BMVI-funded Project LandLeuchten

Problem formulation

The project considers two rural model regions, the Eifel and the Hunsrück, which are characterised by structural change and demographic change. Specific challenges of these regions are, for example, cultural participation, mobility for all generations, supply of food and local products and an attractive cultural and leisure activity.

Project objective

The aim of the project is the development, implementation and testing of a sustainable and holistic approach for securing the quality of life, work and living in rural areas by means of autonomous mobility and networked services. In an open marketplace platform, the added value of automated vehicle platforms for rural areas will be modelled and implemented. With this collaborative Living Lab, various social functionalities are developed with the citizens (e.g. mobile meeting points, driving and delivery services, social participation).


The further development of distributed systems and Smart-Contract-based services using autonomous, electrified vehicles makes it possible to create a local platform and evaluate it in a variety of field tests. In the sense of responsible technology development, new and socially desired mobility services are developed in coordination with the needs of the local population and transferred into innovative business and logistics models. The implementation will take place in the model regions on the basis of selected services, which will be evaluated by the population. In this way, participation in rural areas is strengthened.


  • e.GO Mobile AG, Aachen, Germany

Project volumes

  • 2,899,798 Euro (of which 70 % promotion by BMVI)

Project duration

  • 11/2019 – 10/2022

Project partner

  • e.GO Digital GmbH, Aachen, Germany
  • PSI Logistics GmbH, Dortmund
  • Innoloft GmbH, Aachen, Germany
  • RWTH Aachen University, Chair of Communication Science, HCIC
  • Trier University of Applied Sciences (Umwelt-Campus), teaching and research area distributed systems, Birkenfeld



The purpose of this project is to continue to develop a virtual healthcare assistant, an innovative solution to help healthcare professionals deal with increasing amounts of medical knowledge and data. With the support of EIT Health, the Clinical Artificial Intelligence Improving Healthcare project will bring the innovation to the patient: saving lives, time and costs through significantly improved overview of a person’s health, early diagnoses and accurate, evidence-based treatment.

Our team of healthcare business experts, experienced doctors and artificial intelligence scientists will offer a breakthrough solution for the data problem at 158 000 intensive care beds in our target markets. We combine state-of-the-art advances of machine learning, natural language processing and artificial intelligence with an intuitive human interface.

Our broad experience in dealing with Big Data in all perspectives – business, research and medical – will enable our team to develop a certification-ready solution by the end of the project.

The overall goals of the project are:

  • to bring the solution from prototype to a certification-ready software;
  • to develop a needs-driven solution, tested by experts under real life conditions;
  • to develop a sustainable business and distribution model for our spin-off, start-up company.

Project Parter: UKA Aachen, RWTH Aachen, Cap Digital, ATOS Spain S. A., UAS Trier Research Group Distributed Systems 

The transport of people and goods is one of the most important components of the German economy.  We are currently experiencing a change from traditional transport to autonomous driving. This change will completely change people's mobility habits. For this to be a success, new urban mobility concepts must be developed that integrate the new digital services into urban life. A social transformation process must also be undertaken: Especially with the introduction of new technologies, innovation management is central and aims to involve citizens in the transformation process right from the start. 

Research objectives and approach

The aim of the APEROL research project is a pilot operation of automated, electrically driven vehicles in road traffic and their integration into a comprehensive mobility system. On the basis of comprehensive software support, which offers both citizens and companies tailor-made mobility and transport services, the necessary use of resources is optimised. The implementation of the project is divided into three main areas: piloting, software development and project dialogue.

The pilot operation of autonomous vehicles in the project will take place both on test tracks and successively in real city traffic. This piloting will be carried out with a vehicle based on the platform of the automated small bus e.GO Mover. The second major topic is software development. In addition to the development of intuitive apps for citizens and the provision of logistic software for companies, the main focus is on the development of algorithms for optimal disposition and route planning of the resources used. The third main topic of the dialogue is the external communication of the project and the resulting exchange. As a new technology field, it is essential for the applications of automated driving to enter into a dialogue with citizens and companies right from the start. In this way, the transformation from conventional to automated road traffic will be a success for all involved.

  • Project Manager: PSI Logistics GmbH
  • Project partners: RWTH Aachen, Trier University - Environment Campus (Prof. Guido Dartmann), City of Aachen, e.GO Mobile AG, MAT.TRAFFIC GmbH, Ergosign GmbH
  • Associated project partner: Internet of Things Expert Group of the National Digital Summit, City of Trie
  • Duration 01.10.2018 - 31.12.2020
  • Grant number 16AVF2134
  • Funding amount of the consortium 4.691.277,00 € (total funding amount of the project consortium over all project partners)
  • Sponsor Federal Ministry of Transport and Digital Infrastructure, within the framework of the "Automated and Networked Driving" funding guideline

    BMBF funded Project IMEDALytics

    Intensive care Decision support system with data fusion and pattern recognition for guideline-based, individualized risk stratification, monitoring and therapy guidance

    Project Coordinator: Philips GmbH Innovative Technologies Aachen

    Project partners: University Hospital RWTH Aachen, RWTH Aachen University, Trier University of Applied Sciences - Environmental Campus (Prof. Guido Dartmann), Ergosign GmbH

    IMEDALytics is an innovative, IT-based decision support system for individualized risk stratification, monitoring and therapy management in intensive care medicine. It links the data of a patient with medical knowledge as well as models that were obtained from data of other patients. IMEDALytics visualizes the individualized result of this combination in a user-friendly way for informed and prognostic decisions and documentation of diagnosis and therapy. IMEDALytics uses the advances in the digitalization of the health care system and new technologies for automated data analysis to achieve treatment paths better adapted to the patient and thus avoid undesired long-term consequences such as need for care and long-term ventilation. IMEDALytics is used as an example for volume substitution, which is an essential component of intensive care therapy. The particular challenge for the treating physicians is to determine the optimal, individualized indication, application of the correct dose and selection of the most suitable infusion solution for the respective patient on the basis of the general guidelines.

