Research Data Article: MRI and EEG-TMS dataset

New Dataset Released: High-Resolution Indoor Movement Data for Smart Building Innovation. The Core Problem. To optimize energy efficiency and indoor comfort, modern "smart" buildings need to understand how people actually move and behave inside them. However, researchers often lack high-quality, real-world data to train the AI models that predict these behaviors. What the Dataset Provides?. This article presents a robust, open-access dataset tracking human indoor movement. It captures diverse occupancy patterns, including:. Activity Recognition: Identifying specific actions (sitting, walking, working)., Occupant Trajectories: Precise mapping of how people move through different zones., Environmental Interaction: How movement correlates with the use of building systems (lighting, HVAC). Key Technical Value:. High Granularity: The data is recorded at a high frequency, making it suitable for training advanced Machine Learning (ML) and Deep Learning models., Cross-Disciplinary Use: It serves multiple fields, from Building Information Modeling (BIM) and HVAC optimization to emergency evacuation planning and elderly care monitoring., Standardized Format: The data is structured for immediate use in predictive modeling, reducing the "data cleaning" burden for researchers.