A Multimodal Dataset for Smart Office Occupancy Estimation

This dataset presents a multimodal dataset 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, relative humidity, light intensity, and sound pressure level. Electrical measurements include instantaneous power, voltage, current, and device-state measurements collected from smart sockets, switches, and a dedicated server. Data were collected continuously under routine academic workspace operation, reflecting natural occupancy fluctuations, restricted-access conditions, and heterogeneous network behavior. The custom sensing node was programmed in Arduino C++ and exposed measurements via HTTP requests, while commercial Tuya-based devices were polled locally through the Tuya LAN protocol using the TuyAPI library. Records were stored in structured JSON format, with a common timestamp assigned at the end of each acquisition cycle. Each record therefore represents the aggregation of values collected within the same 10-second polling window rather than perfectly simultaneous measurements acquired at the exact same instant. 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.