New technology and market expectations have altered the game plan for both private and public players. Data and artificial intelligence must be used to make systems and services smarter, with a high degree of specialization and flexibility required. The changes impact the properties and architecture of the systems, as well as systems development – yes, the entire life cycle will change.
For the knowledge environment Smarter Systems, the software in technical systems is in focus, as a majority of the systems' functions are handled there. Software is at the heart of features in automobiles and trucks, manufacturing robots and machines, energy and electrical systems, and healthcare.
A complete knowledge environment
To meet the new challenges, businesses and organizations must expand their capabilities as well as their knowledge. Smarter Systems is a comprehensive knowledge environment focused on future systems and challenges. We identify challenges and offer tailored education and research in collaboration with our partners.Smarter Systems offers education at all levels, including the third cycle. We are responsible for the Master of Science in Software Engineering programme, among others. In addition, we provide a variety of professional education courses in our subject areas. All courses and programmes are closely related to and developed alongside the research conducted within Smarter Systems.
This is how we work
Smarter Systems collaborates closely with businesses and public partners on competency supply and knowledge development. Throughout the process, we collaborate with our partners. For example, initial explorative discussions may result in targeted educational initiatives or short or long-term research collaborations.
If you want to know more about how we can collaborate, contact research and project coordinator Diana Unander.
Smarter Systems formulates two high-level key objectives for smarter engineering of smarter systems that delineate the environment's broad research scope:
- To assure product capabilities in uncertain conditions.
- To devise engineering processes for perpetual adaptation and evolution.
The key objectives generate research questions for each of our four knowledge areas, which delineate the environment's knowledge gap. However, answering the research questions will require synthesis by a concerted effort from the knowledge areas on three themes:
- Assurances for unknowns.
- Smarter ecosystems.
Assurances for unknowns
The first theme centers on a line of integrated research that focuses on the key objective to assure product capabilities in uncertain conditions.
All four research groups below are active in this theme.
Project description: Assurances for decentralized cyber-physical systems
In this project, we investigate how to provide assurances for system behaviours under uncertainty. The research investigates goal models, assurance structures, and data-analytic techniques. We study mechanisms for coordinating online and offline reasoning and decision-making, with trade-offs for multiple conflicting goals, the required verification, and enactment.
The project will investigate the role of visual analytics in verification activities and the communication of verification results to stakeholders properly, for instance in a dynamic certification process. A key deliverable will be an approach for dynamic assurance cases.
Focuses on both key objectives: Assuring product capabilities in uncertain conditions, and devising engineering processes for perpetual adaptation and evolution.
The primary research groups below included in this theme are Engineering Resilient Systems (EReS), Data Intensive Software Technologies and Applications (DISTA), and Information and Software Visualization (ISOVIS).
Project description: Self-learning cyber-physical systems
The scalability and uncertainty that next-generation cyber-physical systems (CPSs) will face require such systems to learn over time. This project will build on recent progress in the machine learning field and study continuous lifelong learning – referring to the CPSs' lifetime – for next-generation CPSs. In particular, we will investigate lifelong meta-learning that allows CPSs to learn a learning approach from many related tasks. To this end, relevant CPSs or their constituents should be enhanced with a meta-learning system. Such a system offers:
- Facilities to store knowledge.
- A scheme to represent knowledge.
- A meta-learner that initiates and evolves a learner from experiences of executed tasks.
- A learner that exploits the learned knowledge to deal with new emerging situations that the component encounters.
A key deliverable will be a lifelong learning approach for smarter CPSs.
The third theme centers around a line of integrated research that focuses on the second key objective, devising engineering processes for perpetual adaptation and evolution.
The research groups below included in this theme are Engineering Resilient Systems (EReS) and AdaptWise.
Project description: Unified modeling approach for smarter cyber-physical systems
This project investigates models, techniques, and tools for smarter engineering processes, including models and model transformations that drive smarter systems and smarter engineering processes. The project investigates design and runtime models involved in the specification, adaptation, and evolution of smarter cyber-physical systems (CPS). Domain-specific languages and developer tools will be essential for creating and maintaining models. A key deliverable will be an integrated, model-based framework for adaptation and evolution.
The knowledge environment Smarter Systems features four knowledge areas, where the research is gathered in on research group each.
AdaptWise The AdaptWise research group conducts research on the foundations and engineering of self-adaptive software systems. The primary focus is on: i) dynamic architectures and runtime mechanisms…
Data Intensive Software Technologies and Applications (DISTA) The research group Data Intensive Software Technologies and Applications studies data-driven approaches, such as machine learning,…
Engineering Resilient Systems (EReS) The Engineering Resilient Systems (EReS) Research Lab conducts research in the area of system resilience. It focuses on investigating (and experimenting with)…
Information and Software Visualization (ISOVIS) The research group Information and Software Visualization mainly focuses on the explorative analysis and visualization of large and complex information…
Smarter Systems has a close connection to the industry graduate school Data Intensive Applications (DIA). The knowledge environment also features a number of research projects, for instance Aligning Architectures for Digital Twin of the Organization (Aladino).