Web Crawler for Machine-Readable Code Identification
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Solution Overview
Problem
Existing systems for identifying machine-readable codes, such as barcodes and QR codes, face inefficiencies when scanning codes that are not recorded in databases, leading to computationally intensive queries and resource usage issues.
Innovation Solution
A web crawler is employed to crawl websites and identify products based on machine-readable codes, determining whether to add a record of the code to the database, thereby reducing the need for intensive queries and optimizing resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a code reader scans a machine-readable code that is not recorded in the database, then the code reader must perform computationally intensive queries to identify the product, but this leads to increased processor cycles, network traffic, memory usage, storage space, and power consumption
Solution Approach 1:
The web crawler performs preliminary actions by proactively scanning websites, extracting machine-readable codes, and adding them to the database before they are needed. This advance population of the database with codes from various web sources ensures that when a code reader scans a code, it is more likely to already be in the database, avoiding computationally intensive queries and reducing processor cycles, network traffic, and power consumption.
2Productivity
If the database is populated with more machine-readable code records, then the system can更快地 identify products, but this increases storage space requirements
Solution Approach 1:
The web crawler implements partial action by selectively crawling only relevant websites and extracting only machine-readable codes that are likely to be scanned by consumers. It doesn't attempt to store every possible code in the universe, but rather focuses on codes from e-commerce sites, product databases, and other relevant sources. This selective approach populates the database with sufficient codes to improve identification speed while avoiding excessive storage requirements.
3Loss of time
If the web crawler extensively crawls websites to collect machine-readable codes, then more codes are added to the database reducing future query needs, but this increases initial network traffic and processing time
Solution Approach 1:
The system performs preliminary web crawling and code collection activities in advance, before actual code reading operations begin. This upfront investment of network traffic and processing time builds a comprehensive database that significantly reduces the time and resources needed for future code identification queries. The one-time preliminary action trades initial energy consumption for long-term time savings.
Solution Approach 2:
The web crawler creates copies of machine-readable codes from various web sources and stores them in the database. Instead of maintaining complex real-time connections to source websites or performing intensive queries during code reading operations, the system copies the essential code data into its database, enabling fast local lookups that minimize future network traffic and processing requirements.
Data Source
AI summary
A method and a system to identify machine-readable codes using a web crawler are provided. Machine-readable codes include, but are not limited to, Universal Product Codes (UPC), quick response (QR) codes, stock-keeping units (SKUs) and international standard book number (ISBN) codes. A web crawler downloads pages from the World Wide Web. A determination module accesses the downloaded pages and identifies a machine-readable code corresponding to a product description included in the downloaded pages. The machine-readable code is included in a downloaded page of the downloaded pages. The determination module further extracts the product description from the downloaded page. A code database stores a record of the machine-readable code and the product description.