Carbon reduction assessment of public buildings based on Apriori algorithm and intelligent big data analysis

Abstract

Today, with the continuous progress of urbanization, public buildings have many environmental problems. Their high carbon emissions and energy consumption have caused considerable environmental pollution. Based on the analysis of the whole life cycle of public buildings, it can be seen from the results that due to its long time span, the service life will cause more pollution to the environment, high energy consumption and carbon emissions. In this environment, this paper completes the design and construction of carbon reduction measurement system for public buildings by combining intelligent big data technology and Apriori algorithm. The system mainly analyzes the whole life cycle of the building to calculate all energy consumption projects of the building, converts them into carbon footprint indicators, and uses the indicators to complete the quantitative assessment of environmental pollution level for public buildings in the whole life cycle, and obtains the carbon reduction assessment data of the building in the operating cycle in combination with the carbon emission factors of energy and electricity. The results of quantitative data analysis can be used for the design and arrangement of energy conservation and emission reduction policies, which can be realized by changing the lighting and ventilation, peripheral protection, shape coefficient and rainwater circulation of buildings. This paper conducts carbon reduction assessment for public buildings by integrating intelligent big data and Apriori algorithm.