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A rule-based context transforming model for robot services in internet of things environment

机译:物联网环境中基于规则的机器人服务上下文转换模型

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In IoT environment, large amount of data can be collected by various sensors, and the collected data can be processed to create new values. On the other hand, in order to provide the robot services to users, context information is required for recognizing the surrounding situational information. However, each sensor gives a single value as context information, so it is difficult to express the surrounding situation of users with only this context information individually. In this paper, we propose a rule-based context transforming model to extract situational information from each context information in IoT environment. The proposed transforming rule is based on a transforming specification that expresses the association between various kinds of context information. The proposed rule can transform it into situational information to use context information of entities having various forms and features by expressing the surrounding situation. In addition, the transforming rule has criteria required for each entity. Therefore the entity information can be used to represent various situations, and the generated situational information can be applied to the robot services. In the experiment, we demonstrated the process of transforming situational information from several sets of context information by applying proposed model.
机译:在物联网环境中,各种传感器可以收集大量数据,并且可以对收集到的数据进行处理以创建新值。另一方面,为了向用户提供机器人服务,需要上下文信息来识别周围情况信息。然而,每个传感器给出单个值作为上下文信息,因此仅用该上下文信息来单独表示用户的周围环境是困难的。在本文中,我们提出了一种基于规则的上下文转换模型,以从物联网环境中的每个上下文信息中提取情境信息。提出的变换规则基于表达各种上下文信息之间的关联的变换规范。所提出的规则可以通过表达周围情况,将其转换为情况信息,以使用具有各种形式和特征的实体的上下文信息。另外,转换规则具有每个实体所需的标准。因此,实体信息可以用于表示各种情况,并且所生成的情况信息可以应用于机器人服务。在实验中,我们通过应用提出的模型演示了从多组上下文信息中转换情境信息的过程。

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