A innovative wavelet transformation method optimization in the noise-canceling application within intelligent building occupancy detection monitoring.

ABSTRACT: The study deals with detection of the occupation of Intelligent Building (IB) using data obtained from indirect methods with Big Data Analysis within IoT. In the area of daily living activity monitoring, one of the most challenging tasks is occupancy prediction, giving us information about people's mobility in the building. This task can be done via monitoring of CO2 as a reliable method, which has the ambition to predict the presence of the people in specific areas. In this paper, we propose a novel hybrid system, which is based on the Support Vector Machine (SVM) prediction of the CO2 waveform with the use of sensors that measure indoor/outdoor temperature and relative humidity. For each such prediction, we also record the gold standard CO2 signal to objectively compare and evaluate the

SUBMITTER: Vanus J 

PROVIDER: S-EPMC10205525 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature