Mobile proactive tourist recommender systems can support tourists by recommending the best choice depending on different contexts related to herself and the environment. In this paper, we propose to utilize wearable sensors to gather health information about a tourist and use them for recommending tourist activities. We discuss a range of wearable devices, sensors to infer physiological conditions of the users, and exemplify the feasibility using a popular self-quantification mobile app. Our main contribution then comprises a data model to derive relations between the parameters measured by the wearable sensors, such as heart rate, body temperature, blood pressure, and use them to infer the physiological condition of a user. This model can then be used to derive classes of tourist activities that determine which items should be recommended.
翻译:移动式主动旅游推荐系统可以根据与自己和环境有关的各种情况推荐最佳选择,从而支持游客。在本文中,我们提议使用可磨损传感器收集关于游客的健康信息,并将这些信息用于推荐旅游活动。我们讨论一系列可磨损装置、推断用户生理状况的传感器,并用流行的自我量化移动应用软件来说明可行性。我们的主要贡献随后包括一个数据模型,用以得出由可磨损传感器测量的参数之间的关系,如心率、体温、血压,并利用这些数据来推断用户的生理状况。然后,这一模型可用于产生确定哪些物品应当推荐的旅游活动类别。