Barcode Reader Data Mining via IoT Middleware
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Solution Overview
Problem
In industrial automation, especially in Smart Factory scenarios, data mining tools for sensor devices like barcode readers are often Cloud-based, making them inaccessible due to complexity, bandwidth, data security, and cost issues, limiting their effectiveness in real-time data analysis and visualization across various devices.
Innovation Solution
Embedding data mining algorithms and visualization tools within IoT middleware platforms at the end-user side, enabling on-field data acquisition, pattern extraction, and formatting directly from devices like barcode readers, which can then be transmitted and visualized remotely through a local network, avoiding the need for Cloud-based solutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data mining tools are deployed Cloud-based, then data analysis capabilities are improved, but system complexity and cost increase
Solution Approach 1:
The patent extracts the data mining functionality from the cloud environment and embeds it directly into the barcode reader device. This allows the device to perform advanced analytics locally without requiring complex cloud infrastructure, thereby improving data analysis capability while reducing system complexity and cost.
Solution Approach 2:
The barcode reader device is equipped with embedded data mining algorithms that enable it to perform data analysis independently without relying on external cloud services. This self-service capability allows the device to process and analyze data locally, eliminating the need for complex cloud-based data mining infrastructure.
2Productivity
If data mining tools are deployed Cloud-based, then data analysis capabilities are improved, but bandwidth requirements increase
Solution Approach 1:
The patent extracts the data mining processing from the cloud and places it locally in the barcode reader. This extraction eliminates the need to transmit large volumes of raw data to the cloud for analysis, significantly reducing bandwidth consumption while maintaining advanced data analysis capabilities.
Solution Approach 2:
The device performs data mining analysis locally before any potential data transmission occurs. This preliminary action allows the device to process and filter data on-site, reducing the quantity of data that needs to be transmitted over the network and thereby reducing bandwidth requirements.
3Productivity
If data mining tools are deployed Cloud-based, then advanced analytics are achieved, but data security risks increase
Solution Approach 1:
The patent extracts sensitive data processing from the cloud environment and performs it locally on the barcode reader device. This extraction ensures that sensitive data never leaves the secure device environment, eliminating data security risks associated with cloud transmission and storage while maintaining advanced analytics capability.
Solution Approach 2:
The embedded data mining algorithms act as an intermediary that processes data locally within the secure device boundary. This intermediary approach allows advanced analytics to be performed without requiring data to be transmitted to external cloud services, thereby maintaining data security while achieving sophisticated analysis.
4Loss of time
If data mining algorithms are embedded in field devices, then real-time analysis is improved, but device complexity increases
Solution Approach 1:
The patent merges the data mining algorithms with the barcode reader's existing processing architecture. By integrating these analytics capabilities into the device's existing structure rather than adding separate complex systems, the device achieves real-time processing capability while minimizing the increase in overall device complexity.
Data Source
AI summary
Systems, methods, and computer-readable storage media are provided for acquiring field device data (e.g., imaging data such as barcode readings), extracting patterns from the field device data, and formatting the extracted patterns—all directly from field devices (e.g., barcode readers) embedded with these capabilities. The information conveyed by the patterns extracted at the devices embedded with these capabilities may be synthesized and shown in a graphical way to end-users, for instance, by exploiting IoT middleware platform services available at end-user side. Accordingly, systems, methods and computer-readable storage media in accordance with embodiments hereof further provide a customized visualization (e.g., a widget) aimed to make the formatted patterns available in an easy, intuitive and effective way.