Comeln - Communities of Practice NRW for Innovative Teacher Training (ComeIn)- Promotion of digitalization-related competences of teachers

Key data:

WBsmart - Educational science foundation of a smart AI-based digital training space for elderly care using personalized recommendation systems

Key data:

KIRETT - Computer support through artificial intelligence in rescue operations to improve first aid (KIRETT)

Key data:

• Category: SME-innovative
  
• Duration: 2021-2024
  
• Funded by: BMBF

Project description:

The project objective was to improve first aid during rescue operations using a wearable device. The resulting wearable was used for computer-aided situation recognition, gave the rescue personnel context-dependent recommendations for action and was intended to minimize late damage caused by incorrect treatment and increase the probability of survival.

The wearable was used to integrate the following innovations into daily rescue operations:

1. Improved quality of care in special emergency situations: in certain special emergency situations, initial care was not optimal - for example in a mass casualty incident (MANV scenario) or rare emergencies such as a snake bite. The wearable made an important contribution to solving these problems by automatically recognizing the situation using vital data from medical devices as well as operational data from the control centre and input from the emergency services.
2. Data integration to improve first aid: The wearable was used to merge data from the control center, medical devices and input from the emergency services - directly at the patient's location.
3. General increase in efficiency through automation and contextual support: As a handy, portable device, the wearable enabled a decisive increase in efficiency and allowed the emergency services to focus their full attention on the emergency patient.
4. Traceability of first aid for quality management and training: The operational data collected was subsequently used to optimize first aid algorithms and training, including targeted feedback into the training system.

The data collected with the wearables and transferred to a database generated a complete overview of patients, treatments and status, including medical history and course of therapy.

Project partner:

• CRS medical GmbH, Asslar
• mbeder GmbH, Siegen
• Chair of Embedded Systems, University of Siegen
• Institute for Knowledge-Based Systems and Knowledge Management, University of Siegen

Associated partners:

• District of Siegen-Wittgenstein
• City of Siegen
• German Red Cross
• Jung-Stilling Hospital Siegen

OSCAR - Online, open learning recommendations and mentoring towards Sustainable research CAReers

Key data:

• Category: Erasmus+
  
• Duration: 2020-2023
  
• Funded by: Erasmus+ Strategic Partnership
  
• Project management organization: DAAD

Project description:

The project OSCAR ("Online, open learning recommendations and mentoring towards Sustainable research CAReers") served the professional development of researchers, master students and doctoral candidates through personalized training on mental health and career development - supported by AI-based learning recommendations and modern online mentoring technologies.

The project was built on three central pillars:

1. AI-powered learning recommendation framework: development of an open online platform to foster transversal key competencies on an individual level, taking into account the learner context.
2. Online mental health mentoring: Psychological support to understand and mitigate the impact of stressful academic environments.
3. Online mentoring in career management: Supporting sustainable research careers through targeted career planning.

Consortium:

• German National Library of Science and Technology (TIB), Hannover - Coordinator
• University of Siegen (USI)
• SciLink
• MCAA
• Career & Life Planning (CALP)
• Instante Falante

Prototype: labs.tib.eu/edoer/

OEduverse Erasmus+ Strategic Partnership - Advancing sustainable research careers for graduate students through training in mental wellbeing, open science, and communication skills

Key data:

Project description:

Open Science (OS) has been a central concept for the progress of science in Europe in the 21st century. To promote a more transparent scientific agenda, scientists needed to acquire interdisciplinary and transversal skills beyond their specialization. Researchers needed to be experts in research management, to know the diversity of intercultural research groups and disciplines, and to manage stressful steps in their research. In addition, researchers needed to be able to address a wider audience and be confident, competent communicators.

