Wearable Proximity Sensor Using Multi-Source Data Fusion
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Solution Overview
Problem
Current systems for detecting the proximity of articles with specific characteristics are limited in their accuracy and ability to select reliable information sources, often failing to provide timely and precise alerts for users who need to avoid certain substances due to allergies, nutritional, or religious reasons.
Innovation Solution
A wearable device equipped with a processor and multiple sensors that detect characteristic information from various sources, such as RFID tags, labels, and physical shapes, compares this information with predefined data to generate alarms when a match or mismatch is detected, improving detection accuracy and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors and information sources are used to detect article characteristics, then detection accuracy is improved, but device complexity increases
Solution Approach 1:
The system segments the detection task by using multiple specialized sensors (RFID reader, barcode scanner, camera, weight sensor, moisture sensor, temperature sensor) to detect different types of information sources separately. Each sensor is optimized for specific detection tasks, and the processor integrates these segmented detection results to achieve comprehensive and accurate article identification while maintaining manageable device complexity through modular architecture.
2Reliability
If multiple information sources are evaluated and selected, then reliability of detection is improved, but processing time increases
Solution Approach 1:
The processor pre-establishes selection criteria and confidence thresholds for evaluating information sources before detection begins. When articles are detected, the system applies these pre-defined rules to quickly evaluate and select the most reliable information source without requiring complex real-time analysis, thus improving detection reliability while minimizing processing time delays.
Solution Approach 2:
The system implements feedback mechanisms where detection results from multiple information sources are continuously evaluated and compared. The processor uses feedback from initial detections to refine selection criteria and adjust evaluation parameters, enabling rapid convergence on the most reliable information source while maintaining high detection reliability through iterative optimization.
3Measurement precision
If the system compares detected information with predefined characteristic information, then accuracy of avoiding harmful articles is improved, but device complexity increases
Solution Approach 1:
The system transitions from single-dimension detection to multi-dimensional verification by comparing detected article information across multiple dimensions (RFID data, barcode information, visual characteristics, weight, moisture content, temperature) against corresponding predefined characteristics. This dimensional expansion enables comprehensive accuracy verification while managing complexity through structured comparison frameworks and hierarchical evaluation protocols.
Data Source
AI summary
A condition-responsive wearable device for sensing and indicating proximity of an article with a specific characteristic includes a processor and a sensor. The sensor is configured to detect an article with two or more information sources within a predetermined distance of the sensor. The information sources contain characteristic information of the article. The wearable device also includes a memory storing instructions that, when executed by the processor, cause the processor to receive predefined characteristic information, select detected characteristic information from at least two of the information sources to compare with the predefined characteristic information, and compare the selected detected characteristic information with the predefined characteristic information. The wearable device includes an indicator configured to generate an alarm in response to detecting a match between the selected detected characteristic information and the predefined characteristic information.