      Project Coordinator: Prof. Guido Dartmann

      Project partners: Expert Group Internet of Things of the National Digital Summit

      The digital transformation will dramatically change our economy and society in the coming decades. The Internet of Things (IoT) plays an essential role in the networking of the analogue world. The natural handling of sensors and communication modules, but also their programming up to the cloud application is the prerequisite for new application ideas and business models.  Germany's medium-sized companies in particular, however, have an enormous shortage of skilled workers in this area, since there are few good IT graduates who specialize in the subject area of the Internet of Things. Those who have specialized in this area are being attacked by the big "players" in the metropolitan regions. For the SMEs in the rural regions an enormous need of know-how emerges. Here we want to offer a solution with our concept, which facilitates the access to the Internet of things for medium-size enterprises and accelerates the development of first prototypes (Rapid Prototyping). Our concept is intended to further train existing specialists (lifelong learning) and simplify and accelerate their entry into the new IoT technology. IoT-driven business models are not tied to central resources in big cities and are, therefore, particularly suitable for rural development. Rural areas in particular can also benefit disproportionately from the application possibilities of IoT (monitoring in agriculture, new services). We have already developed a basic platform for this, which we would like to further develop as a pilot platform for medium-sized companies. We have defined the following four goals for this project:  

      • IoT training: The development of a training program for medium-sized companies in the field of IoT. Together with the Internet of Things expert group of the Digital Summit, policy recommendations will be formulated. IoT competition between the companies involved. The results could be presented at the Digital Summit.     
      • Rapid Prototyping in small companies in the region: The IoT pilot provides the medium-sized companies with a platform with which they can continue to implement prototypes in the future.
      • Adaptation to the individual needs of the company: The IoT pilot platform should be expandable and adaptable to the needs of the respective company in the region.    
      • Data-based business models for companies in the region: By integrating a data analysis software environment into the tool chain of the IoT pilot platform, companies should be able to test new data-based business models.   

        IoT Workshop of the Digital Summit

        Project partners: Expert Group Internet of Things of the National Digital Summit

        The IoT Workshop is a cooperation project within the Internet of Things expert group of the Digital Summit. Within this group, an IoT gateway and a software environment was developed for communicating the Internet of Things. 

          BMBF-funded project: Cognitive Tools for Cyber-Physical Systems (since 2017)

          Project Coordinator: Prof. Guido Dartmann

          Project partner: ISEK & Computer Vision group RWTH Aachen University

          In this project, practical trials on machine learning and data analytics will be developed at the Environmental Campus and RWTH Aachen University. In the experiments, the entire breadth of this topic is implemented in practical applications on hardware and software. The laboratories will be integrated into the respective Master's programs in Computer Science and Information Technology. Provided offline data sets enable the use of the learning units even without access to the hardware.

          The project benefits from synergies between the participating universities and the cooperation in a research project on machine learning. A total of five of the proposed experiments will be implemented on the Internet of Things (IoT) platform developed by Trier University of Applied Sciences together with the Internet of Things expert group of the Digital Summit.

          The experiments cover the fields of environment sensing, industry 4.0 and mobility. This project is also being advised by partners from industry in order to implement the tests in a practical manner. In addition, there should also be the possibility of developing further experiments from industrial applications. A further goal of the project is the establishment of a maker platform for machine learning on which industrial partners can get in contact with the students of both universities and work together on interesting problems.

            Associated Partner in BMBF-funded project: Wireless Security in Cyber Physical Systems (WiSeCPS)

            Project Coordinator: Prof. Gunes Karabulut Kurt

            Projektpartner: ICE RWTH Aachen University

            Associated Partner: Prof. Guido Dartmann

            The user demand and data transmission rates are ever increasing in wireless communication networks. However, due to their broadcast structure, wireless connections are inherently risky. In recent years, however, advances in the field of secure wireless communications have been made in the physical layer including beamforming and artificial interference approaches. However, these works are yet to be used for cyber-physical systems (CPS), which will enable us to interconnect all elements of an industrial production process. CPSs contain stringent requirements such as a maximum allowed latency, in addition to the commonly known metrics as security capacity. Existing PHY security solutions fail to address these requirements.

            In our project WiSeCPS, we target to enhance the current PHY security solutions, and provide a target to jointly use different approaches in an optimized fashion according to the requirements of a CPS. Our main goal in this project is to establish a secure CPS communications framework, determine the performance limits and propose applicable security solutions with proof-of-concept hardware demonstrations using software defined radio nodes. With this main goal our objectives are listed below.

            Objective 1: Improvement of the existing wireless security solutions for the CPS secrecy strategies

            Objective 2: Development of a common quality metric for the secrecy strategies in CPS

            Objective 3: Development and application of multi agent optimization concepts with improved secrecy in distributed CPS, to propose a flexible control architecture

            Objective 4: Integration of the strategies in a real test environment using software defined radio nodes to understand performance limits within a proof of concept (PoC) level deployment

            Objective 5: Proposal of PHY-Security Framework for CPS


            Further Projects:

            • PARIS (BMBF), Topic: Machine Learning and autonomous driving (2017)
            • PHOENIX (open FET, H2020), Topic: Sensor Networks (since 2015)
            • I2EASE (BMBF), Topic: V2V and V2X Communication (since 2015)
            • METIS (FP7, EU), Topic: 5G Mobile Communication (2013)
            • NEWCOM++ (FP7, EU), Topic: Channel Modelling, Simulations (2009)