AI Methods for Sensor-Based Activity Recognition and Context-Awareness

A.Y. 2021/2022
Course offered to students on the PhD programme in
2
ECTS
10
Overall hours
Lesson period
November 2021
Language
English
Lead instructor: Gabriele Civitarese
The goal of this course is to introduce the main concepts about techniques that analyze data from several sensors (e.g., the ones on mobile/wearable devices, or in smart-homes environments) to automatically detect the user's context (e.g., the activities performed, the visited places, the surrounding environment). These methods are crucial to develop applications that automatically adapt to the users's context. In particular, this course will focus on one of the most interesting problems in this area: the automatic recognition of human activities. Indeed, monitoring the activities that humans perform in ther daily life enables several important applications, that range from healthcare (e.g., remote monitoring of elderly subjects) to well-being (e.g., monitoring the physical activity level). Activity recognition techniques may be based on machine learning, knowledge-based reasoning, and hybrid approaches (i.e., a combination of machine learning and knowledge-based reasoning). This course will present the main methods and research results in this area, and it will discuss the most relevant open research problems.
Basics of Machine Learning and Logic
Assessment methods
Giudizio di approvazione
Assessment result
superato/non superato
How to enrol

Deadlines

The course enrolment deadline is usually the 25th day of the month prior to the start date. More specifically:

  • 27 December 2021 for courses starting in January 2022
  • 25 January 2022 for courses starting in February 2022
  • 25 February 2022 for courses starting in March 2022.

Deadlines for enrolment in other courses will be announced as soon as possible.

How to enrol

  1. Access enrolment on PhD courses online service using your University login details
  2. Select the desired programme and click on Registration (Iscrizione) and then on Register (Iscriviti)

Ignore the option "Exam session date” that appears during the enrolment procedure.

Contact

For help please contact [email protected]

Professor(s)
Reception:
send email for an appointment
Room 7021, via Celoria 18