Fixed Retail Scanner AI Acceleration for Event-Triggered Image Analysis
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Solution Overview
Problem
Existing retail scanners lack efficient on-board artificial intelligence capabilities for advanced image analysis and data processing, limiting their ability to perform complex tasks such as product recognition and verification.
Innovation Solution
Integration of an on-board AI accelerator module with a system processor and camera modules in a fixed retail scanner, enabling local AI analysis for decoding barcodes and performing machine learning tasks, supplemented by a remote server for enhanced capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If an on-board AI accelerator module is integrated into the fixed retail scanner, then the scanner's ability to perform complex image analysis and data processing tasks locally is improved, but the device complexity increases
Solution Approach 1:
The patent divides the AI processing capability into separate accelerator modules that can be independently integrated into the scanner system. These modules are designed as discrete components that interface with the existing system processor, allowing the complex AI functionality to be added without redesigning the entire system. The segmentation enables modular deployment where different AI accelerator configurations can be selected based on specific application needs.
Solution Approach 2:
The AI accelerator module is designed to perform multiple functions including image analysis, data processing, pattern recognition, and verification tasks. This multi-functional design allows a single added component to address various complex tasks that would otherwise require multiple separate systems, thereby improving productivity without proportionally increasing device complexity.
2Measurement precision
If image data is transmitted continuously to the AI accelerator, then the analysis capability is improved, but the data transmission volume and processing load increase
Solution Approach 1:
The system implements event-triggered image data transmission where the AI accelerator receives image data selectively based on detected events or conditions rather than continuously. This partial action approach ensures that the AI processor receives sufficient data to maintain high analysis capability while avoiding the excessive data transmission that would occur with continuous streaming, thereby reducing the quantity of data processed.
Solution Approach 2:
The patent dynamically adjusts the parameters of image data transmission based on system conditions, event detection, and analysis requirements. By changing parameters such as transmission frequency, data resolution, and trigger conditions, the system optimizes the balance between maintaining high analysis capability and minimizing data transmission volume according to actual operational needs.
Data Source
AI summary
The disclosure includes a fixed retail scanner including a data reader, comprising a main board including one or more processors including a system processor, one or more camera modules, and an artificial intelligence (AI). The system processor is configured to transmit image data received from the one or more camera modules responsive to one or more event triggers detected by the system processor, and wherein the AI accelerator is configured to perform analysis based on an AI engine local to the AI accelerator in response to the event trigger. A remote server may also be operably coupled to the fixed retail scanner through the multi-port network switch, the remote server having a remote AI engine stored therein, wherein the local AI engine within the fixed retail scanner is a simplified AI model relative to the remote AI engine within the remote server.