Course Syllabus

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Questo corso esplorerà l'intersezione tra intelligenza artificiale, apprendimento automatico, tecnologie di comunicazione e tecnologia di consumo. Gli studenti acquisiranno una comprensione completa dello stato attuale delle tecnologie intelligenti per i consumatori, nonché del loro potenziale sviluppo e impatto futuro, comprese le tendenze emergenti, la ricerca all'avanguardia e le applicazioni reali. Gli argomenti trattati comprendono anche l'Internet degli oggetti, l'elaborazione di segnali, immagini e linguaggio naturale, i sistemi di raccomandazione e altro ancora.

Il corso è composto da una parte teorica e da una parte pratica.

La parte teorica mira a esplorare l'intelligenza artificiale, l'apprendimento automatico, le tecnologie di comunicazione e le tecnologie di consumo. La parte pratica mira ad approfondire l'ecosistema ICT dal punto di vista applicativo attraverso l'analisi di applicazioni di rilevamento intelligente in ambito domestico, nella sanità, ecc.

La parte pratica consiste in esercizi di base e avanzati che utilizzano framework di deep learning.

Moduli del corso:

  1. Course Presentation: An overview of the course structure, objectives, and key learning outcomes.
  2. Introduction to Intelligent Consumer Technologies**: A broad introduction to the field, exploring its history, current trends, and future potential.
  3. Signal Processing in Consumer Devices:
    • Speech Processing: Understanding how devices process spoken commands and interact vocally with users.
    • Image Processing: Techniques for enhancing, recognizing, and interpreting images by digital devices.
    • Inertial Processing: Exploration of how devices use inertial sensors to provide context-aware functionalities.
  4. Personalization Technologies: Examining how devices use data to customize and adapt their functionalities to individual user preferences.
  5. Communication Technologies: Insight into the technologies that enable devices to connect and communicate, including WiFi, Bluetooth, and NFC.
  6. Privacy in Intelligent Consumer Technologies: Critical analysis of privacy issues, focusing on data security, user rights, and ethical design principles.

Obiettivi Formativi:

Upon completion of this course, students will:

  • Understand the fundamental concepts of signal processing as applied to voice, image, and motion.
  • Gain insight into how consumer technologies are personalized and how they communicate.
  • Be able to identify and discuss the technological underpinnings of intelligent consumer devices.

Fondamenti di AI, Machine e Deep Learning, Fondamenti di tecnologie di comunicazione, Fondamenti di programmazione

L’insegnamento prevede una parte di lezioni teoriche che si terranno in aula, e una parte di laboratorio che si terranno in laboratorio e/o in aula e che richiederanno l’uso del proprio PC. Entrambe le parti saranno basate sia su didattica erogativa che interattiva.

• Scientific articles suggested by the teacher.
• Teachers' slides (http://elearning.unimib.it/)
• GitHub of the course:
1. https://github.com/paolonapoletano
2. https://github.com/CeLuigi

Primo Semestre

L'esame consiste nell'ideazione e nella realizzazione di un progetto assegnato dal docente (o autoproposto) sulle tecnologie di consumo intelligenti. Il progetto può essere sviluppato individualmente o in collaborazione con un collega. Il progetto sarà discusso sotto forma di presentazione orale e i docenti potranno porre domande sulle parti teoriche e pratiche del corso.

Paolo Napoletano, Lunedi from 14 to 16
Luigi Celona, Lunedi from 14 to 16
Ionel Eduard Stan, Lunedi from 14 to 16

IMPRESE, INNOVAZIONE E INFRASTRUTTURE
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This course will explore the intersection of artificial intelligence, machine learning, communication technologies and consumer technology. Students will gain a comprehensive understanding of the current state of intelligent consumer technologies, as well as their potential future development and impact, including emerging trends, cutting-edge research, and real-world applications. Topics will include also Internet of Things, signal, image, natural language processing, recommender systems, and more.

The course consists of a theoretical part and a practical part.

The theoretical part aims at exploring artificial intelligence, machine learning, communication technologies and consumer technologies. The practical part aims to deepen ICT ecosystem from an applied perspective by analyzing intelligent sensing applications in home environment, in healthcare etc.

The practical part consists in basic and advanced exercises using deep learning frameworks.

Course Modules:

  1. Course Presentation: An overview of the course structure, objectives, and key learning outcomes.
  2. Introduction to Intelligent Consumer Technologies**: A broad introduction to the field, exploring its history, current trends, and future potential.
  3. Signal Processing in Consumer Devices**:
    • Speech Processing: Understanding how devices process spoken commands and interact vocally with users.
    • Image Processing: Techniques for enhancing, recognizing, and interpreting images by digital devices.
    • Inertial Processing: Exploration of how devices use inertial sensors to provide context-aware functionalities.
  4. Personalization Technologies: Examining how devices use data to customize and adapt their functionalities to individual user preferences.
  5. Communication Technologies: Insight into the technologies that enable devices to connect and communicate, including WiFi, Bluetooth, and NFC.
  6. Privacy in Intelligent Consumer Technologies: Critical analysis of privacy issues, focusing on data security, user rights, and ethical design principles.

Learning Outcomes:

Upon completion of this course, students will:

  • Understand the fundamental concepts of signal processing as applied to voice, image, and motion.
  • Gain insight into how consumer technologies are personalized and how they communicate.
  • Be able to identify and discuss the technological underpinnings of intelligent consumer devices.

Fundamental of AI, Machine and Deep Learning, Fundamental of Communication Technologies, Fundamental of programming.

The teaching includes a part of theoretical lectures that will be held in the classroom, and a part of laboratory that will be held in the laboratory and/or classroom and will require the use of one's own PC. The two parts will be based both on delivery mode and interactive mode.

• Scientific articles suggested by the teacher.
• Teachers' slides (http://elearning.unimib.it/)
• GitHub of the course:
1. https://github.com/paolonapoletano
2. https://github.com/CeLuigi

First semester

The exam consists in the design and realization of a project assigned by the teacher (or self-proposed) about intelligent consumer technologies. The project can be developed individually or in collaboration with one colleague. The project will be discussed as an oral presentation and the teachers can ask questions about the theoretical and practical parts of the course.

Paolo Napoletano, Monday from 14 to 16
Luigi Celona, Monday from 14 to 16
Daniela D'Auria, Monday from 14 to 16

INDUSTRY, INNOVATION AND INFRASTRUCTURE
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Key information

Field of research
INF/01
ECTS
6
Term
First semester
Activity type
Mandatory to be chosen
Course Length (Hours)
56
Degree Course Type
2-year Master Degreee
Language
English

Staff

    Teacher

  • Luigi Celona
    Luigi Celona
  • Paolo Napoletano
    Paolo Napoletano
  • IS
    Ionel Eduard Stan

Students' opinion

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Bibliography

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Enrolment methods

Manual enrolments
Self enrolment (Student)

Sustainable Development Goals

INDUSTRY, INNOVATION AND INFRASTRUCTURE - Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation