Competencies and objectives

 

Course context for academic year 2024-25

Ambient intelligence, or smart environments, refers to a paradigm in which physical and digital environments are imbued with intelligence and interaction capabilities to naturally and unobtrusively adapt to and respond to people's needs and desires. This vision involves the seamless integration of sensors, devices, and intelligent systems into everyday surroundings, making technology invisible and transparently integrated into daily life. Through data collection, machine learning, and intuitive interaction, ambient intelligence aims to enhance quality of life by providing personalised, efficient, and contextually relevant solutions. Whether in homes, offices, cities, or even wearable devices, ambient intelligence offers an environment where technology adapts to users, anticipating their needs and providing more intuitive and enriching experiences.

This course explores the fundamentals and applications of smart environments. Throughout the course, students will gain knowledge of the main theoretical and technological concepts related to ambient intelligence, including the Internet of Things (IoT), machine learning, human-computer interaction, sensing, and ubiquitous computing; aspects that may have been introduced in other courses but will be contextualised to the field of ambient intelligence. Case studies and practical projects demonstrating how ambient intelligence can transform various environments, such as homes, cities, industry, or healthcare, will be examined.

 

 

Course content (verified by ANECA in official undergraduate and Master’s degrees) for academic year 2024-25

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 2024-25

The main objective of this course is to provide a deep understanding of how technology can be designed and implemented to create smart environments that autonomously adapt and respond to people's needs and preferences. Special attention will be given to intelligent systems for human-environment interaction.

Specifically, the main objectives are as follows:

  1. Provide a solid understanding of the theoretical principles and fundamental concepts underlying ambient intelligence. This includes reviewing different aspects of application to smart environments, such as human-computer interaction, artificial intelligence, machine learning, the Internet of Things (IoT), and sensing.
  2. Understand the current state and future requirements of the technologies necessary for implementing a smart environment.
  3. Learn the techniques and different applications of human-computer interaction in smart environments, such as computer vision, speech and natural language recognition, virtual reality, and multimodal systems.
  4. Explore practical applications of ambient intelligence in various contexts. This can range from smart homes to offices, smart cities, and healthcare environments.
  5. Learn to identify the needs and desires of people in different contexts and propose creative and innovative solutions that leverage ambient intelligence.
  6. Analyse ethical and security aspects associated with the use of smart technologies in everyday environments.

 

 

General

Code: 43510
Lecturer responsible:
FLOREZ REVUELTA, FRANCISCO ASIS
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