Trends boetween indoor CO2 concentration and electricity usage through topological data analysis
Shun Endo, Shinji Yokogawa · 2021 IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech) · 2021
In this study, we analyze multidimensional data collected from a large number of sensors installed in an active-learning space in a university through topological data analysis (TDA). Further, we propose a method to examine this data visually. The proposed method visualizes the relationship between electricity usages and observes carbon dioxide (CO2) concentration data, extracting the features of electricity usage, as well as the factors contributing to the increase in CO2. This method, which relies on TDA, clarifies the data structure and expresses the correspondence with the original data, which is effective for the visualization and application of multidimensional time-series data. Correlations were found between CO2levels, energy consumption, and the presence of people.