CMSE423 - Embedded System Design

 Instructor:

Assoc. Prof. Dr. Mehmet Bodur

Catalog Description 

Application areas, common characteristics, and challenges in embedded system design. Requirement specification, models of computation and modeling methods such as automata, and statecharts, data flow modeling. High-end Embedded Systems (HES) hardware, ASICs, processors, memories, communication, conversion between analog and digital inputs and outputs, sampling, and actuators, secure hardware. Embedded operating systems, general requirements, RTOS, virtual machines, real time databases. IoT projects and implementation. Evaluation and validation, performance evaluation, energy and power models, simulation, rapid prototyping, emulation. Test, test pattern generation, evaluation of test patterns, design for testability. (CMPE223). 


Textbook(s)  

E.A. Lee and S.A. Seshia, (PDF) Introduction to Embedded Systems, A Cyber-Physical Systems Approach, 2Ed, MIT Press, 2017.
Ibrahim, Dogan, Advanced PIC microcontroller projects in C: from USB to RTOS with the PIC18F series, Newnes, Elsevier, 2008

Indicative Basic Reading List 
 M. Bodur. Course Notes by
John B. Peatman, Embedded Design with the PIC18F452 Microcontroller, Pearson Education, 2003


Topics Covered and Class Schedule

(4 hours of lectures per week)

W 1 ( ) Trends in Embedded Systems Industry, application areas. 
W 2 ( )   Common challenges in High-end Embedded Systems (HES) design and applications W01.2
W 3 (  )   Importance of modeling the real world, and cyber world, for given requirement specifications,
W 4 (  ) Modeling the physical world: physical laws and constraints, kinematics, and dynamics. (quiz-1)
W 5 ( ) Discrete Systems Modeling, Discrete and Hybrid systems. 
W 6 ( ) Commons of HES Projects, analog, digital, and hybrid approaches 
W 7 ( ) HES hardware, communication, analog and digital inputs and outputs, actuators 
W 8 (  ) Midterm Exam
W 9 (  ) Modeling tools and methods: automata, and statecharts, data flow modeling, sampling, and secure hardware.
W 10 (  ) RTOS, virtual machines, real time databases.  (Midterm Exam)
W11 (  )  IoT projects and implementation. Team project discussions.
W 12 ( )  Evaluation and validation, performance evaluation, energy and power models  (quiz-2)
W 13 ( )  Simulation, emulation, and rapid prototyping.  
W 14 (  )  Test, test pattern generation, evaluation of test patterns, design for testability. 
W 15 ( ) Student Prototype Project Discussions, (Final Exam)

Laboratory Schedule: 

(2 hours of laboratory per week) for arduino (PP89) 380MBytes

W 3-4   (Mar 4 / Mar11) Modeling of vehicle speed and speed control using Signal Flow Diagrams (PDF)
W 5   (Mar 18) Modeling of vehicle orientation and line tracking control using Signal Flow Diagrams
Week 6   ESD application (Arduino),  LED and motor interfacing for vehicle speed control. 
Week 6  ESD application (Arduino or PIC), interfacing of optical detectors for vehicle line tracking.
Week 9 RPB2 remote access to ports, 
Week 10 RPB2 traffic light control,
Week 11 Discussions on Team Projects -1,
Week 12 Discussions on Team Projects -2, 


Course Learning Outcomes

Upon successful completion of the course, students are expected to have the following competencies

  1. Perform kinematic and dynamics modeling of simple physical systems for HEES design (1).
  2. Know typical structure of a HEES, and use simple digital i/o ports in C (1).
  3. Know analog, digital and hybrid approaches, and use a typical AD converter of a HEES (1).
  4. Know typical control, and monitoring approaches for High End Embedded Systems (HEES)  (1).
  5. Know common cyber modeling tools and methods, and apply FSM techniques on HEES (1).
  6. Know common principles of IoT systems, and apply them on an IoT platform (1).
  7. Analyse technical requirements and design a HEES using indicators, displays, sensors and actors (1).
  8. Analyse and comment on ethical social and environmental responsibilities of an embedded system design (4).
  9. Practice an embedded system preliminary design starting from technical requirements (2).
  10. Practice an embedded system design in teams including its tests (5).
  11. Prepare a team design report to document hardware/software development of a HEES, including its tests (6).

Assessment

Method Percentage
Labs 10%  (Lab projects each 5%) 
Quiz, and Homework
 15% (HW. 5%)
Midterm Exam
 
20% (All teams quizzes are 30%)
Design Project
 25% (Team Projects,
Report 15 %, Individual evaluation 10%)
Final Examination
 
30% (Three parts, 15% short questions, 10% longer questions, 5% oral questions)

Quiz and HW grading: Unscheduled 10-min Pop Quizzes at the end of the lecture hours. Two home works before midterm and before final. Reading home-works, and small project-home works related to details of the calculations for HLES design.

Lab grading: Six labs (0.5p each),  reports of  labs (0.5p each), and hardware implementation (about 4p). Missing more than 2 labs resets lab grade.

Policy on makeups: For eligibility to take a makeup exam, the student should bring a valid excuse (medical report) within 3 working days of the missed exam. No make-up exam for quizzes. Final and midterm make-up exams are conducted after final exam. Students may get NG if they miss both midterm and final exam.

Policy on cheating and plagiarism: Any student caught cheating at the exams or assignments will automatically fail the course and may be sent to the disciplinary committee at the discretion of the instructor.

Updated by: Assoc. Prof. Dr. Mehmet Bodur    Update Date: 19.04.2019

Contribution of Course to ABET Criterion 5

Credit Hours for:

 Mathematics & Basic Science : 0
Engineering Sciences and Design : 4
General Education : 0 

 

Relationship of the course to Program Outcomes


1.  an ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics

2. an ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors

4. an ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts

5. an ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives

6. an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions



Prepared by: Assoc. Prof. Dr. Mehmet Bodur
Date Prepared: 19 April 2019