The OEduverse strategic partnership built on the successful EDUWORKS MCA-ITN and aimed to establish a consortium to address this key skills shortage in the labor market. The project was built on three central pillars:

1. Developing best practices for psychological support training: researchers were supported to understand the stress of science and develop positive cognitive frameworks to address the challenges of OS.
2. Developing OS training: Innovative teaching with a focus on publishing, privacy and ethics, project management - all against the backdrop of contemporary issues in OS.
3. Promoting OS and engagement: developing scientists' storytelling skills through performing arts training to expand their opportunities to engage with non-scientific communities.

Context/Background:

OS skills were critical for both the scientific and corporate sectors in the 21st century. Researchers needed to be confident, competent communicators, experts in research management, familiar with the diversity of cross-cultural research groups and disciplines, able to manage stressful moves while remaining open and innovative, and integrating basic IT skills to support their analytical work. Together these formed OS competencies. The OEduverse project aimed to establish a personalized training framework to provide the basics of OS skills training for early and advanced career researchers that met the needs of the job market.

Objectives:

OEduverse created and delivered high quality training content to groups of researchers working in diverse and interdisciplinary environments with the aim of:

• To promote lifelong learning to bridge the gap between individuals, education and the labor market. This was achieved through the development and deployment of innovative courses embedded in a learning program. These courses included the development of skills critical to the labor market such as communication, intercultural competencies, psychological skills to avoid stress, and scientific communication skills.
• Integrate a network of professionals and engage a range of stakeholders from academia, industry and government institutions to create diversity and promote continuous education.
• Raise awareness of the impact of a data-driven society in education and work at both organizational and policy levels.

Consortium:

• University of Siegen (USI)
• German National Library of Science and Technology (TIB), Hannover
• SciLink
• Trinity Student Counseling Services (TCD)
• MCAA
• SPACE

Project website:

https://oeduverse.eu/

MS@CPS - Master of Science on Cyber Physical Systems (MS@CPS)

Key data:

Project description:

Establishment of an international Master of Science in Cyber Physical Systems:

With the proliferation of technologies such as the Internet of Things (IoT), autonomous vehicles, embedded systems, cloud computing, Big Data and the 5th generation Internet, the integration of software and hardware has become increasingly crucial for reliable, secure and flexible systems. Cyber Physical Systems (CPS) was a new multidisciplinary field that addressed precisely this integration.

The international MS@CPS Master's program offered a specialized and practice-oriented view of this research field and prepared students to work as highly skilled analysts, designers and developers of both software and hardware aspects for industry-relevant systems and applications in the CPS context.

The program comprised two central tracks: Embedded Systems (ES) and Knowledge-based Systems (KBS), the combination of which formed the foundation for CPS. Through enrollment, students interacted with people from different countries and cultural backgrounds. Thanks to the ECTS system, they were able to adapt to different teaching environments, experience different teaching methods and qualify for mutually beneficial opportunities.

The consortium:

• Three European universities
  • University of Hertfordshire, Great Britain
  • University of Siegen, Germany
  • Royal Institute of Technology, Sweden
• Six Middle Eastern universities
  • German Jordanian University, Jordan
  • Tafila Technical University, Jordan
  • University of Sfax, Tunisia
  • University of Carthage, Tunisia
  • Palestine Technical College, Palestine
  • Al-Quds University, Palestine

The project was coordinated by the University of Siegen.

Project publications:

I. Ishaq et al: "Work in Progress - Establishing a Master Program in Cyber Physical Systems: Basic Findings and Future Perspectives". In: 2019 International Conference on Promising Electronic Technologies (ICPET), Gaza City, Palestine, pp. 4-9, 2019.

Project website:

https://blogs.uni-siegen.de/ms-cps/

iDev40 - Integrated Development 4.0 (iDev40)

Key data:

• Category: EU research project
  
• Duration: 2018-2021
  
• Funded by: ECSEL Joint Undertaking - Horizon 2020

Project description:

Digitalization and Industry 4.0 have been drivers of fundamental business innovation and disruption. By closely linking development processes, logistics and production with Industry 4.0 technologies, iDev40 achieved a disruptive step to accelerate time to market. By developing and implementing a digitalization strategy for the European electronic components and systems industry, a "breakthrough" was initiated.

