Metadata Mapping Calculator for Weather-Based Distancing Forecasts
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Solution Overview
Problem
Existing predictive models for social distancing and environmental safety actions, particularly in response to airborne pathogens like COVID-19, rely heavily on meteorological data and complex fluid dynamic modeling, which are costly, site-specific, and lack universal applicability, failing to provide accurate, user-specific recommendations for diverse environmental conditions.
Innovation Solution
A simple scoring equation based on a multifactor artificial neural network (ANN) that incorporates meteorological metadata, user-specific susceptibility, and environmental factors to forecast spatiotemporal safety actions, using open API data for meteorological inputs and user feedback to improve model accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex fluid dynamic modeling is used for predictive modeling, then measurement precision and reliability are improved, but device complexity and cost increase
Solution Approach 1:
The patent extracts the essential predictive capability from complex fluid dynamic modeling by identifying key meteorological parameters (temperature, humidity, wind speed, wind direction) that drive pathogen transmission. This allows the system to achieve accurate forecasts using simplified equations rather than full CFD modeling, resolving the contradiction between precision and complexity.
Solution Approach 2:
The patent changes the modeling approach from complex fluid dynamic parameters to simplified meteorological parameters. By transforming the problem into a parameter-based prediction system using readily available weather data, the model achieves comparable accuracy with significantly reduced computational complexity and cost.
2Reliability
If site-specific factors are incorporated into the model, then reliability for specific locations is improved, but adaptability to different locations decreases
Solution Approach 1:
The patent creates a universal forecasting model that can be applied across different locations and conditions by using general meteorological parameters and transfer functions. The model maintains reliability for site-specific predictions while achieving broad adaptability through its reliance on universally available weather data and generalized transmission physics, eliminating the need for location-specific calibration.
3Adaptability or versatility
If meteorological data and environmental factors are integrated, then adaptability to different environmental conditions is improved, but device complexity increases
Solution Approach 1:
The patent segments the environmental factors into distinct meteorological parameters (temperature, humidity, wind speed, wind direction) and incorporates them as separate inputs to the prediction model. This segmentation allows the system to handle multiple environmental conditions independently through simple transfer functions, achieving high environmental adaptability without increasing overall model complexity.
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
Provides accurate, user-specific, and cost-effective forecasting of physical distancing and safety actions for various environmental hazards, adaptable to different locations and conditions, reducing reliance on costly and site-specific monitoring systems.
Implementation Method 1
The model currently bases the calculations on mass transfer and air transport of Particulate Matter (PM) that makes up transmissible airborne particles
Implementation Method 2
mass transfer and air transport of Particulate Matter (PM) that makes up transmissible airborne particles
Data Source
AI summary
Predictive modelling was demonstrated in software forecasting site-specific, user-specific recommendations for levels of physical distancing from novel airborne pathogen sources, and can forecast corrective safety actions mitigating other environmental hazards, and be combined with other environmental predictive safety models for economic full safety software package, with recommended corrective actions including social distances, safety actions, and control of the source, receptor or path in between, early recommendations and distancing found prevent future novel pandemics (Kaur 2021), and main initial calculation with highest degree of accuracy being social distancing and appropriate actions to protect against the early pandemic identification and preliminary transmissibility characterization studies, because the main use is outdoor calculation of safety actions since the modelling currently relies on meteorological data, but this invention would likewise predict mitigation actions and quantities anytime air or other environmental media behaves similarly.