MILAN

该数据集包含了来自智能家庭测试环境中的运动和接触传感器收集的二元数据，活动已被标注。此外，该数据集存在类别高度不平衡的问题，其中“其他”类别占主导地位，并且数据分割采用了滑动窗口方法。该数据集的规模为来自9名受试者的数据收集，其任务是进行人体活动识别。

This dataset contains binary data collected by motion and contact sensors in a smart home test environment, with all activities annotated. Furthermore, this dataset suffers from severe class imbalance, where the "Other" category dominates, and a sliding window approach was employed for data segmentation. The dataset was constructed using data collected from 9 participants, and its target task is human activity recognition.