Embedded Systems (ES)

Programme website

Academic Coordinator: Matthias Becker, mabecker@kth.se

FIRST & SECOND SEMESTER

Programme website

Academic Coordinator: Dr Tomi Westerlund, tomi.westerlund@utu.fi

FIRST & SECOND SEMESTER

Also, at least 10 ECTS of elective studies need to be taken during the entry year to obtain at least 60 ECTS in total. For example, Data Analysis and Knowledge Discovery (5 ECTS), Algorithm Design (5 ECTS), or Machine Learning and Algorithmics Seminar (5 ECTS).

Programme website

FIRST & SECOND SEMESTER

Programme website

Academic Coordinator: Matthias Becker, mabecker@kth.se

SPECIALISATION: Embedded Platforms

Degree project 30 credits advanced level is mandatory during the spring term.
In accordance with KTH's regulations, a mandatory course in Research Methodology and Scientific Writing 7,5 credits needs to be included. This course can be taken anytime during the studies. Currently, the following courses are offered:

• Research Methodology and Scientific Writing - 7,5 credits (P1 only)
• Theory and Methodology of Science with Applications (Natural and Technological Science) - 7,5 credits

THIRD & FOURTH SEMESTER

Dr. Matthias Becker is Assistant Professor at KTH Royal Institute of Technology since November 2019. Since 2020, he is the coordinator of the Embedded Platform Track of the EIT Digital Master School program. His main research interests are the design and analysis of real-time and embedded systems. In this area, Matthias has co-authored over 50 publications in peer-reviewed international journals, conferences and workshops. He received his B.Eng. degree in Mechatronics/Automation Systems from the University of Applied Sciences Esslingen, Germany in 2011. In the year 2013 he got his M.Sc. degree in Computer Science specializing in embedded computing from the University of Applied Sciences Munich, Germany. He received his Licentiate and PhD degree in Computer Science and Engineering from Mälardalen University in 2015 and 2017 respectively. Matthias has been a visiting researcher at CISTER - Research Centre in Real-Time and Embedded Computing Systems in Porto, Portugal for two months in 2015 and for three months in 2016 and he has been postdoctoral researcher at KTH Royal Institute of Technology in 2018 and 2019.

Programme website

Academic Coordinator: Tamás Dabóczi, daboczi@mit.bme.hu

SPECIALISATION: Embedded Artificial Intelligence

The specialisation aims to educate engineers who develop intelligent applications based on embedded systems, using artificial intelligence methods. Application examples include (1) from the automotive field Advanced Driver Assistance Systems (ADAS) and support for different levels of autonomous driving; (2) from the healthcare field medical signal processing and sports/lifestyle support using wearable electronics; (3) from the smart manufacturing field predictive maintenance; (4) from the development field model-in-the-loop, hardware-in-the-loop, and software-in-the-loop testing. Engineers active in this area should have an understanding of hardware platforms including programmable circuits and hardware accelerators, as well as the intelligent signal processing methods and the artificial intelligence algorithms running on them.

The specialisation has the following main goals:

• It aims to present the sensing of physical signals and the methods for pre-processing the raw sensor data in embedded systems. It introduces the most commonly used sensors and the disturbing and distorting effects in sensing, and introduces the common steps of signal processing, independent of the applications.
• It presents artificial intelligence based algorithms for information processing in embedded systems. Its special focus is the understanding of data derived from physical processes. In the implementation of algorithms it addresses the possibility of implementing them on embedded hardware platforms and accelerators.
• The specialisation also presents methods for developing intelligent embedded systems that are critical from the point of view of functional safety. Students learn about the life cycle models of safety-critical systems as defined in development standards, design principles, safety and reliability analysis to justify design decisions, and systematic testing and verification methods.

THIRD SEMESTER

FOURTH SEMESTER

Electives Courses

Total credits for the whole exit year: 60 ECTS.

There is a strong cooperation with the industry in the field of intelligent embedded systems. The most appropriate link to this cooperation is the internship and thesis work at industry partners. Many large automotive research centres reside in Budapest (thyssenkrupp, Bosch, Knorr-Bremse, Continental), and also other embedded system developers like Ericsson.

Prof. Tamás Dabóczi is the Head of the Department of Measurement and Information Systems, Budapest University of Technology and Economics, Budapest, Hungary. Besides coordinating the EIT Digital Master School’s former Critical Embedded Systems and the current Embedded Artificial Intelligence specialisation, he has been involved in developing four new Embedded Systems (ES) specialisations both at BSc and MSc level in the past years. He teaches Applications of data processing, Real-time systems, Embedded and ambient systems, and Information processing within ES tracks.

His research area is embedded systems, with special emphasis on information processing and numerical correction of distortions. He has published around 80 papers in areas of signal processing, intelligent embedded systems, and cyber-physical systems. He has been visiting scientist at Swiss Federal Institute of Technology (ETH, Zürich, Switzerland), at Technical University of Karlsruhe (Karlsruhe, Germany), and at National Institute of Standards and Technology (NIST, Gaithersburg, MD, USA). He cooperates with the leading international R&D companies in Budapest like thyssenkrupp, Bosch and Ericsson. Prof. Dabóczi has led many national and international research- and industrial development projects.

