Competencies and objectives

 

Course context for academic year 2023-24

La inteligencia ambiental, o entornos inteligentes, se refiere a un paradigma en el que los entornos físicos y digitales están imbuidos de inteligencia y capacidades de interacción para adaptarse y responder a las necesidades y deseos de las personas de manera natural y no intrusiva. Esta visión implica la integración fluida de sensores, dispositivos y sistemas inteligentes en el entorno cotidiano, permitiendo que la tecnología se vuelva invisible y se integre de manera transparente en la vida diaria. A través de la recopilación de datos, el aprendizaje automático y la interacción intuitiva, la inteligencia ambiental tiene como objetivo mejorar la calidad de vida, brindando soluciones personalizadas, eficientes y contextualmente relevantes. Ya sea en hogares, oficinas, ciudades o incluso en dispositivos portátiles, la inteligencia ambiental ofrece un entorno en el que la tecnología se adapta a los usuarios, anticipando sus necesidades y ofreciendo experiencias más intuitivas y enriquecedoras.


Esta asignatura explora los fundamentos y aplicaciones de los entornos inteligentes. A lo largo del curso, los estudiantes adquirirán conocimientos sobre los principales conceptos teóricos y tecnológicos relacionados con la inteligencia ambiental, incluyendo la Internet de las Cosas (IoT), el aprendizaje automático, la interacción persona-máquina, la sensorización y la computación ubicua; aspectos que pueden haber sido introducidos en otras asignaturas, pero que se contextualizarán al ámbito de la inteligencia ambiental. Se examinarán casos de estudio y proyectos prácticos que demuestren cómo la inteligencia ambiental puede transformar diversos entornos, como los hogares, las ciudades, la industria o la salud.

 

 

Course content (verified by ANECA in official undergraduate and Master’s degrees) for academic year 2023-24

Transversal Competences

  • CT1 : Be able to lead projects related to artificial intelligence, as well as to manage work teams.
  • CT2 : Demonstrate computer and information skills in the field of artificial intelligence.
  • CT3 : Show oral and written communication skills.

 

General Competences

  • CG1 : Apply the knowledge acquired to real problems related to artificial intelligence.
  • CG10 : Be able to use engineering principles and modern computer technologies to research, design and implement new applications of artificial intelligence,
  • CG5 : Know how to manage the available information and resources related to artificial intelligence.
  • CG7 : To be able to adapt to the constant evolution of the discipline and to understand and apply new technical and scientific developments related to artificial intelligence.
  • CG8 : Knowing how to plan, design, develop, implement and maintain products, applications and services related to artificial intelligence, taking into account technical, economic and efficiency aspects.

 

Specific Competences

  • CE20 : Capacidad para concebir, diseñar y aplicar técnicas de adquisición y actuación inteligentes a sistemas ciberfísicos y de internet de las cosas.
  • CE21 : Know, design and manage architectures and platforms for the development of intelligent distributed applications in heterogeneous environments.

 

Basic Competences

  • CB10 : That students possess the learning skills that allow them to continue studying in a way that will be largely self-directed or autonomous.
  • CB6 : Possess and understand knowledge that provides a basis or opportunity to be original in the development and/or application of ideas, often in a research context
  • CB7 : That students know how to apply the knowledge acquired and their ability to solve problems in new or little-known environments within broader (or multidisciplinary) contexts related to their area of ¿¿study
  • CB8 : Students are able to integrate knowledge and deal with the complexity of making judgements on the basis of incomplete or limited information, including reflections on the social and ethical responsibilities associated with information which, while incomplete or limited, includes reflections on the social and ethical responsibilities linked to the application of their knowledge and judgements.
  • CB9 : Students are able to communicate their conclusions and the ultimate knowledge and rationale behind them to specialist and non-specialist audiences in a clear and unambiguous way.

 

 

 

Learning outcomes (Training objectives)

- Know the technologies, architectures and infrastructures related to IoT, Cyber-Physical Systems and intelligent platforms and environments.

- Define the technological requirements for the execution of applications in heterogeneous environments with intelligent interfaces.

- Modelling solutions for smart applications in different fields: cities, homes, industry, health.

 

 

Specific objectives stated by the academic staff for academic year 2023-24

No data

 

 

General

Code: 43510
Lecturer responsible:
CLIMENT PEREZ, PAU
Credits ECTS: 3,00
Theoretical credits: 0,60
Practical credits: 0,60
Distance-base hours: 1,80

Departments involved

  • Dept: INFORMATION TECHNOLOGY AND COMPUTING
    Area: COMPUTER ARCHITECTURE
    Theoretical credits: 0,6
    Practical credits: 0,6
    This Dept. is responsible for the course.
    This Dept. is responsible for the final mark record.

Study programmes where this course is taught