Alphanumeric Encoding for URI Payload Data in QR Codes
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Solution Overview
Problem
Current encoding techniques for barcodes, such as QR codes, are inefficient due to varying character encodings, leading to interoperability issues and suboptimal use of space, especially when encoding URIs, which affects readability and error correction.
Innovation Solution
Implementing custom alphanumeric encoding methods like BASE36, BASE37, BASE38-QR-URI-UNRESERVED, BASE42, BASE45, Base64, Base66, Base183, and Base191 to efficiently convert URI-oriented payload data into machine-readable codes that are more compatible across systems, reducing the physical space required and enhancing error correction capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If standard character encodings are used for barcode-URI creation, then interoperability is achieved, but encoding efficiency is poor and physical space is wasted
Solution Approach 1:
The patent changes the encoding parameter from standard character encodings to custom base-N encodings (where N > 64) to improve encoding efficiency. By increasing the base of the encoding system, more characters can be represented per unit space, thereby reducing the physical size of barcodes while maintaining interoperability through standardized conversion processes.
2Length of stationary object
If larger base encodings are used, then string size is reduced, but compatibility with existing systems becomes problematic
Solution Approach 1:
The patent introduces an intermediary conversion process that translates custom base-N encoded data into standard formats that existing systems can process. This mediator layer allows the system to benefit from the compactness of high-base encodings while maintaining compatibility with legacy systems that expect standard character encodings, thus resolving the compatibility issue.
3Reliability
If more physical space is allocated for QR codes, then readability is improved, but space efficiency is reduced
Solution Approach 1:
The patent changes the encoding density parameter by using higher base encodings, which pack more information into fewer characters. This allows QR codes to maintain or improve readability while occupying less physical space, effectively reversing the traditional trade-off by increasing information density rather than expanding code size.
4Reliability
If error correction is enhanced, then reliability is improved, but QR version (size) must increase
Solution Approach 1:
The patent changes the fundamental encoding parameter to use higher base-N systems, which inherently require fewer characters to represent the same amount of data. This reduction in character count allows more of the QR code capacity to be allocated to error correction mechanisms without increasing the overall QR version or physical size, thus improving reliability within the same space constraints.
Data Source
AI summary
Computer-implemented methods and systems for efficient alphanumeric encoding for arbitrary payload data are disclosed. The computer-implemented method, performed by a server system, includes accessing URI-oriented payload data. The method further includes converting the URI-oriented payload data into an alphanumeric data type based, at least in part, on an alphanumeric encoding method. The alphanumeric encoding method may be one of BASE36, BASE37, BASE38-QR-URI-UNRESERVED, BASE42, BASE45, Base64, Base66, Base183, and Base191. The method further includes generating a machine-readable code based, at least in part, on the converted URI-oriented payload data.