95639 - INDUSTRY 4.0

Conoscenze e abilità da conseguire

The general objective of this course is to provide the general conceptual and technological framework that characterise Industry 4.0, focusing in particular on Internet of Things (IoT), Industrial IoT and Computer Vision and their application in digital transformation contexts. At the end of the course, a student: - has a global understanding about the big picture related to Industry 4.0 - knows the main principles, technologies and standards about Internet of Things (IoT) and Industrial IoT, integrated with contents delivered by other courses (e.g. service oriented architectures, API, web, cloud) - knows some main state-of-the art directions in this context. Examples are Web of Things, Digital Twins - knows the main application domains and concrete case studies concerning the application of IoT and Industrial IoT - knows the main topics in the field of computer vision (e.g. object detection and classification) and their applications - knows state-of-the art approaches and technologies in the context of computer vision, with reference to both classic techniques for image representation and deep learning based solutions - is able to analyse and evaluate the application of the models and technologies, as well as to build projects and prototype technologies, given a Digital Transformation context/problem

Contenuti

This course covers fundamental concepts, technologies, drivers, trends, and implications of Ubiquitous Computing in the context of the Industry 4.0 and Digital Transformation.

Overarching Learning Goal: Students know the cross‑disciplinary drivers, and current state of the field of (industrial) Digital Transformation. They recognize patterns, can evaluate technology‑driven business models, and can make educated estimates regarding future trends in the post‑PC age.

Overarching Competency Goal: Students are capable of ideating, implementing, and presenting ideas and approaches in the context of Digital Transformation, Industry 4.0, and Ubiquitous Computing.

Learning Goals

 Students know about the current scope, limitations, expected developments, and impact to industrial businesses of the following domains and technologies:

Internet of Things and Web of Things

Autonomous Agents

Mixed Reality technologies and (mobile) gaze tracking

Testi/Bibliografia

Relevant literature will be announced during the lectures.

Metodi didattici

This course features lectures, exercises, and a multi-week project. These course elements are designed to convey theory as well as hands‑on experience and are structured in three phases:

• The first phase starts with an introduction to digital transformation and its drivers and then goes in-depth on central aspects of modern computing in digital transformation contexts: Sensing, Internet and the Web of Things, Autonomous Systems, Human‑in‑the‑Loop Methods, and System Integration.
• The second phase brings students to the forefront of current research developments through a seminar where the students present and discuss current published research papers.
• The final phase of the course is dedicated to application and creativity, where the students will apply their learnings in the context of Capstone Projects. Following a structured ideation process and based on the methods and technologies covered in the course, the students will submit and present their project proposals in the field of Industry 4.0 and Digital Transformation.

Modalità di verifica e valutazione dell'apprendimento

Available assessment methods are a written exam, an implementation exercise, a seminar talk, and a final project presentation. The specific assessment methods will depend on the number of enrolled students.

Evaluation criteria and grading:

• 18-23:the student shows sufficient knowledge about the basic concepts and a sufficient technical and methodological preparation;
  
• 24-27: the student shows good knowledge about the conceptual part and adequate capabilities of applying concepts in practice;
  
• 28-30: the student shows good knowledge about the conceptual part, good critical and analytical skills, a good capability of applying concepts in practice by means of a satisfactory technical and methodological preparation;
  
• 30L: the student shows excellent knowledge about the conceptual part, extensive critical and analytical skills, remarkable abilities in applying concepts in practice by means of a robust technical and methodological preparation.

Strumenti a supporto della didattica

All required materials will be made available as part of the lectures and exercises.

Orario di ricevimento

Consulta il sito web di Danai Charitini Vachtsevanou