@mastersthesis{development-gsi-mastersthesis-20232,
author = "Mora P{\'e}rez, Jos{\'e} Ignacio ",
abstract = "Today, the number of systems that use artificial intelligence and process large amounts of data is very high, applications with new functionalities that support people and professionals in different fields are developed every day.

Emotion-aware systems, the culmination of AI’s foray into the realm of human emotions, represent an exciting and transformative frontier in technology. These systems are engineered to not only comprehend but also respond to human emotions in real-time, whether they are expressed through spoken words, written text, facial expressions, or physiological signals.

The potential impact of an immersive emotion-aware system extends across diverse
domains. In healthcare, it offers a revolutionary approach to mental health support, with applications in early detection and intervention. In education, it transforms the learning experience, customising content to match students’ emotional engagement. In marketing and customer service, it redefines engagement by tailoring responses to customer sentiments.

Therefore, in this master thesis, we have developed an immersive emotion-aware system that is able to analyse emotions in real-time and also has the ability to analyse videos, extracting their emotional characteristics from various sources, video, audio and text. To visualise the data collected by this system, it has been necessary to implement a web application with several dashboards depending on whether real-time or video analysis has been chosen. The application allows the user to visualise the extracted data in the form of graphs, allowing them to be interpreted in a much more visual way and making them easier to understand.

To summarise, the objective of this project has been to develop an immersive emotion-aware system through a web application that allows real-time analysis and video analysis, very useful functionalities for many fields.",
address = "ETSI Telecomunicaci{\'o}n",
institution = "Universidad Polit{\'e}cnica de Madrid",
keywords = "emotion analysis;dashboard;internet of Things;web development;python",
month = "September",
title = "{D}evelopment of an {I}nmersive {E}motion-aware system",
type = "TFM",
year = "2023",
}