Teaching AI competencies in engineering using projects and open educational resources

A major challenge in engineering education is to empower students to use their acquired technical skills to solve real-world problems. In particular, methods of Artificial Intelligence (AI) need to be studied as tools in their respective application contexts. This puts pressure on university lecturers concerning the didactical design and elaboration of a course, and requires them to move towards a practice-based learning approach. Moreover, working on real-world problems leads to uncertainties for the lecturer and their students. Before and during the course, it is not always clear which methods will be used to solve the problem, respectively which competencies the participants need to acquire. Therefore, we propose to combine two established approaches: a project-based learning approach and the use of digital, curated learning content provided by Open Education Resources (OERs). We hypothesise that a practical study project solving a real-world problem using a combination of OERs and project-based learning is beneficial to AI education. Furthermore, we show implementations of our concept in three different courses. The first results indicate that student-centred tasks lead to high intrinsic motivation. At the same time, lecturers have to deal with a modified and extended role: They are no longer the broadcaster of knowledge but rather a guide within the learning process. Using the combination of OERs and project-based learning, the courses are attractive and exciting for students and lecturers without becoming unmanageable

Generative KI als Werkzeug in der wissenschaftsbasierten Lehre – Ein Selbstversuch

<p>Die Entwicklungen in der Anwendung Künstlicher Intelligenz können die wissenschaftsbasierte Lehre bereichern. Erste Erfahrungen im letzten Semester mit 50 Studierenden bestätigen dies.</p&gt

Framework for an Autonomic Transport System in Smart Cities

Today the concept of smart cities is discussed in scientific society and politics. A core function of smart cities is transportation. This paper gives a short overview on the concepts for Intelligent Transport Systems (ITS) for smart cities and proposes a framework for the design of an autonomic transportation system that provides personalized mobility services to its users in a smart city setting. The transportation poses extreme environment for ICT systems due to fast moving vehicles and users, requiring real-time acquisition and high performance processing of large scale data, and rapidly changing communication networks topologies and node densities. The aim of this paper is to propose a framework that will act as a reference for the design of future transportation systems that are able to cope with the ever rising system complexities and users’ demands. Therefore, a backbone system providing information at different levels was designed following the principles of a corporative ICT that were proposed in [1]. The framework fulfills the main requirement providing suitable information about the local decision engines in vehicles and infrastructure interacting in smart cities traffic systems

Autonomic Transport Management Systems—Enabler for Smart Cities, Personalized Medicine, Participation and Industry Grid/Industry 4.0

Today’s societies are facing great challenges in transforming living environments in a way better serving people’s demands of the future. A key point in this transformation is reinventing cities as smart cities, where the core services are integrated in a way that ensures a high quality of life while minimizing the usage of resources [Smart cities in Europe. Serie Research Memoranda 0048, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics 1]. Setting up smart cities resp. transforming cities to smart cities includes the development of smart transport systems as a main service all other services rely on. Thinking about current mega trends like Individualization of Products (Mass Customization) in so called Industry grid also known as Industry 4.0 [Umsetzungsempfehlungen für das Zukunftsprojekt Industrie 4.0 2] (Industrie 4.0 describes the industry in the 4th industrial revolution to customized mass production after mechanization, mass production, digitalization [Map ‘n’ tag. Thinking highways 3]), Personalized Medicine or the need of better support for disabled and older people in an aging society, the interconnection of involved bodies is a premise. In virtual world this means integration of data networks and ICTs in the physical world this means establishing individual and personalized transport services that cover individual mobility and individual distribution of goods. To ensure the best utilization of infrastructure while having less employable people in an aging society a high grade of automation and information integration is needed. We call this a smart transport system as the next step in development of today’s intelligent transport systems (ITS) and propose establishing this ITS of the future as an autonomic system to meet all the different requirements and ensure a high reliability of the overall system. Reliability is essential since most other services of the living environment smart city, will rely on transport systems. This chapter gives an overview on state of research based on current literature and recent publications of the authors (see references) and focus on the ICT system needed to manage transportation the autonomic transport management system

ersonal smart travel agent for empowering persons with disabilities using public transport

Today's public transport is not easy to use by people having mental problems or those who are disabled. Traffic planning today is powered by online time tables calculating the optimal way to use public transport in terms of time and costs. Therefore usually a graph representing the public transport network is set up and algorithms taken from graph theory or operations research are used to find optimal routes. This is not suitable for a group of travellers having constraints in using vehicles, vehicle types or particular stations for health reasons. On the other hand, since most of those people are not able to drive a car on their own, making public transport available and moreover easily usable enable these people to improve their mobility and their quality of life in general. This paper shows an approach developed within the mobile project funded by The German Federal Ministry of economy and energy that allows supporting this group of users during a travel using public transport and undertaking personal constraints in route planning. This allows getting personalized advice during travel and while travel planning. This is implemented by generation of a second graph representing the public transport network not in dimension of time and costs but in preferences and dislike of a given traveller. The second graph is an overlay to the standard graph to get a personalized graph that allows finding a suitable route respecting the constraints of the user