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User-driven design of ontology-based, context-aware and self-learning continuous care applications

机译:用户驱动的基于本体,上下文感知和自学习的连续护理应用程序的设计

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A plethora of technologies is adopted in modern continuous care settings. Nowadays, the nurse is responsible for orchestrating all these devices to take advantage of the collected information. This causes caregivers to lose time, miss out on patient insights and lack a general overview of the situation. In this paper, an ontology-based and self-learning context-aware platform is presented. This platform combines pervasive and context-aware techniques with knowledge management techniques to leverage the aforementioned problems and allows to easily build intelligent applications to support caregivers in their everyday activities. Moreover, a self-learning framework is proposed, which allows detecting trends in the usage of these applications and adapting them accordingly. However, the integration of context-aware technologies can prove to be difficult if domain experts are not involved in the development process. This increases the fear of the technology, makes the staff feel less in control and empowered and causes that the technologies are not tuned towards the work processes of the staff. Therefore, a participatory ontology engineering methodology is also presented which allows involving the stakeholders in each part of the development process of context-aware applications.
机译:现代连续护理环境采用了多种技术。如今,护士负责协调所有这些设备,以利用收集到的信息。这导致护理人员浪费时间,错过了患者的见解,并且缺乏对情况的总体了解。本文提出了一种基于本体的自学习上下文感知平台。该平台将普适性和上下文感知技术与知识管理技术相结合,以利用上述问题,并允许轻松构建智能应用程序以支持护理人员的日常活动。此外,提出了一种自学习框架,该框架允许检测这些应用程序的使用趋势并进行相应调整。但是,如果领域专家不参与开发过程,则集成上下文识别技术可能会很困难。这增加了对技术的恐惧,使员工感到缺乏控制和授权,并导致技术未针对员工的工作流程进行调整。因此,还提出了一种参与型本体工程方法论,该方法论使利益相关者参与上下文感知应用程序开发过程的每个部分。

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