Abstract: The field of artificial intelligence, especially machine learning, is currently evolving rapidly. There is a growing demand for the development of emotional intelligence models, which are being applied across various sectors, including intelligence assessment, education, and healthcare. These emotional intelligence models are designed to recognize and manage human emotions effectively. In our project, we developed the EIWebCam software system, which allows for real-time detection of a person's emotional state using a facial image captured by a webcam. We prepared the necessary datasets, designed and trained a machine learning model, and integrated the webcam into the system. The entire system was deployed in a cloud environment. At each stage of our experiments, we evaluated the advantages and disadvantages of the chosen technologies. As a result, we identified effective scenarios for the performance of the EIWebCam system. This software system is utilized to assess an individual's emotional state in real time.

Keywords: Emotional intelligence, machine learning, webcam, face recognition, neural networks, cloud server, cloud service

Pages: 121-126