The course investigates the use of sensors, embedded in mobile computation devices (e.g. smartphones, smartwatches, etc.), for understanding a user’s context, modelling a user’s behaviour, and devising novel applications based on the acquired information. The course equips students with tools for a practical realisation of mobile sensing. The framework of choice is Android, the most popular mobile operating system. Within Android, the course investigates methods for one-off and periodic sensing of different sensors, data pre-processing, and on-device machine learning. The core component of the course (90% of the final mark) is a practical project where students will implement a state-of-the-art mobile sensing solution.
The solutions will be developed in small (two people) teams, will be continuously guided by the instructors, progress will be checked via two in-class presentations, and the final report, in the form of a workshop paper, that will be written for each of the projects.
Lectures are accompanied by mandatory labs, where students will implement theoretical concepts in practice. Certain labs will be based on the analysis of publicly available mobile sensing research datasets, some will cover Android programming concepts, while some labs will be focused on specific issues that emerge during the students’ project development. Finally, each student will be in charge of presenting a seminal research paper from the field, and this presentation will carry 10% of the final mark. This course has one short oral exam and no written exams.
The course is taught in English.
