In current article a process of development of an application for ecological data analysis was researched, particularly pollutants concentration measurements using wavelet transform apparat. To improve the ecological situation and preventing harmful ecological event it is needed to monitor the condition of environment. Ecological monitoring contains a complex system of observations of current environment conditions, observations’ results processing and analysis, creating ecological prognosis including natural and anthropogenic factors. Monitoring data serves as a main source of information for making ecologically significant decisions. Ecological data is stochastic and are extremely random, are known by extraordinary dissipation, directly or indirectly depend on numerous parameters. This data is hard to analyze with methods of classical mathematic, sometimes, when the randomness of the data is high, it could be even impossible. Pollutant’s concentration measurements data makes a time series. In current paper for the analysis of the time series wavelet transform tools were used, either the discrete version or the continuous one, based on those a mathematical model of the process was created. Object-oriented modelling of project’s architecture was created based on provided mathematical model, particularly, classes, components and activity diagrams were built. The application was developed as a cross-platform stand-alone app. After the analysis it was proved to be reasonable to write the application in Python programming language using libraries for mathematical and statistical functions, particularly NumPy, Math, Statistics, and additionally PyWv for wavelet usage assistance. Current application allows to process ongoing and historical data from multiple sources to analyze tendencies of changes in atmosphere condition
Read full abstract