Programme website

Academic Coordinator: Prof Luigi Palopoli, luigi.palopoli@unitn.it

SPECIALISATION: Real-Time Systems and Design of Cyber-Physical Systems

UNITN provides a specialisation on real-time systems, a particular class of embedded systems that are required to operate in close connection with the environment. The prominent issue for a successful design of a real-time system is its predictability: the system has to be bug free to the maximum degree allowed by the current industrial practice, it has to react to external stimuli in a predictable time and has to optimize resource utilization. Students will be exposed to the most recent trends on safety critical systems, embedded control systems and sensor networks.

Track 1: Real-Time Embedded Systems

Real-time systems are a particular class of embedded systems that are required to operate in close connection with the environment. The prominent issue for a successful design of a real-time system is its predictability: the system has to be bug free to the maximum degree allowed by the current industrial practice, it has to react to external stimuli in a predictable time and has to optimize resource utilization. To be able to develop a real-time system, a student has to be in command of several foundational disciplines on software development, computing architecture, model-based design. In addition, he/she will be exposed to the most recent trends on safety critical systems, embedded control systems and sensor networks. This rich basis of knowledge is constructed through the mandatory courses and elective courses, while a wide choice of optional courses enable the students to enrich their expertise in areas that are tightly related to embedded systems (e.g., distributed systems, security, software technologies). Laboratory experiences in which the students are required to operate on robotic and multimedia application contribute to the construction of practical skills that prove essential in the daily work experience on embedded real-time systems.

Track 2: Methodologies for Cyber-Physical Systems Design
Cyber-physical systems are a new generation of systems with integrated computational and physical abilities that interact with humans through a number of new modalities and operate in open environments. The potential applications of cyber-physical systems are beyond count; a few examples are next-generation airplanes and space vehicles, hybrid gas-electric vehicles, fully autonomous urban driving, and prostheses that allow brain signals to control physical objects. Over the years engineering disciplines have defined powerful methods to design systems able to operate in the environment (e.g., frequency domain techniques, optimal control, stochastic control etc.). Meanwhile, research in computing systems has produced a wealth of innovative ideas on how to exploit modern computing architectures to their full extent (e.g., using reconfigurable hardware and optimised compilers). The challenges posed by the design of cyber-physical systems call for new ideas and methods that stay at the confluence between once separate disciplines (Engineering and Computer Science). Additional contributions can arrive from social sciences through the establishment of Human Machine Interaction as a new science in its own right. Receiving exposure to these disciplines is crucial for a study programme tailored for future professional operating in this area, but the complex expertise required can be constructed only through hands-on experience on a real-life design problems of cyber-physical systems. This is the objective of this specialisation track.

Prof Luigi Palopoli is the coordinator of Embedded Systems major at Trento University, Italy. He is associate professor and received his PhD degree from the Scuola Superiore S. Anna, Pisa, Italy, which is one of the most active university sites worldwide in real-time systems. He has a strong network of collaborations with several institutions working on real-time scheduling, control and robotics. He is the coordinator of an EU project on assistive robotics (www.ict-dali.eu). The research on embedded system in Trento is carried within the EECS research program at the DISI department. Research activities in embedded systems are on sensor networks, design methodologies, real-time control and robotics.

Programme website

Academic Coordinator: Dr Tomi Westerlund, tomi.westerlund@utu.fi

SPECIALISATION: Smart Systems

In the Smart Systems specialisation, students will get a strong knowledge base for designing and implementing autonomous and intelligent systems. For example, the programme focuses on various hardware and software architectures, hardware accelerators, reconfigurable circuits, and device-specific programming, with preference to integrate intelligence and sensors into actuators. Individual and group assignment projects are related to several courses and are an integral part of the courses. Graduate students will be able to meet the new challenges posed by the increasing complexity of the systems.

The preference is to select the elective courses from the above list, but depending on the time of the internship, a student should discuss with Tomi Westerlund before enrolling the course. The mandatory specialisation studies include a Master’s Thesis (30 ECTS) and I&E Study (6 ECTS).

Upon completion of the Smart Systems specialisation, students will be able to design and implement hardware accelerators and embedded systems for different sets of sensors and data processing approaches. A student will understand the basic concepts of robotic perception, mapping and navigation and acquire data from different sensors and convert it for visualization and analysis to be used with real robots. Students will be able to utilise different approaches for the design of control systems in robotics.

The local coordinator for the specialisation, Dr Tomi Westerlund, is the leader of the Turku Intelligent Embedded and Robotic Systems (https://tiers.utu.fi) research group at the University of Turku. He has a long experience in education and research in the field. His main research interest is in Multi-robot Systems and Autonomous Robots. Specifically focusing on the collaborative operation of heterogenous robots and UAVs/UGVs, localization and mapping in dense urban and unstructured environments by utilizing artificial intelligence at the edge (embedded and distributed intelligence).

Academic Coordinator: Peeter Ellervee, peeter.ellervee@taltech.ee

SPECIALISATION: Distributed Control for Embedded Systems

The main focus of the courses is on control software supported by additional topics like security, communications, etc. All courses are electives, except the master thesis and internship in the last semester. While comparing against the other exit years, the main differenced can be outlined as distributed control for embedded systems – systems that consist of multiple embedded devices and controlled in a distributed manner.

THIRD SEMESTER

Four courses to be selected from the two blocks above, courses from the entry year should guide the selections.

FOURTH SEMESTER

Industrial Training - internship at a company (6 ECTS) in parallel with the master thesis work (24 ECTS).