Project publication · IEEE Open Journal of the Computer Society
Summary
The article proposes an artificial intelligence of behavior approach to recognize human emotions in closed environments using sensors and contextual data.
Main contribution
The proposal combines environmental measurements and signals related to emotional state to build adaptive spaces. The approach extends the use of artificial intelligence toward interaction between people, environment and technology.
Resultados y alcance
Los experimentos muestran que la combinación de señales y modelos de inteligencia artificial permite reconocer estados emocionales en recintos cerrados. El rendimiento está condicionado por la variabilidad entre personas, el contexto, la calidad de los sensores y la necesidad de proteger privacidad y consentimiento.
Link with BoND1
BoND1 considers IoT networks as infrastructure for capturing context and enabling intelligent services. This publication connects with that vision by using sensing and machine learning to interpret closed environments and support adaptive decisions.
Project publication IEEE Open Journal of the Computer Society
Summary
The paper proposes a behavioral artificial intelligence approach to recognize human emotions in closed environments based on sensors and contextual data.
Bibliometric indicators
- JCR area
- Computer Science, Theory & Methods
- JCR year
- 2025
- Scholar query
- 26 October 2026
Main contribution
The proposal combines environmental measures and signals related to the emotional state to build adaptive spaces. The approach expands the use of artificial intelligence towards the interaction between people, environment and technology.
Results and scope
The experiments show that the combination of signals and artificial intelligence models makes it possible to recognize emotional states in closed spaces. Performance is conditioned by variability between people, context, sensor quality, and the need to protect privacy and consent.
Link with BoND1
BoND1 views IoT networks as infrastructure to capture context and enable smart services. This publication connects with that vision by using sensing and machine learning to interpret closed environments and support adaptive decisions.