CO2 Concentration Estimation Using Virtual Space Simulation
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Solution Overview
Problem
Existing methods fail to accurately estimate carbon dioxide concentration distribution in indoor spaces where people are present, as they do not account for the impact of human presence on carbon dioxide concentration patterns.
Innovation Solution
An estimation method and system that utilizes simulations based on three-dimensional space information, environmental data, and person location to derive and approximate carbon dioxide concentration distributions, incorporating location information to estimate actual concentrations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If simulations are performed to derive carbon dioxide concentration distribution considering human presence, then estimation accuracy is improved, but computational complexity and processing time increase
Solution Approach 1:
The system performs simulations in advance to derive carbon dioxide concentration distribution patterns under various human presence conditions. These simulation results are stored as reference data, allowing the system to quickly estimate actual concentrations by comparing sensor readings with pre-computed simulation patterns, avoiding the need to run complex simulations in real-time.
Solution Approach 2:
The system creates a virtual model of the indoor space that replicates the physical environment's geometric information and ventilation characteristics. This virtual copy allows simulations to be performed on the model rather than requiring complex physical measurements, and the simulation results can be directly applied to estimate actual carbon dioxide concentrations in the real space.
2Measurement precision
If detailed three-dimensional information and environmental data are collected, then estimation accuracy is improved, but data processing complexity and time increase
Solution Approach 1:
The system collects and processes detailed three-dimensional space information, ventilation system data, and environmental parameters in advance to perform simulations. This preliminary processing creates a comprehensive virtual model that can be used for rapid estimation without requiring real-time processing of all these detailed parameters.
Solution Approach 2:
The estimation process is divided into distinct phases: (1) collecting detailed information about the space geometry and ventilation systems, (2) performing simulations using this information to derive concentration patterns, (3) storing simulation results as reference data, and (4) using this pre-processed information for rapid actual concentration estimation. This segmentation allows complex data processing to be done once rather than repeatedly.
3Measurement precision
If the system accounts for human presence and location in simulations, then estimation accuracy is improved, but system complexity increases
Solution Approach 1:
The system focuses simulation efforts on local regions where human presence is detected or expected. Rather than modeling the entire space with equal detail, the simulation concentrates computational resources on areas with high carbon dioxide generation potential, using location information to guide where detailed modeling is most needed.
Solution Approach 2:
The simulation model dynamically adjusts parameters based on detected human presence and location. When people are present in specific areas, the model modifies carbon dioxide generation rates and ventilation effectiveness parameters for those local zones, allowing accurate estimation without requiring a permanently complex model for all possible scenarios.
Data Source
AI summary
An estimation method includes an analysis step, an extraction step, an approximation step, a location information acquisition step, an estimation step, and a notification control step. The analysis step includes deriving, as analytic information, a carbon dioxide concentration distribution in a virtual space. The extraction step includes extracting, from the analytic information, information about a virtual carbon dioxide concentration distribution in a height direction. The approximation step includes establishing an analysis formula for approximating the carbon dioxide concentration distribution in the height direction. The location information acquisition step includes acquiring location information about a person. The estimation step includes estimating an actual carbon dioxide concentration distribution in a real space using the analysis formula and the location information. The notification control step includes making notification of information about the actual concentration distribution estimated in the estimation step.