail envelopes, thereby eliminating the time-consuming manual review process while maintaining delivery accuracy
Solution Approach 2:
The OCR system enables the mail processing system to automatically perform the recognition and extraction of address information without human intervention, making the system self-sufficient in handling handwritten mail sorting and routing tasks
2Measurement precision
If human review is used to process handwritten address information, then delivery accuracy is improved, but operational cost increases
Solution Approach 1:
The patent substitutes expensive human labor with an automated OCR-based image recognition system that can process large volumes of handwritten mail at a fraction of the cost, while the system's ability to learn from training data ensures maintained delivery accuracy
Solution Approach 2:
The system creates digital copies of handwritten address information through optical scanning and converts them into machine-readable text data, eliminating the need for physical handling and manual transcription by human workers
3Productivity
If automated processing is implemented, then processing speed is improved, but recognition accuracy deteriorates
Solution Approach 1:
The patent implements a preliminary training phase where the OCR system is trained on datasets containing various handwriting styles, formats, and conditions before deployment. This pre-training ensures that when the system processes actual mail at high speed, it maintains high recognition accuracy by having already learned from diverse examples
Solution Approach 2:
The system incorporates feedback mechanisms where recognition results are continuously evaluated and used to refine the model's performance, allowing the automated processing system to improve its accuracy over time while maintaining high processing speeds
Data Source
AI summary
In one aspect, a computerized method useful for dynamic location-based virtualized mail services includes the step of determining an identity of a user receiving a physical mail. The method includes the step of determining a location of the user. The method includes the step of determining a set of delivery locations within a specified distance of the user's current location. The method includes the step of communicating, via an electronic message, the delivery location to the user's mobile device.