ROBOD, Room-level Occupancy and Building Operation Dataset

This comprehensive dataset consisting of indoor environmental conditions, Wi-Fi connected devices, energy consumption of end uses (i.e., HVAC, lighting, plug loads and fans), HVAC operations, and outdoor weather conditions collected through various heterogeneous sensors together with the ground truth occupant presence and count information for five rooms located in a university environment. The five rooms include two different-sized lecture rooms (Room 1 and Room 2) , an office space for administrative staff (Room 3), an office space for researchers (Room 4), and a library space (Room 5) accessible to all students. A total of 181 days of data was collected from all five rooms at a sampling resolution of 5 minutes. This dataset can be used for benchmarking and fostering data driven approaches in the field of occupancy prediction and occupant behaviour modelling, building simulation and control, energy forecasting and various building analytics.本综合数据集涵盖了通过多类异构传感器采集的室内环境参数、已接入Wi-Fi的设备信息、终端用能（即暖通空调（HVAC）、照明、插座负载及风扇）能耗、暖通空调运行状态，以及室外气象条件，同时附带了某大学校园内5个房间的真实人员在场情况与人数统计数据。该5个房间分别为两间不同规模的报告厅（1号房间与2号房间）、行政人员办公室（3号房间）、科研人员办公室（4号房间）以及面向全体学生开放的图书馆阅览区（5号房间）。本次数据采集覆盖全部5个房间，总时长共计181天，采样分辨率为5分钟。本数据集可用于人员到场预测、人员行为建模、建筑模拟与控制、能源预测及各类建筑数据分析领域的基准测试，以及数据驱动方法的研发与应用。