Internet of Things (IoT) has introduced new applications and environments. Smart Home provides new ways of communication and service consumption. In addition, Artificial Intelligence (AI) and deep learning have improved different services and tasks by automatizing them. In this field, reinforcement learning (RL) provides an unsupervised way to learn from the environment. In this paper, a new intelligent system based on RL and deep learning is proposed for Smart Home environments to guarantee good levels of QoE, focused on multimedia services. This system is aimed to reduce the impact on user experience when the classifying system achieves a low accuracy. The experiments performed show that the deep learning model proposed achieves better accuracy than the KNN algorithm and that the RL system increases the QoE of the user up to 3.8 on a scale of 10.

物联网 (IoT) 引入了新的应用程序和环境。智能家居提供了新的通信方式和服务消费方式。此外，人工智能 (AI) 和深度学习通过自动化改进了不同的服务和任务。在该领域，强化学习 (RL) 提供了一种从环境中学习的无监督方式。在本文中，针对智能家居环境提出了一种基于 RL 和深度学习的新型智能系统，以保证良好的 QoE，专注于多媒体服务。该系统旨在减少分类系统精度较低时对用户体验的影响。进行的实验表明，所提出的深度学习模型比 KNN 算法实现了更好的准确性，并且 RL 系统在 10 的尺度上将用户的 QoE 提高到 3.8。