Embedded Systems

Code:

CC4040

Acronym:

CC4040

Level:

400

Keywords
Classification	Keyword
OFICIAL	Computer Science

Instance: 2022/2023 - 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	13	Study plan since 2014/2015	1	-	6	42	162
M:ERSI	12	Official Study Plan since 2021_M:ERSI.	1	-	6	42	162
M:SI	15	Study plan since 2020/2021	1	-	6	42	162

Teaching language

English

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
• At least 40% for the grade of the mini-exams or for the grade of the exam "Recurso"

Calculation formula of final grade

The final grade is based on

1. lab assignement (NT): 10 points
2. two mini-exams (NME1,NME2): 5 points each

Final grade is:
NF = NT + NME1 + NME2

If NF <9.5, the student may go to the exam "Recurso" (ExR). In this case, the final grade will be:
NF = NT + NExR

Where NExR corresponds to the grade of the exam "Recurso".

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

The lab assignment grade may vary in minus/more 3 points between members of a group, based on an internal group auto-assessment and the performance evaluation by the teachers.

Special assessment (TE, DA, ...)

Se above in calculation formulas.

Classification improvement

The final grade "Melhoria de Classificação" (CM) is the sum of the grades obtained in the lab assignment (NT), and in the exam "Melhoria de Classificação" (NExM):

CM = NT + NExM

where each component has a maximum weighting of 10 points.

Observations

Jury: Sérgio Crisóstomo, Vítor Rodrigues