We propose a model of the situational context of a person and show how it can be used to organize and, consequently, reason about massive streams of sensor data and annotations, as they can be collected from mobile devices, e.g. smartphones, smartwatches or fitness trackers. The proposed model is validated on a very large dataset about the everyday life of one hundred and fifty-eight people over four weeks, twenty-four hours a day.

翻译：我们提出一个人的情景模型,说明如何利用它来组织并由此解释大量传感器数据和说明流,因为这些数据和说明可以通过移动设备收集,例如智能手机、智能观察器或健身跟踪器。 提议的模型在关于四个星期、一天二十四小时、每天一百五十八人的日常生活的庞大数据集上得到验证。