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Embedded Systems
The research specialisation of Embedded Systems focuses on developing the technology that is used to control various products such as cars, robots and machines. This research ranks internationally among the best in the world.
The researchers work close to industry and create technology which makes it possible to increase safety in health care, reduce risks in industry and simplify everyday life through smart solutions in our homes. A large part of this research is conducted in cooperation with industrial partners such as ABB and Volvo.
Six areas of focus
The research is conducted in the following areas:
- Real-time systems
- Software development
- Dependable systems
- Verification and validation
- Sensor Systems and Health
- Robotics and Avionics
Furthermore research is conducted in wireless communication and artificial intelligence.
Third-cycle studies - our PhD programmes
Apart from conventional research studies within the subjects of Computer Science and Electronics, two company research schools in Embedded Systems are conducted in collaboration with a number of industrial companies. These company research schools give staff at the companies the opportunity to further educate themselves as researchers and to take doctoral degrees.
- ITS EASY is a company research school in Computer Science and Software Technology in which eight companies participate. This is funded by the Knowledge Foundation.
- ITS ESS-H is a company research school in Embedded Sensor Systems for Health, which is funded by the Knowledge Foundation.
- Array is an company research school in automation, developed in collaboration with several of the world's leading automation companies. It is funded by the Knowledge Foundation.
Research profile
A research profile is a long-term strategic venture that involves researchers from several areas of skills. MDU's research profiles are conducted in collaboration with the private sector, which means that representatives from the companies involved work side by side with the researchers in the profile. Its purpose is to make use of one another’s skills and thereby achieve a better result.
Research groups in Embedded Systems
Artificial Intelligence och Intelligent Systems
Foundational and applied research in Artificial Intelligence and Machine Learning for Intelligent Systems for both industry, medical and business applications. The research focuses on methods and techniques enabling learning, reasoning, experience reuse, and experience sharing. We work with both autonomous AI applications as well as decision support systems.
Read more about Artificial Intelligence och Intelligent SystemsAutomated Software language and Software engineering
The ASSO research group focuses on automating the engineering of software languages and software by applying advanced computation and data manipulation techniques.
Read more about Automated Software language and Software engineeringBiomedical Engineering
The research within the Biomedical Engineering group focuses on reliable non-invasive physiological data acquisition and signal processing. The aim is to find solutions to real problems and the projects are performed in close collaboration with the public sector.
Read more about Biomedical EngineeringCertifiable Evidences and Justification Engineering
This group performs research on languages, techniques, metrics, and processes for engineering evidence(s) and justifications for the purpose of certification/selfassessment.
Read more about Certifiable Evidences and Justification EngineeringComplex Real-Time Embedded Systems
We focus on execution and analysis of real-time systems, with a particular focus on multiprocessor scheduling techniques, synchronization protocols, predictable execution of real-time systems, compositional theory and technology, and similar topics related to predictability of real-time systems.
Read more about Complex Real-Time Embedded SystemsCyber-Physical Systems Analysis
The research group is focused on analyzing cyber-physical systems, as concurrent and distributed systems where embedded computers and networks monitor and control the physical processes.
Read more about Cyber-Physical Systems AnalysisData Communication
Data Communication, a part of the Division of Networked and Embedded Systems.
Read more about Data CommunicationDependable Software Engineering
Methods and processes for engineering dependable software systems.
Read more about Dependable Software EngineeringFormal Modelling and Analysis of Embedded Systems
Focusing on formal modelling, analysis, and verification techniques for real-time embedded systems. In particular, formal syntax and semantics of componentbased and service oriented models with extra-functional properties such as time or resources.
Read more about Formal Modelling and Analysis of Embedded SystemsHeterogeneous systems - hardware software co-design
The group aims to boost exploitation of heterogeneous systems in terms of predictability, effective development and efficient software-hardware integration for next-generation intelligent embedded systems.
Read more about Heterogeneous systems - hardware software co-designIndustrial Software Engineering
Focusing on engineering of complex software-intensive embedded systems, covering the entire lifecycle and including technologies, methods and processes. Particular emphasis on component- and model-based software engineering for embedded systems.
