IKT455 Introduction to Embedded and Edge Computing Systems
- ECTS Credits:
- 7.5
- Responsible department:
- Faculty of Engineering and Science
- Course Leader:
- Linga Reddy Cenkeramaddi
- Lecture Semester:
- Autumn
- Teaching language:
- English.
- Duration:
- 1 term
The course is connected to the following study programs
- Artificial Intelligence and The Internet of Things, Master's Programme
- Artificial Intelligence, 5-year master programme
Teaching language
English.Recommended prerequisites
Basic knowledge in sensors and signal processing, electronic circuit design and programming.
Course contents
The main goal of this course is to teach students the fundamental concepts in FPGA-based embedded system design and to clearly illustrate the way in which advanced FPGA-based systems are designed today, using computer aided design (CAD) tools. In this course, students will learn to implement and program the processors embedded in electronic devices. In the lab, FPGA boards will be used as target platforms. At the end of this course, students will be able to use electronic design automation tools and will have implemented a set of complete embedded systems on the FPGA boards. In addition, topics such as Introduction to Python programming and Python to FPGA will also be covered.
Learning outcomes
On successful completion of the course, the students should be able to
- Review and evaluate hardware and software platforms for Embedded and Edge Computing Systems.
- Demonstrate an understanding of microprocessor/microcontroller design.
- Demonstrate an understanding of FPGA implementation using VHDL.
- Design simple applications using VHDL and run these in FPGAs.
- Understanding how to build embedded systems for various applications.
- Hardware interfaces (inter processor communications, XADC, UART, I2C, SPI… etc.)
- Python programming for smart sensor systems and/or autonomous systems.
- Python to FPGA Implementation.
Teaching methods
The course is organized in combination of lectures, assignments, paper studies, labs, report writing and self-study. The tasks are done individually or in small groups with group supervision.
The workload for the average student is approximately 200 hours.
Evaluation
The person responsible for the course decides, in cooperation with student representative, the form of student evaluation and whether the course is to have a midway or end of course evaluation in accordance with the quality system for education, chapter 4.1.
Offered as Single Standing Module
Yes, if there are places available
Admission Requirement if given as Single Standing Module
Admission requirements for the course are the same as for the master’s programme in ICT.
Assessment methods and criteria
Graded portfolio assessment, individually or in groups. Groups are given joint grades. Information about the content of the portfolio will be given in Canvas at the start of the semester.