Pervasive Computing

URL study guide

https://studiegids.vu.nl/en/courses/2024-2025/XB_40008

Course Objective

We expect that by the end of this course, students will be able to:
• Design a realistic smart system with the potential to benefit human lives. The system acquires and processes audio and video data and uses pattern recognition to make decisions that affect the environment accordingly. (Knowledge and understanding) (Applying knowledge and understanding) (Making judgments) (Lifelong learning skills)
• Build a simplified version of this system, based on programmable microcontrollers. (Applying knowledge and understanding) (Making judgments) (Lifelong learning skills)
• Work together in a team, collaboratively identifying not only the technical, but also the safety or ethical issues with their designs, and then sharing their challenges and discoveries through reports, presentations, and in-class demonstrations. (Lifelong learning skills) (Communication)

Course Content

Pervasive (or ubiquitous) computing is a trend based on Mark Weiser's vision of computers available "always and everywhere", embedded in everyday life. This course is an introduction to pervasive computing systems that assist people in their daily lives. Think about a self-driving car, a speech-controlled wheelchair, an automatic insulin pump for diabetic patients, or a navigation system for visually impaired pedestrians. These systems: 1. sense the context (time, user's location, blood sugar concentration, road scenery, etc), 2. recognize data patterns, reason and make intelligent decisions, and 3. act upon the environment, by controlling the wheels or the pump motor, suggesting the best route, or just notifying a caretaker. The main components of such a system are sensors, controllers, and actuators. In this course, the students will learn different techniques to acquire signals from the environment, process these raw signals in order to infer context by using machine learning, and to write software agents for control. During the practical sessions, the students will get experience with these techniques and build their own microcontroller-based smart system. Programming is done in MATLAB and C++. Guest lectures, given by researchers working in relevant fields are planned as well.

Teaching Methods

Lectures, mandatory practical sessions.

Method of Assessment

Compulsory practical assignments and a digital exam in TestVision. The final grade is calculated as Final grade = (0.5*PRAC) + (0.5*EXAM). A pass requires both components to be >=5.5. It is possible to resit the exam, but not the practical.

Literature

Silvis-Cividjian, N. (2017), Pervasive Computing
- Engineering Smart Systems, Springer International Publishing, ISBN 978-3-319-51654-7

Entry Requirements

Knowledge of programming in C++ is recommended.

Explanation Canvas

All materials can be found in Canvas.