Beacon Disambiguation for User Identification
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Solution Overview
Problem
Automated compliance systems in healthcare environments face challenges in distinguishing between multiple users without increasing user workload, often relying on costly and inaccurate triangulation methods, which hinder effective hand-washing compliance monitoring.
Innovation Solution
A beacon disambiguation system that uses beacons with communication and sensor units to identify active users by processing signal IDs and strengths, disambiguating users based on probability thresholds, and correlating beacon sensor data with station sensor data to accurately determine user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If triangulation methods are used to distinguish multiple users, then user identification capability is improved, but system cost and complexity increase significantly
Solution Approach 1:
The patent replaces complex mechanical triangulation systems with sensor-based detection systems. Instead of using multiple antennas and complex signal processing for triangulation, the system uses sensors (cameras, microphones, motion detectors) to detect user presence and attributes, significantly reducing system complexity while maintaining identification accuracy
Solution Approach 2:
The patent uses sensor data copies (images, audio recordings, motion patterns) to identify and distinguish users. By analyzing copies of user interactions captured by sensors rather than requiring direct physical measurement systems, the patent achieves accurate user identification with simpler hardware
2Measurement precision
If triangulation methods are used to distinguish multiple users, then user identification capability is improved, but power consumption increases
Solution Approach 1:
The patent replaces power-intensive triangulation radio frequency systems with lower-power sensor systems. Sensors such as cameras and motion detectors consume significantly less power than the multiple high-gain antennas and signal processing equipment required for accurate triangulation, thereby reducing overall system power consumption
3Difficulty of detecting and measuring
If automated systems sense multiple users but cannot distinguish active users, then user presence detection is improved, but user interaction identification accuracy deteriorates
Solution Approach 1:
The patent segments user detection into multiple independent sensing modalities (visual sensors for presence, motion sensors for activity level, audio sensors for interaction). By dividing the detection task across different sensor types and analyzing their combined output, the system can distinguish between mere presence and active interaction with higher accuracy
Solution Approach 2:
The patent uses dynamic analysis of sensor data to identify active users. By monitoring changes in motion patterns, interaction frequency, and sensor response over time, the system dynamically identifies which users are actively interacting versus merely present, improving identification accuracy
Data Source
AI summary
A method and system can include: a station including a station communication unit, a station control unit, and a station storage unit; receiving transmissions of signals containing messages from beacons; detecting IDs from the messages; detecting a received strength of the signals; adding the IDs to a list; identifying one of the IDs as corresponding to an active user based on the list only having a single one of the IDs or based on a probability of the IDs being above a threshold, the active user being a user interfacing with the station; and disambiguating the IDs on the list based on the probability of the IDs being below the threshold.