Safety-critical and autonomous systems
Courses included in the programme:
Choose four courses to complete your minor studies.
Apply before Aug 18, 2019
Within this course we will explore the fundamentals of sensing techniques, including digital image processing, light detection and ranging (LIDAR), in the context of emerging technologies such as autonomous navigation. We will also:
- Analyse the performance of active remote sensing techniques such as those using lidar and radar.
- Analyse the performance of passive remote sensing techniques such as those using digital image processing.
- Apply engineering knowledge and techniques to the design, assembly, and evaluation of multidimensional sensing instrumentation.
Apply before Oct 13, 2019
The aim of the course is to gain basic knowledge in computer aided modeling and control of discrete event systems: automata, formal languages, blocking, controllability, observability, modularisation and algorithms.
Learning outcomes: Modeling of simple discrete events using automata, analysis and design of supervisory systems for these.
Apply before Oct 13, 2019
Prerequisites: General basic IT knowledge. Basic knowledge on computer architecture, computer network, system design and operating systems. Basic knowledge on programming (e.g. courses in C/C++ or Java programming).
After a completed course the student has acquired the skills needed to analyse the real-time and resource constraints of a real-time system design to ascertain the consistency and schedulability of the system.
The student has acquired the skills needed to suggest changes to the specification or implementation strategy to ensure that the real-time constraints are satisfied.
The student has also acquired skills needed to design systems such that they satisfy real-time requirements.
The course explores the fundamentals of safety systems engineering and the connection to advance methodologies to design complex technological systems. It focuses on teaching new approaches, frameworks and theories to analyse, design, deploy and manage engineering systems with focus on safety. This course introduces new techniques for assisting the determination of requirements in software design and development. It also presents and applies new tools for hazard and risk analysis and for designing safety-guided processes with applications in software and system logic design.
After completing the course the student should understand
- principles of designing, modelling and verification of safety-critical systems,
- the principles of safety analysis, risk assessment,
- main issues in ensuring safety of software-intensive safety-critical systems.
Bringing a laptop to the course is recommended, but not mandatory.
Different degrees of autonomy are pervasive in modern ICT systems. The driver towards more autonomy is the need to handle the complexity of the systems while at the same time increase the quality (efficiency, safety, etc) of the resulting system. For example the promise of autonomous vehicles is to increase service levels for customers, while at the same time decreasing the overall carbon footprint of traffic. Analogously in datacenters autonomy is used to guarantee QoS for services, while optimising the energy-expenditure of the computing infrastructure.
In this course we will study the principles of autonomy for ICT systems using the Mape-K reference architecture. We will present a comprehensive framework for the design of autonomic systems irrespective of their levels of autonomy and application areas.
The course consists of lectures, exercises and a project. The project is either a research project reported in writing, or a programming project using the carla.org simulator. You will need to give a presentation based on the project.
More information: http://studiehandboken.abo.fi/en/course/DV00BO00/4556
Distributed computing systems have emerged to play a serious role in industry and society. Therefore, reliability of distributed systems has become an important issue. This course aims at giving an overview of reliable distributed systems and their components with a focus on cloud computing. We will look at possible failures in distributed systems and how to avoid them. Examples of applications of reliability techniques will be given.
After the end of the course the students should be familiar with distributed systems and cloud computing. The student should also be able to identify different failures in distributed systems and to describe reliability techniques to avoid these failures.