In-Gauge and En-Gage: Understanding Occupants' Behaviour, Engagement, Emotion, and Comfort Indoors with Heterogeneous Sensors and Wearables

We conducted a field study at a K-12 private school in the suburbs of Melbourne, Australia. The datasets contained two elements: (1) In-Gauge dataset: we conducted a 5-month longitudinal field study using two outdoor weather stations, as well as indoor weather stations in 17 classrooms and temperature sensors on the vents of occupant-controlled room air-conditioners; these were collated into individual datasets for each classroom at a 5-minute logging frequency, including additional data on occupant presence. (2) En-Gage dataset: we tracked 23 students and 6 teachers in a 4-week cross-sectional study En-Gage, using wearable sensors to log physiological data (electrodermal activity, heart rate, blood column pulse, skin temperature, 3-axis acceleration), as well as daily surveys to query the occupants' thermal comfort, learning engagement, emotions and seating behaviours. Overall, the combined dataset could be used to analyse the relationships between indoor/outdoor climates and students' behaviours/mental states on campus, which provide opportunities for the future design of intelligent feedback systems to benefit both students and staff.

本研究在澳大利亚墨尔本郊区的某所K-12私立学校进行了实地调查。数据集包含两个部分：（1）In-Gauge数据集：我们利用两个户外气象站以及17个教室内的气象站和居住者控制空调出风口的温度传感器，开展了为期5个月的纵向实地研究；这些数据以5分钟为间隔，为每个教室建立独立的个体数据集，并包含居住者存在的额外数据。（2）En-Gage数据集：在为期4周的横断面研究中，我们追踪了23名学生和6名教师，利用可穿戴传感器记录生理数据（皮肤电活动、心率、血压脉搏、皮肤温度、三轴加速度），并通过每日调查了解居住者的热舒适度、学习参与度、情绪和就坐行为。总体而言，结合后的数据集可用于分析室内外气候与学生在校园中的行为/心理状态之间的关系，为未来智能反馈系统的设计提供机遇，以惠及学生和教职工。