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In this paper, a data acquisition and integration platform for internet of things is proposed. The platform is developed under a cloud computing environment using context-oriented approaches. It collects sensor data from different types of sensor devices, including such as RFID, ZigBee sensors, GPS devices, temperature sensors, humidity sensors, luminance sensors, etc. First we are devoted to the...
This paper presents an algorithm that generalizes big sets of contextual situations. Apart from giving details on its mechanisms and implementation, we discuss its employment in a context experience sharing system, KRAMER, and simulate its performance in function of several parameters modelling the expected real data experiment.
Context data are updated frequently due to the dynamic changes of the various sensor values and the situations of application entities. Without a proper management, the stored contexts will become different from those of the real-world. Those invalid contexts will cause context inconsistency problems and thus should be eliminated at the right time and in an appropriate manner. In this paper, we propose...
In existing mobile content service systems, the study is quite rare on automatic situation-service rule construction. Hence, a method is proposed that the semantic association rules between situations and preferences are built by quantitative frequent marked lattice. Different recommendation rules can be extracted along multi-dimensional context routes from this lattice structure. It is propitious...
Within domain-based service environments, service discovery through appropriate matchmaking procedures remains a key challenge. In particular, the consideration of additional context information and the need for dynamic and fast service publishing cause high demands on the according automatic matching procedures and the service description structures they are operating on.Within this paper, we introduce...
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