Integrated Development 4.0 led the digital transformation of individual processes towards an integrated digital value chain based on the "Digital Twin" concept. Development, planning and production benefited from the digital twin concept through highly digitalized virtual processes along the entire product life cycle.

In view of the European policies for 2020 and beyond, iDev40 offered solutions for social and organizational challenges: innovative technologies to master the growing complexity in the development and production of ECS "Made in Europe", strengthening European competitiveness and supporting "knowledge workers" in manufacturing through smarter machines (AI).

Central areas of work:

• Methods and tools for AI & ML The aim was to implement data and knowledge management systems that intelligently managed data in a large heterogeneous environment, provided security concepts for on-demand data management and used artificial intelligence and deep learning algorithms to semi-automatically enrich content and extract facts from unstructured content.
• Virtualization & value chain To enable the virtualization of ECS value chains, knowledge-based development was integrated into digitalized production companies. Core areas such as virtual manufacturing, experiment control and remote development were addressed.
• Digitalization across the entire product life cycle The aim was to develop a company-wide strategy for data formalization, transfer and collaboration in the sense of a single source of truth (SSoT). Based on the resulting database, a "digital twin" was developed that made complex processes more manageable in a learning environment and improved productivity, resource utilization and quality.
• Skills & Workplaces 4.0 In the area of Industry 4.0, social skills were also in demand in the context of digitalization. Through knowledge-driven and integrated HR development, the focus was on employee training, the design of production systems and value chains as well as cross-border collaboration.

The iDev40 project was co-financed by the ECSEL Joint Undertaking as well as funding from Austria, Belgium, Germany and Spain and the European Structural and Investment Funds. It was coordinated by Infineon Technologies Austria AG.

Adistes - Active Diagnosis based on Semantic Web Technologies for Distributed Embedded Real-Time Systems

Key data:

• Category: DFG research project
  
• Duration: 2016-2019
  
• Funded by: DFG (German Research Foundation)

Project description:

Active diagnosis aimed to significantly improve system reliability by using diagnostic data at runtime for fault isolation and online troubleshooting. Active diagnosis for open real-time embedded systems (e.g., healthcare management and medical systems) was an open research problem due to strict real-time and dependability requirements combined with components that were unknown at design time.

The project extended semantic techniques normally used in large-scale IT systems to active diagnosis in open real-time embedded systems. Modeling techniques were developed to express diagnostic features, symptoms, faults and recovery actions. Distributed knowledge management methods provided relaxed consistency while ensuring real-time frameworks. Real-time inference was investigated using time-driven scheduling of diagnostic queries. The goal of query transformations, semantic transformations and goal-oriented learning was to improve schedulability and reliability. The methods and algorithms were implemented as prototypes and evaluated experimentally and analytically in terms of reliability and timeliness.

Important contributions that went beyond the state of the art:

• Modeling techniques for a diagnostic knowledge base
• time-controlled planning and optimization of diagnostic queries for real-time inference
• distributed knowledge base management with relaxed consistency
• goal-oriented self-learning for active diagnosis in open embedded systems

To jointly address these challenges in a framework for active diagnosis, two research fields were brought together in the project:

• the field of fault-tolerant embedded systems
• the field of knowledge-based system and semantic web technologies

The research idea of the project was to develop reliable and predictable methods for active diagnosis based on rule-based inference and semantic web technology. Semantic web services had been successfully used in standard IT applications to deal with highly dynamic and open systems, to provide semantic information and to capture relationships and dependencies.

However, there was a significant research gap, as semantic web services did not support modeling of the relevant properties for active diagnosis, nor did they allow conclusions to be drawn about real-time guarantees or adaptive learning behavior.

Therefore, the development of a diagnostic ontology was proposed for the time-driven scheduling of rule executions of an ODRE system, dynamic knowledge management and self-learning techniques to fulfill the requirements of open assumptions, real-time and reliability, and to be able to experimentally and analytically evaluate reliability and timeliness.