Occupancy Detection

Occupancy detection aims to accurately determine the presence and number of people in a given space, a crucial task for optimizing energy efficiency, improving building management, and enabling various smart applications. Current research focuses on developing robust and cost-effective methods using diverse data sources, including CO2 levels, electricity consumption, and visual data analyzed via deep learning models like transformers and convolutional neural networks (CNNs), often incorporating techniques like active learning to reduce data collection needs. These advancements have significant implications for building automation, energy conservation, and the development of more intelligent and responsive environments.