Data set for estimating the precise number of occupants in a room using multiple non-intrusive environmental sensors like temperature, light, sound, CO2 levels, and PIR motion detectors has been collected. This project focuses on the classification task of predicting the occupancy status of a room based on these sensor readings. The dataset includes features such as date, time, temperature, light intensity, sound levels, CO2 concentration, and PIR motion readings from various sensors placed in the room.
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