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Schlussbericht Projekt “Flexibler Erlebnisbus für nachhaltigen Freizeitverkehr” (FEB-NAFV)
No full textDer motorisierte Individualverkehr (MIV) stellt in touristisch geprägten Regionen eine erhebliche Herausforderung dar. Er beeinträchtigt nicht nur die Natur, das Klima und das Landschaftsbild, sondern mindert auch das Urlaubserlebnis der Gäste und die Akzeptanz des Tourismus bei der lokalen Bevölkerung. Datengetriebene, flexible und emissionsfreie Mobilitätsangebote bieten die Möglichkeit, den MIV zu reduzieren und Elektromobilität zu fördern. Zudem können sie Maßnahmen zur Besucherlenkung unterstützen und so zum Erhalt attraktiver Lebens- und Urlaubsregionen beitragen.
Das Forschungsprojekt Flexibler Erlebnisbus für nachhaltigen Freizeitverkehr (FEB-NAFV) zielt darauf ab, den Individualverkehr und die damit verbundenen Emissionen im Freizeitverkehr zu reduzieren sowie touristische Hotspots zu entlasten. Dies soll durch die Entwicklung und Pilotierung eines bedarfsorientierten und emissionsfreien Erlebnisbusses im Allgäu erreicht werden.
Das Konzept des Erlebnisbusses basiert auf einer datengetriebenen Einsatz-, Routen- und Erlebnisplanung. Dies beinhaltet auch ein fundiertes Elektromobilitätskonzept. Ein besonderer Fokus liegt auf der Übertragbarkeit und Skalierbarkeit des Projekts auf andere Regionen. Zudem soll das Mobilitätsangebot als Instrument zur Besucherlenkung im Allgäu fungieren.
Um Missverständnisse zu vermeiden, soll an dieser Stelle betont werden, dass es nicht um die Entwicklung eines On-Demand-Angebots wie Rufbusse oder Sammeltaxis ging. Primär stand nicht Flexibilität aus Kundensicht im Mittelpunkt des Vorhabens, sondern Flexibilität aus verkehrsplanerischer und touristischer Perspektive. In diesem Sinne bedeutet Flexibilität hier, dass mit der Einsatzplanung des Busses flexibel auf veränderliche Kontextparameter wie Wettervorhersage oder das prognostizierte Verkehrs- und Besucheraufkommen reagiert werden kann.
Das Projekt FEB-NAFV lief von November 2021 bis Oktober 2024 und wurde im Rahmen der Innovationsinitiative mFUND durch das Bundesministerium für Digitales und Verkehr (BMDV) gefördert (Projektträger: Deutsche Zentrum für Luft- und Raumfahrt e.V.; Förderkennzeichen 01F2198A). Zu den Verbundpartnern gehörten das Institut für Nachhaltige und Innovative Tourismusentwicklung (INIT) in Füssen der Hochschule Kempten, welches die Verbundkoordination übernahm, die Allgäuer Überlandwerk GmbH (AÜW), Steinbacher-Consult Ing.ges. mbH & Co. KG und die Outdooractive AG. Zusätzlich unterstützten assoziierte Partner das Projekt, darunter die FLEXIBUS KG, der Deutsche Alpenverein (DAV) Sektion Kempten und der Naturpark Nagelfluhkette e.V
Cycle Time Reduction in Production Systems via Digital Twin-Based Compensation of Pneumatic Reaction Times
No full textIn event-based control systems, actuator operations are typically triggered by physical sensor signals to ensure process safety. However, this can lead to systematic delays, especially in pneumatic systems, due to system-related reaction times. This paper presents a method to compensate such delays by statistically advancing control signals without the need for additional sensors.
