The Internet of Things (IoT) has recently been applied in the domain of cultural exhibition enabling the cultural sites to provide more personal and proactive experiences to their visitors. To come up with valuable services, several solutions to analyze the spatio-temporal trajectories of visitorshave been put forward. However, they neither consider the inherent uncertainty of the underlying indoor positioning technologies – Bluetooth Low Energy (BLE), RFID, etc. – nor other visitors’ features apart from the spatio-temporal ones (e.g. the level of interaction with the museum displays). For that reason, the present work introduces RECITE, a framework to classify trajectories representing visitors’ actions that copes with the aforementioned limitations of existing solutions. Firstly, RECITE states a novel mapping process for a BLE-based indoor positioning system to accurately detect the visitors’ locations. On top of this mechanism, RECITE includes an ensemble of fuzzy rule classifiers able to tag the visitors’ ongoing trajectories in real time considering both spatio-temporal and other behavioural factors. Finally, the framework has been evaluated in a case of use scenario showing quite promising results.

中文翻译：

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RECITE：文化遗址用户轨迹分析框架

物联网（IoT）最近被应用于文化展览领域，使文化场所能够为参观者提供更加个性化和主动的体验。为了提供有价值的服务，已经提出了几种分析访客时空轨迹的解决方案。然而，他们既没有考虑底层室内定位技术的内在不确定性——蓝牙低功耗 (BLE)、RFID 等——也没有考虑除时空特征之外的其他游客特征（例如与博物馆展示的交互水平） . 出于这个原因，目前的工作引入了 RECITE，这是一个对表示访问者行为的轨迹进行分类的框架，可以应对现有解决方案的上述局限性。首先，RECITE 为基于 BLE 的室内定位系统提出了一种新颖的映射过程，以准确检测访客的位置。在此机制之上，RECITE 包括一组模糊规则分类器，能够在考虑时空和其他行为因素的情况下实时标记访问者正在进行的轨迹。最后，该框架已经在一个使用场景的情况下进行了评估，显示出非常有希望的结果。