A Multimodal Dataset for Smart Office Occupancy Estimation

This dataset presents a multimodal datasource collected in a real smart environment located at the Pontifical Catholic University of Rio Grande do Sul (PUCRS), Brazil. The dataset documents environmental, electrical, and device-interaction measurements collected from a heterogeneous Internet of Things (IoT) deployment composed of commercial smart devices and a custom ESP32-based sensing node. Environmental variables include carbon dioxide concentration, temperature, humidity, light intensity, and sound level. Electrical measurements include instantaneous power, voltage, current, and device state indicators collected from smart sockets, switches, and a dedicated server. Data were collected continuously under routine academic workspace operation, reflecting natural occupancy fluctuations, restricted access control, and heterogeneous network conditions. The custom sensing node was programmed in Arduino C++ and exposed measurements via HTTP requests, while commercial devices were queried through their respective cloud APIs. All records were stored in structured JSON format with synchronized timestamps. These data can support research in occupancy detection, energy usage analysis, anomaly detection, and smart-building experimentation. The dataset also provides a documented example of a real-world IoT deployment suitable for replication or comparative studies.