One of the most important concepts of the internet of things is related to software services, where the system must be able to provide real-time data collected from various environments. So that software services represent a variety of physical and virtual real-world objects that can grow very fast. This condition is related to the ability of sell-adaptation software services. However, the existing model of self-adaptation is generally not paying attention to the requirements for service evolution. The objective of this paper is to introduce self-adaptation modeling techniques which consist of, first, domain modeling of the internet of things to represent real-world context; second, developing an inference engine for context inference. As a form of evaluation, this model is applied to the patient monitoring system that will relate to the concept of self-adaptation of various systems, devices, actors, and environment. The case study results show the system's ability to anticipate changes in context and growth needs.
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