Mobile and Embedded Computing

linfo2146  2021-2022  Louvain-la-Neuve

Mobile and Embedded Computing
5.00 credits
30.0 h + 15.0 h
Q2
Teacher(s)
Sadre Ramin;
Language
English
Main themes
  • Cellular networks
  • Internet of things and sensor networks
  • Mobile and embedded applications
Learning outcomes

At the end of this learning unit, the student is able to :

1 Given the learning outcomes of the "Master in Computer Science and Engineering" program, this course contributes to the development, acquisition and evaluation of the following learning outcomes:
  • INFO1.1-3
  • INFO2.4-5
  • INFO5.2-5
  • INFO6.1, INFO6.3
Given the learning outcomes of the "Master [120] in Computer Science" program, this course contributes to the development, acquisition and evaluation of the following learning outcomes:
  • SINF1.M1
  • SINF2.4-5
  • SINF5.2-5
  • SINF6.1, SINF6.3
Students completing this course successfully will be able to
  • Explain how in mobile cellular and sensor networks operate
  • Describe the key problems that affect these environments and identify their impact on the mobile and embedded systems
  • Integrate and combine the above concepts in order to solve complex mobile computing problems.
 
Content
  • Wireless sensor networks
  • Internet of Things
  • Programming embedded systems with network connection
  • Network protocols for resource-constrained devices
  • Introduction to mobile networks
Teaching methods
The course consists of a series of lectures and accompagning exercises and project(s). The teaching method can change depending on the circumstances and the number of participating students or for other reasons. Face-to-face classes as well as remote teaching or a mix of the two methods are possible.
Evaluation methods
Mode of evaluation for the June session:
  • Group project (40% of the final mark)
  • Exam (60% of the final mark)
If the student fails to obtain at least 50% of the total points in the June session, the student can repeat only the failed part(s) (exam and/or project) in the August session. However, in that case the project has to be done alone and a new topic might be assigned.
Other information
Background:
  • LINFO1252 (basic knowledge in C and computer systems)
  • LINGI1341 (or a similar basic networking course)
Online resources
Moodle and/or Teams
Faculty or entity
INFO


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Master [120] in Data Science Engineering
DATE2M
5
Master [120] in Electrical Engineering
ELEC2M
5
Master [120] in Computer Science and Engineering
INFO2M
5
Master [120] in Data Science: Information Technology
DATI2M
5
Master [120] in Computer Science
SINF2M
5