Read more about Industrial Software EngineeringLearning and Optimisation
The group aims to explore the synergy between machine learning and optimization to achieve collaborative effects in building highly efficient and smart systems.
Read more about Learning and OptimisationModel-Based Engineering of Embedded Systems
Development of methods and tools for model-based engineering of embedded systems. Including: models for architectural and behavioral descriptions of system and requirements for systems, techniques for analyzing and transforming models, and runtime architectures for resource efficient, predictable embedded systems.
Read more about Model-Based Engineering of Embedded SystemsProgramming Languages
Worst-case execution time analysis, as well as design and analysis of languages for real-time and embedded systems. Focusing on static program analysis for embedded systems, specializing in Worst-Case Execution Time analysis.
Read more about Programming LanguagesReal-Time Systems Design
Focusing on design methods, architectures, and communication for real-time system, with current emphasis on functional safety, cybersecurity, adaptive real-time systems, and software testing.
Read more about Real-Time Systems DesignRobotics
The robotics research group is mainly conducting research in the area of autonomous collaborating systems.
Read more about RoboticsSafety-Critical Engineering
Focusing on bridging the theoretical foundations of dependability and industrial software development practices, with an emphasis on the technology and process aspects of complex dependable systems.
Read more about Safety-Critical EngineeringSoftware Testing Laboratory
Testing of embedded software, empirical studies of software testing, test automation and model-based testing.
Read more about Software Testing LaboratoryUbiquitous Computing
Computing as environmental process and environment as computing devices.
Read more about Ubiquitous ComputingMore information about Embedded Systems
Fore more information about Embedded Systems,
please contact Research leader Mikael Sjödin.
Ongoing research projects
AIDOaRt är ett tre år långt europeiskt projekt som involverar 32 organisationer, grupperade i kluster från sju olika länder, med fokus på AI-förstärkt automatisering som stöder modellering, kodning, testning, övervakning och kontinuerlig utveckling inom Cyber-Physical Systems (CPS) eller inbyggda system.
Project manager at MDU: Gunnar Widforss
Main financing: ECSEL, VINNOVA
Detta projekt kommer att undersöka hur man kan kombinera avancerad akademisk forskning med industriellt relevanta problem och metoder för att tillhandahålla förbättrade och kostnadseffektiva lösningar som är direkt tillämpliga i industrin.
Project manager at MDU: Alessandro Papadopoulos
Main financing: Stiftelsen för Strategisk Forskning (SSF)
The INDTECH project is an industrial graduate school at MDU, focusing on the implementation of Industry 4.0 and applied AI in production systems in collaboration with 12 partner organizations consisting of leading industrial companies, research institutes and technology centers and supporting organizations such as AI Sweden, PiiA, Automation Region and Blue Institute. INDTECH Industrial Technology Graduate School offers advanced training in the field of industrial digitization, a new and emerging field of technology that revolutionizes all aspects of the manufacturing and process industry
Project manager at MDU: Markus Bohlin
Main financing: KK-stiftelsen
The purpose of this project is to study how system developers can design their products to have capabilities that make them effective in an SoS context, and how SoS designers can compose the available elements, called constituent systems (CS), as efficiently as possible to achieve a particular mission.
Project manager at MDU: Jakob Axelsson
Main financing: KKS / Knowledge Foundation
The project aims to increase the efficiency of analysis and management of risks in critical societal interconnected systems-of-systems. This is achieved by risk analysts, who, with a certain amount of work, become able to identify and reduce significantly more risks than they can manage with today's methods and the same amount of effort.
Project manager at MDU: Jakob Axelsson
Main financing: Myndigheten för samhällsskydd och beredskap (MSB)
Detta projekt kommer att utveckla självövervakande och kontinuerliga inlärningsmetoder för att främja en bredare tillgänglighet av datadrivet prediktivt underhåll i kraftnät.Kontinuerligt (och livslångt) lärande har hög potential att stödja mer grundade och exakta underhållsbeslut genom att hantera förändrade förhållanden i kraftnät, som t.ex. åldrande av elektriska komponenter. Fallstudier med data som samlats in från kraftnät kommer att utföras för att utvärdera effektiviteten i de föreslagna metoderna.
Project manager at MDU: Ning Xiong
Main financing: SSF