A bidirectionally coupled digital twin, based on virtual commissioning models, continuously evaluates live data and derives optimized advance signals during operation. The method integrates event-based control with time-based triggering and employs a hybrid approach combining empirical quantiles with analytical confidence intervals to maintain safe operation. Validated in a testbed under realistic industrial conditions, the approach achieves an average time saving of 315 ms per compensated transition. The system architecture decouples real-time PLC execution from non-real-time analysis, enabling scalable integration with diverse control and simulation platforms. The results demonstrate the potential of digital twins for active, data driven optimization in discrete manufacturing systems
From Inter- to Transdisciplinarity via Research Labs: A Format for Joining Diverse Perspectives and Expertise in HCI-Research
No full textWith HCI increasingly addressing complex societal challenges, transdisciplinarity emerges as a necessary extension of interdisciplinarity that involves the active integration of practitioners and stakeholders. In this paper, we propose Research Labs as a format to foster transdisciplinarity through discourse and reflection in HCI. They are organized as theme-driven, moderated sessions based on a consistent setup of modules, each following a distinct objective to provide both, continuity for enabling systematic reflection processes while also ensuring flexibility for participants to address individual topics, or needs. This concept was applied within eight sessions conducted over three years in the context of participatory design of socio-technical innovation for informal care. With familiarity and trust, dynamic adaptation mechanisms, and participatory elements, we identify preliminary learnings on how to strengthen transdisciplinarity within HCI processes. The paper outlines opportunities and limitations of the format and suggests directions for further development and application
Artificial Intelligence in Math Education of Engineers
No full textThis paper considers if Artificial Intelligence (AI) tools based on Large Language Models (LLMs) can support math education of engineers. A typical spectrum of engineering math tasks is evaluated with the help of GPT-4 which is also used as a verification tool. Suitable prompting methods compatible with the facilities of students are investigated. A proposal for a zero-shot prompt is made that uses LATEX for the input of mathematical formulas and demands outputs in natural language and Python code as additional output format. For verification purposes the LLM is provided with the natural language and code outputs and the offline computed Python results
Chancen und Herausforderungen in der interprofessionellen Zusammenarbeit zwischen pflegerischem und pharmazeutischem Personal im Kontext der Verblisterung für Heime
No full textDer Vortrag behandelt die Rollen und Anforderungen des Pflegepersonals bei der Arzneimittelversorgung von Heimen und Pflegediensten sowie die wahrgenommene Qualität der Zusammenarbeit mit pharmazeutischem Personal
Relevanz der digitalen Gesundheitskompetenz (dGK) für Versorgungsforschung und -praxis – Teil I
No full textMit der fortschreitenden Digitalisierung begegnen Bürger*innen, Patient*innen und Versorger*innen vermehrt digitalen und/oder hybriden Präventions- oder Versorgungsangebote und digital gestützten Gesundheitsinformationen. Im Zuge dessen ist digitale Gesundheitskompetenz (dGK) als Erweiterung der Gesundheitskompetenz (GK) eine entscheidende Fähigkeit im Umgang mit gesundheitlichen Herausforderungen. dGK beschreibt das Suchen, Finden, Verstehen und Bewerten und Anwenden von Gesundheitsinformationen aus digitalen Quellen. Derzeit bestehen vielfältige Definitionen, die jedoch vor allem neuere digitale Anwendungen nicht berücksichtigen. Ziel dieses ersten Teils des Artikels der Mitglieder der AG Digital Health des Deutschen Netzwerks Versorgungsforschung e.V. (DNVF) ist es, eine Arbeitsdefinition von dGK theoriebasiert herzuleiten. Diese fußt auf bekannten Definitionen der Gesundheitskompetenz und auf Dimensionen einschlägiger Rahmenmodelle. Es wird besonderes Augenmerk auf die Abgrenzung und Gemeinsamkeiten von GK und dGK gelegt. Anschließend wird die Operationalisierung von dGK im Kontext international bewährter Ansätze betrachtet. Die dGK wird hier als relationales Konstrukt angesehen, welchem sich über eine mehrdimensionale Operationalisierung auf individueller, interaktionsbezogener und Systemebene angenähert werden kann.As digitization progresses, citizens, patients and providers increasingly encounter digital or hybrid prevention or care services and digitally supported health information. Under these circumstances, electronic health literacy (eHL) as an extension of health literacy (HL) is a crucial skill that entails searching, finding, understanding, evaluating and applying health information based on digital sources when encountering challenges to health. There are currently multiple definitions that do not take into account newer digital applications in particular. The aim of part I of this article by the members of the Digital Health working group of the German Network for Health Services Research (DNVF) is to derive a working definition of eHL which is founded on known definitions of (e-)health literacy and on dimensions of relevant framework models and theories. Particular attention is paid to the delimitation and similarities between HL and eHL. Also, this article looks at the operationalization of eHL in the context of internationally proven approaches. Here, eHL is viewed as a relational construct that can be approached via multidimensional operationalization at the individual, interaction-related and system levels
Künstliche Intelligenz auf dem Silbertablett: Ein Diskussionsbeitrag über Voraussetzungen für einen sinnstiftenden Einsatz durch Pflegefachpersonen
No full textJohanna Aigner, Julia Noll und Dr. Florian Fischer liefern einen Diskussionsbeitrag über Voraussetzungen für einen sinnstiftenden Einsatz von KI durch Pflegefachpersonen
Digitally supported interprofessional interaction in healthcare—a scoping review
No full textBackground
The increasing complexity of patient care and workforce shortages in healthcare systems necessitate improved interprofessional interaction. Digital technologies offer promising solutions to facilitate such interaction across healthcare settings.
