Accurate occupancy detection of an office room from light, temperature, humidity and CO2 measurements using statistical learning models

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Anomaly Detection in Time Series: A Comprehensive Evaluation (2022, unknown): “4% 24 0 Occupancy [24, 41] real multi 6,208 28.”
Fusion of Nonintrusive Environmental Sensors for Occupancy Detection in Smart Homes (2018, methodology): “sensors was installed in a two-person university office by Candanedo and Feldheim [15].”
IoT-Based Sensor Data Fusion for Occupancy Sensing Using Dempster–Shafer Evidence Theory for Smart Buildings (2017, methodology): “(b) Sample snapshot of the digital camera used to establish ground occupancy taken from [16].”
Internet of Things for Green Building Management: Disruptive Innovations Through Low-Cost Sensor Technology and Artificial Intelligence (2018, background): “As such, existing studies of occupancy detection in building environments, such as [25] and [26], have used techniques that exploit environmental information (including carbon dioxide level, noise level, humidity level, and particulate matter concentration) instead of using a camera.”
Unsupervised Anomaly Detection With LSTM Neural Networks (2017, methodology): “1) Occupancy Detection: We first evaluate the performances of the algorithms on the occupancy data set [37].”