Embedded Systems

Code:

CC4040

Acronym:

CC4040

Level:

400

Keywords
Classification	Keyword
OFICIAL	Computer Science

Instance: 2020/2021 - 2S

Active?	Yes
Responsible unit:	Department of Computer Science
Course/CS Responsible:	Master in Computer Science

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
M:CC	23	Study plan since 2014/2015	1	-	6	42	162
MI:ERS	28	Plano Oficial desde ano letivo 2014	4	-	6	42	162
M:SI	11	Study plan since 2020/2021	1	-	6	42	162

Teaching language

Suitable for English-speaking students

Objectives

Introduction to the fundamental issues in the design and implementation of hardware and software solutions for embedded systems.

Present to students the capabilities and limitations of these systems and the rationale behind their wide usage in different enviroments.

Introduce the students to development in these platforms, providing and enviroment for work organization within the teams.

Learning outcomes and competences

At the end of the course, students should be able to:

• identify embedded systems, describe their importance in everyday life, the technological issues that arise with their development, and the current solutions and limitations;
• design, formalize, implement and analyse software applications for a range of embedded devices taking into account requirements, specificities of the systems and their limited resources.

Working method

Presencial

Program

• Introduction to embedded systems: applications, requisites, performance, design.


• Modelling Dynamic Behaviour: continuous, discrete and concurrent models.


• Embedded system design: sensors and actuators, processors, I/O devices


• Operating systems for embedded systems and real-time systems: processes, resource management, scheduling.


• Hardware and software pointers: design, development and debugging.


• Sensor networks: architectures, protocol-stack, operating systems, programming.

Mandatory literature

Edward A. Lee and Sanjit A. Seshia;; Introduction to Embedded Systems, A Cyber-Physical Systems Approach, 2015. ISBN: 978-1-312-42740-2 (Available online at: http://leeseshia.org)
Wolf Wayne Hendrix; Computers as components. ISBN: 9780123743978 (Sections from chapters 3, 4, 5)

Complementary Bibliography

Sohraby Kazem; Wireless sensor networks. ISBN: 978-0-471-74300-2 (Selected chapters, overview)

Teaching methods and learning activities

Theoretical classes presenting the fundaments of embedded systems and practical classes with an emphasis on programming these systems.

keywords

Technological sciences > Technology > Micro-technology > Microsystems
Technological sciences > Technology > Instrumentation technology > Sensors

Evaluation Type

Distributed evaluation without final exam

Assessment Components

designation	Weight (%)
Teste	50,00
Trabalho laboratorial	50,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Estudo autónomo	60,00
Frequência das aulas	42,00
Trabalho laboratorial	60,00
Total:	162,00

Eligibility for exams

Minimum grade requirements (satisfy both):

• At least 40% for the lab assignement (NT)
• At least 40% for the exame grade (either by mini-exams or final exam) (NE)

Calculation formula of final grade

The final grade is based on

1. lab assignement (NT): 10 marks
2. theo evaluation by 2 mini-exams or 1 exam
1. 2 mini-exams in the semester (NME1,NME2): 5 marks each
2. 1 final exam (NEF): 10 marks

Final grade is:
NF = NT + NE

Where:

• Exam Grade (NE) = Max(NME1+NME2, NEF)

Note that the final Exam is for improving the NME grades, and as such is not mandatory.

This weighting applies to all exams: normal, "recurso", special season, last year student or grade improvement.

Special assessment (TE, DA, ...)

Se above in calculation formula.

Classification improvement

Students wishing to improve their grades on the following year may do so on both components by re-doing the one they wish to improve.

Within the semester, the student can improve the NME grade by taking the final-exam.

Observations

Classes and the evaluation may be adjusted according to the evolution of the COVID-19 pandemic. These changes could be:

• (partial or total) remote classes;
• changes to the type of work to be done and/or the weights of the evaluation components.