Contamination Likelihood Assessment Using Crowd-Adjusted RSSI
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing contamination likelihood assessment methods based on Received Signal Strength Indication (RSSI) are not accurate enough to determine proximity below 2 meters, leading to approximate results in tracing suspected cases during pandemics.
Innovation Solution
A method that evaluates contamination likelihood by determining exposure duration and adjusting RSSI values and thresholds based on crowd attributes such as diversity and density, which affect the assessment of distance between individuals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If RSSI-based distance calculation is used to determine proximity, then the method is simple and easy to implement, but the measurement precision is insufficient to accurately distinguish people below 2 meters
Solution Approach 1:
The patent changes the parameter used for distance assessment from raw RSSI values to signal propagation models that account for environmental factors. By introducing crowd density and diversity as modifying parameters, the system adjusts the effective distance calculation to achieve more accurate proximity detection below 2 meters while maintaining implementation simplicity.
Solution Approach 2:
The patent introduces crowd attributes (density and diversity) as intermediary factors that mediate between the raw RSSI measurement and the final distance assessment. These intermediary parameters allow the system to compensate for environmental variations without requiring complex direct measurement methods, thus improving precision while keeping the overall approach simple.
2Reliability
If crowd attributes are introduced to adjust RSSI values, then the contamination likelihood assessment accuracy is improved, but the device complexity increases
Solution Approach 1:
The patent modifies the assessment parameters by incorporating crowd density and diversity as adjusting factors. These parameter changes enable the system to account for environmental variations in signal propagation, thereby improving the reliability of contamination likelihood assessment without requiring fundamentally new measurement technologies.
Solution Approach 2:
The patent introduces dynamic adjustment of RSSI values based on real-time crowd conditions. By making the assessment parameters adaptive to changing environmental factors (crowd density and diversity), the system improves accuracy while maintaining a relatively simple computational approach that adjusts existing parameters rather than creating entirely new assessment mechanisms.
Data Source
Figure 1
Figure 2~3
Figure 4~6
AI summary
The invention relates to a method (200) for the evaluation of a contamination likelihood for a person of interest (POI), carrying a user device (502) configured to detect signals comprising: - determining (202) a duration, called exposure duration, comprising at least one time window(s) (108), of a predetermined length, during which a user device (502) of said POI detected at least one contaminated person's signal, and - for each time window (108), assessing (214) a contamination likelihood for said POI according to: ▪ a received signal strength indication (RSSI) value relative to the distance between said contaminated person and the POI, and ▪ an RSSI threshold value, representing a contamination distance below which contamination is possible; wherein said method (200) comprises using at least one crowd attribute characterizing the crowd around said POI during at least one of said time window(s), to adjust the received RSSI value and/or the RSSI threshold value. The invention also relates to a computer program and a system implementing such a method.