García Cuesta, EstebanLópez López, José ManuelGómez Vergel, DanielHuertas Tato, Javier2020-11-132020-11-132021García-Cuesta, E., López-López, J. M., Gómez-Vergel, D., & Huertas-Tato, J. (2021). An Adaptive Cognitive Model to Integrate Machine Learning and Visual Streaming Data. In Advances in Intelligent Systems and Computing: 15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020) (pp. 176–185). Springer. https://doi.org/10.1007/978-3-030-57802-2_1797830305780159783030578022http://hdl.handle.net/11268/9448In this paper, we present our current work towards developing a context aware visual system with capabilities to generate knowledge using an adaptive cognitive model. Our goal is to assist people in their daily routines using the acquired knowledge in combination with a set of machine learning tools to provide prediction and individual routine understanding. This is useful in applications such as assistance to individuals with Alzheimer by helping them to maintain a daily routine based on historical data. The proposed cognitive model is based on simple exponential smoothing technique and provides real time detection of objects and basic relations in the scene. To fulfill these objectives we propose the integration of machine learning tools and memory based knowledge representation.engconference output10.1007/978-3-030-57802-2_17restricted accessInteligencia artificialAprendizaje automáticoInteligencia artificialAutoaprendizaje