Room Occupancy Detection
Heartbeat Publication Articles
This project aims to predict whether a room is occupied based on the data collected from the sensors. The data set is collected from the UCI Machine Learning Repository. The data set contains 7 attributes: date, temperature, humidity, light, CO2, humidity ratio, and occupancy. The data set is divided into 2 data sets for training and testing. It provides experimental data for binary classification (room occupancy of an office room) from Temperature, Humidity, Light, and CO2. Ground-truth occupancy was obtained from time-stamped pictures that were taken every minute.