Workstation assignment
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Solution Overview
Problem
The spread of diseases like COVID-19 in workplaces poses challenges due to asymptomatic carriers and varying susceptibility among employees, necessitating effective workstation assignment strategies to mitigate risk.
Innovation Solution
A system and method that utilize a processor to generate user profiles and workstation characteristics models, assigning users to workstations based on risk levels and airflow patterns to minimize disease transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If employees are assigned to workstations without considering risk levels and airflow patterns, then workstation assignment is simple and quick, but the risk of disease spread increases
Solution Approach 1:
The system performs preliminary actions by generating user profiles with risk levels and creating workstation characteristics models with airflow patterns before assignment. This pre-processing of data allows the system to make informed assignments that reduce disease risk while maintaining operational efficiency during the actual assignment process.
Solution Approach 2:
The processor acts as an intermediary that processes user profiles and workstation characteristics to generate optimized assignments. This intermediary processing layer analyzes multiple factors (risk levels, airflow patterns, susceptibility) and translates them into actionable assignment decisions, resolving the contradiction between simplicity and effectiveness.
2Reliability
If workstation assignment considers multiple user characteristics and risk factors, then disease transmission risk is reduced, but assignment processing time increases
Solution Approach 1:
User profiles with risk levels and workstation characteristics models are generated in advance, storing pre-processed information about user susceptibility and airflow patterns. This preliminary preparation allows the assignment process to quickly retrieve and compare pre-analyzed data rather than performing complex calculations in real-time, thus reducing processing time while maintaining reliability.
Solution Approach 2:
The system transforms complex multi-factor risk assessment into simplified risk level parameters that can be efficiently compared and processed. By converting multiple user characteristics into standardized risk levels and airflow patterns into comparable metrics, the system enables fast processing while preserving the reliability benefits of comprehensive analysis.
3Measurement precision
If comprehensive user profiles and workstation models are generated, then assignment accuracy is improved, but computational resources required increase
Solution Approach 1:
The system segments the comprehensive assessment into separate components: user profiles containing user-specific risk factors and workstation characteristics models containing environment-specific airflow patterns. This segmentation allows the processor to generate and store these models independently, then efficiently combine them during assignment without requiring excessive computational resources for real-time analysis of all factors simultaneously.
Solution Approach 2:
The system creates simplified representations (profiles and models) that copy essential characteristics of users and workstations without replicating all underlying data. These compressed models retain the necessary information for accurate assignment while requiring significantly less computational resources to process and store than complete user data sets and detailed workstation specifications.
Data Source
AI summary
A processor may generate a workstation characteristics model of a workspace. A processor may generate respective user profiles for each of one or more users. Each of the respective user profiles may include user data associated with a respective user. A processor may assign, based on the respective user profiles, a respective risk level to each of the respective user profiles. A processor may compare each of the respective risk levels to a risk threshold level. A processor may apply a user characteristic model. A user characteristic model may be based on each of the respective risk levels and the workstation characteristics model. A processor may assign each of the one or more users to respective workstations based on the user characteristic model.