Sub-field · 3 papers
Smart Building Occupancy Management
Machine learning and predictive modeling are applied across diverse smart environment and data-driven decision contexts, including building occupancy forecasting for HVAC optimization, crowdfunding campaign outcome prediction, and privacy-preserving crowd management in smart cities and buildings. The unifying thread is the use of data-driven techniques to extract actionable insights from human behavioral patterns in physical or digital spaces.