A context-aware Internet of Things system must be able to observe, interpret, and reason the dynamic situations of the environment to provide pertinent information and services to the user. This article proposes an approach structured around three contributions: semantic representation of IoT data, context situations detection, and contextual information dissemination for consumers. The main contribution of this article is represented by a hybrid system for the intelligent detection of the context situation in an IoT environment, which combines machine learning algorithms and approximate logic, more precisely, artificial neural network, case-based reasoning, and fuzzy logic. Finally, we chose a use case in the intelligent transportation sector to validate our approach.