Objectives
This scoping review aimed to identify, categorize, and assess digital technologies that support interprofessional interaction among healthcare professionals, using the NASSS framework to evaluate their implementation context and impact.
Methodology
A systematic search was conducted across five databases. The eligible studies examined digital tools enabling interaction between different professional groups in healthcare. Data from 407 studies were extracted and coded using four NASSS domains (Condition, Technology, Value Proposition, and Adopter System). Thematic analysis and visualizations were employed to synthesize findings.
Results
Seven primary technology categories were identified. Most technologies were implemented at the organizational level, primarily within hospital and intersectoral care settings, with oncology being the most common clinical focus. While many tools showed positive impacts on workflow efficiency, access to specialist expertise, and team communication, challenges relating to usability, data privacy, role ambiguity, and staff workload were also reported. Value propositions and impacts on staff varied significantly across technologies.
Conclusion
Digitally supported interprofessional interaction holds promise for enhancing communication, collaboration, and efficiency in delivering healthcare. However, successful adoption depends on aligning technological design with clinical workflows, involving end-users in development, and addressing regulatory, ethical, and organizational challenges
Price Aware Power Split Control in Heterogeneous Battery Storage Systems
No full textThis paper presents a unified framework for the optimal scheduling of battery dispatch and internal power allocation in Battery Energy Storage Systems (BESS). This novel approach integrates both market-based (price-aware) signals and physical system constraints to simultaneously optimize (1) external energy dispatch and (2) internal heterogeneity management of BESS, enhancing its operational economic value and performance. This work compares both model-based Linear Programming (LP) and model-free Reinforcement Learning (RL) approaches for optimization under varying forecast assumptions, using a custom Gym-based simulation environment. The evaluation considers both long-term and short-term performance, focusing on economic savings, State of Charge (SOC) and temperature balancing, and overall system efficiency. In summary, the long-term results show that the RL approach achieved 10% higher system efficiency compared to LP, whereas the latter yielded 33% greater cumulative savings. In terms of internal heterogeneity, the LP approach resulted in lower mean SOC imbalance, while the RL approach achieved better temperature balance between strings. In the short-term evaluation, LP delivers strong optimization under known conditions, whereas RL demonstrates higher adaptability in dynamic environments for real-time BESS control
Feasibility of AI-Assisted Programming for End-User Development
No full textEnd-user development,where non-programmers create or adapt their own digital tools, can play a key role in driving digital transformation within organizations. Currently, low-code/no-code platforms are widely used to enable end-user development through visual programming, minimizing the need for manual coding.
Recent advancements in generative AI, particularly large language model-based assistants and “copilots”, open new possibilities, as they may enable end users to generate and refine programming code and build apps directly from natural language prompts. This approach, here referred to as AI-assisted end-user coding, promises greater flexibility, broader applicability, faster development, improved reusability, and reduced vendor lock-in compared to the established visual LCNC platforms.
This paper investigates whether AI-assisted end-user coding is a feasible paradigm for end-user development, which may complement or even replace the LCNC model in the future. To explore this, we conducted a case study in which non-programmers were asked to develop a basic web app through interaction with AI assistants.The majority of study participants successfully completed the task in reasonable time and also expressed support for AI-assisted end-user coding as a viable approach for end-user development. The paper presents the study design, analyzes the outcomes, and discusses potential implications for practice, future research, and academic teaching