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Methods of environmental monitoring parameters based on smart measurement systems

机译:基于智能测量系统的环境监测参数方法

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As the effects of global warming are spreading globally, the world population encounters one of the most important social and scientific phenomena-changing the parameters of the environment due to pollution. Any conducted action requires precise and accurate measuring of the environmental parameters at several dozens of thousands points deployed around the world. Since financially, as well as practically, it is impossible to create such a large number of measuring stations which would network all over the planet, it is obvious that some alternative solutions must be found. A new measuring system is developed and measuring methods for remote measurement of environmental parameters are implemented. This system can be implemented as a stationary or mobile measuring station. The working hypothesis is based on the use of statistical analysis of measurement data. It leads to the possibility of reducing the number of sensors at measure station, as based on the monitoring of one value-gas concentration (the concentration of carbon monoxide) can be estimated values of other gas (the concentration of nitrogen — dioxide) in the case that they originate from the same source. Using prediction and regression models — interpolation and extrapolation have shown the possibility to reduce the number of measuring stations. Also, based on a mathematical model (ARMA) estimation of concentrations of gases based on previous measurements is shown.
机译:随着全球变暖的影响在全球范围内蔓延,世界人口遇到了最重要的社会和科学现象之一,即由于污染而改变了环境参数。任何采取的行动都需要在全球部署的数十万个点上精确,准确地测量环境参数。由于在经济上和实践上都不可能创建如此庞大的测量站,这些测量站将遍布整个地球,因此很明显,必须找到一些替代解决方案。开发了一种新的测量系统,并实现了用于远程测量环境参数的测量方法。该系统可以实现为固定式或移动式测量站。工作假设基于对测量数据的统计分析的使用。由于可以监测一种值的气体浓度(一氧化碳的浓度),可以估算出另一种气体的值(氮-二氧化碳的浓度),因此可以减少测量站传感器的数量。它们来自同一来源的情况。使用预测和回归模型-内插法和外推法显示了减少测量站数量的可能性。此外,显示了基于数学模型(ARMA)的基于先前测量值的气体浓度估算值。

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