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

Abstract

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. © 2017 IEEE.