An Ambient Intelligence responds to user requests based on several contexts. A relevant context is related to what has happened in the ambient; therefore, it focuses a primordial interest on events. These involve information about time, space, or people, which is significant for modeling the context. In this paper, we propose an event-driven approach for context representation based on an ontological model. This approach is extendable and adaptable for academic domains. Moreover, the ontological model to be proposed is used in reasoning and enrichment processes with the context event information. Our event-driven approach considers five contexts as a modular perspective in the model: Person, temporal (time), physical space (location), network (resources to acquire data from the ambient), and academic events. We carried out an evaluation process for the approach based on an ontological model focused on (a) the extensibility and adaptability of use case scenarios for events in an academic environment, (b) the level of reasoning by using competence questions related to events, (c) and the consistency and coherence in the proposed model. The evaluation process shows promising results for our event-driven approach for context representation based on the ontological model.

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An Intelligent environment can respond to the necessities of the users according to the context, this is so that the individuals can have the ideal climatic conditions in order to go about their activities, these conditions are related through a series of special norms. The events that we describe in this paper are in relation to the events of the environment (temperature, humidity, brightness, and presence), also involved are different variables like time, space, or person, such are important in order to be able to model what is occurring in a determined place. In this project, we propose a personalized ontological design for the academic dominion. The ontological model is utilized for the identification of environmental events according to the data acquired from the environment through the simulation of intellectual agents. Also, our ontological model is used to rationalize with the information obtained from the identified events. The model of ontologies based on events considers four contextual questions like a perspective modular: person, seasonality (weather), spatiality (location), network (resources in order to acquire environmental data) and event (academic events). And the detector is based on rules obtained from the standards of optimum climatic conditions of a physical space.