Worker Attention Monitoring via Eye Tracking and Pupil Analysis
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Solution Overview
Problem
Existing quality assurance systems involving human resources lack real-time monitoring of worker concentration and attention, which is crucial for effective quality control in manufacturing processes.
Innovation Solution
A system that uses cameras and/or lidars to determine a worker's viewing direction and pupil size, dividing the monitor screen into blocks with predefined worker and expectation parameter sets, and comparing these to assess concentration and intervene if deviations exceed permitted limits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time monitoring of worker concentration is implemented using cameras and lidars, then worker attention evaluation capability is improved, but system complexity and cost increase
Solution Approach 1:
The patent replaces subjective human assessment of worker concentration with automated optical measurement systems (cameras and lidars) that objectively track eye position, pupil size, and viewing direction. This substitution enables precise real-time measurement of worker attention states without manual intervention.
Solution Approach 2:
The patent introduces an intermediate processing system that bridges the physical monitoring devices (cameras/lidars) and the quality control database. This intermediary layer processes raw optical data into meaningful concentration metrics, manages data storage, and coordinates interventions, thereby managing system complexity.
2Reliability
If continuous monitoring and intervention systems are implemented, then quality control effectiveness is improved, but loss of time due to processing and intervention increases
Solution Approach 1:
The patent pre-establishes intervention protocols and decision criteria before monitoring begins. Thresholds for concentration deviations, intervention triggers, and response procedures are predetermined and stored in the system, enabling immediate automated responses without deliberation delays when worker attention drops.
Solution Approach 2:
The patent implements a closed-loop feedback system where worker concentration data is continuously monitored, compared against standards, and immediately fed back through interventions (alerts, task adjustments) to maintain quality. This real-time feedback cycle ensures rapid correction of attention deviations while maintaining quality control effectiveness.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables real-time evaluation of worker attention and effectiveness, improving the efficiency of quality control processes by providing immediate feedback and interventions to maintain focus and quality standards.
Implementation Method 1
the worker's presence is perceived mechanically by cameras and/or lidars on the basis of methods known per se, the viewing direction of the worker's eyes and the pupil size of the eyes are determined
Data Source
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AI summary
The invention is a quality assurance procedure using human resources to improve the effectiveness of the quality management system where the viewing direction (1) of a worker representing the human resource at a given place of work in a situation facing a monitor (2) of a given phase of a manufacturing process is displayed. The worker's presence is perceived mechanically by cameras and/or lidars (3) on the basis of methods known per se, the viewing direction (1) of the worker's eyes (4) and the pupil size of the eyes (4) are determined and at given intervals time stamps are generated and stored containing this information. The system (7) includes at least one server (5) connected informatically to the monitor (2). The screen of the monitor (2) is devided into parts containing smaller blocks (6) according to a predefined pattern. Worker parameter sets are assigned to each block (6), where the worker parameter sets include at least the viewing direction (1) of the eyes (4), their time duration related to a given block (6) and pupil size. Expectation parameter sets are also assigned to each block (6), which include at least parameters corresponding to the worker parameter sets. The worker parameter sets and the expectation parameter sets related to each block (6) are compared one by block (6) by an application running on at least one server (5) with a given set of criteria, which consists the maximum permitted deviation of the worker and the expectation parameter sets and in case of exceeding the maximum permitted deviation an intervention is carried out by block (6) on the monitor (2) and in the system (7).