大规模普适环境下具有不确定性感知的用户定位统一可扩展模型

P. Aksenov, K. Luyten, K. Coninx
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引用次数: 5

摘要

本地化已经成为许多移动应用程序的标准功能。目前有许多室内和室外位置跟踪技术,提供了多种方式将定位信息传递到移动应用程序(例如,基于位置的服务)。诸如精度随时间和覆盖区域的变化或质量和可靠性的差异等因素使得为一个应用程序采用几种技术变得麻烦。这项工作提出了一种方法,该方法对定位系统的能力进行建模,然后使用该模型建立一个统一的定位视图,特别注意来自不同定位条件及其对用户的表示的不确定性。我们讨论了该方法的技术考虑、挑战和问题,并报告了一项关于用户接受基于该方法的应用程序建议行为的用户研究。研究结果显示了该方法的可行性,并揭示了用户在使用应用程序时对自动但知情的变化的偏好。
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A Unified Scalable Model of User Localisation with Uncertainty Awareness for Large-scale Pervasive Environments
Localisation has become a standard feature in many mobile applications. Numerous techniques for both indoor and outdoor location tracking are available today, providing a diversity of ways positioning information can be delivered to a mobile application (e.g., a location-based service). Such factors as the variation of precision over time and covered areas or the difference in quality and reliability make the adoption of several techniques for one application cumbersome. This work presents an approach that models the capabilities of localisation systems and then uses this model to build a unified view on localisation, with special attention paid to uncertainty coming from different localisation conditions and its presentation to the user. We discuss technical considerations, challenges and issues of the approach and report about a user study on users' acceptance of the suggested behaviour of an application based on the approach. The results of the study showed the feasibility of the approach and revealed users' preference towards automatic but yet informed changes they experienced while using the application.
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