Research Field:

Applied Artificial Intelligence

About

Due to the large amount of data from the areas of transportation and energy, we use artificial intelligence to analyze it. New use cases for artificial intelligence are emerging in the process.



Related Research Projects


  • Wind Structures

    The most important energy source from the field of renewable energies in Europe is wind. Currently, wind can still be interpreted as a stochastic variable. Accordingly, we improve our understanding of wind structures with mathematical and statistical tools.

    Agent Based Simulations and Policy Recommandations for Epidemics in the Global South

    The People´s Republic of China was the first region to be affected by a global pandemic outbreak in January 2020. COVID-19 spread quickly around the globe, presenting the international community with new dimensions of economic, social and moral problems. Countries responded by making macroscopic decisions for their nations. The individual regions were not equipped with the appropriate applications to be able to act regionally. Accordingly, micro-management decision support tools could be developed by us to advise the regional decision makers.

    Simulations for future Transport Systems

    Disruptive developments in automated driving systems, new drive concepts and digital mobility are shaping the way people in rural and urban areas. In combination with these technical potentials, novel mobility concepts can improve people`s everyday mobility of people in terms of both cost efficiency and sustainability. In addition, the challenges of demographic change and urbanization can be and negative developments can be mitigated.

  • AI for Aerospace Technology

    A major driver of climate change is flying, so we are striving to make this more sustainable. in doing so, we are focusing on researching the effects of operating conditions on aircraft engines to improve the timely planning of maintenance events and optimize them. To do this, we use machine learning mainly with time series of aircraft engines and numerical weather prediction models. The research aims to improve fuel efficiency and increase component longevity. This should enable plant operators and service providers to reduce costs and environmental footprint.

Related Transfer Projects


  • Transfer Project 1:
    Transportation

    Status: Ongoing

    Transfer Project 2:
    Medical Technology

    Status: Before Take Off

    Transfer Project 3:
    Wind Energy

    Status: Preparation

  • Transfer Project 5:
    Aerospace

    Status: Pre-Studies

    Transfer Project 7:
    Transportation

    Status: Preparation

    Transfer Project 8:
    AI

    Status: Pre-Studies

  • Transfer Project 9:
    Real Estate

    Status: Pre-Studies

Related Publications

Published

Wacker, B., Seebaß, J. V., & Schlüter, J. C. (2020). A modular framework for estimating annual averaged power output generation of wind turbines. Energy Conversion and Management, 221: 113149. doi:10.1016/j.enconman.2020.113149

Wacker, B., & Schlüter, J. C. (2020). An age- and sex-structured SIR model: Theory and an explicit-implicit numerical solution algorithm. Mathematical Biosciences and Engineering, 17, 5752-5801. doi:10.3934/mbe.2020309

Schröder, M., Bossert, A., Kersting, M. et al. COVID-19 in South Africa: outbreak despite interventions. Sci Rep 11, 4956 (2021). doi:10.1038/s41598-021-84487-0

Schlüter, J., Sörensen, L., Bossert, A. et al. Anticipating the impact of COVID19 and comorbidities on the South African healthcare system by agent-based simulations. Sci Rep 11, 7901 (2021). doi.org/10.1038/s41598-021-86580-w

In Press

Schlüter, J., Bossert, A., Rössy, P., & Kersting, M. (2021). Impact assessment of autonomous demand responsive transport as a link between urban and rural areas. Research in Transportation Business & Management, 39, 100613. doi:10.1016/j.rtbm.2020.100613

Submitted

Bossert, A., Kersting, M., Timme, M., Schröder, M., Feki, A., Coetzee, J., & Schlüter, J. (2020). Limited containment options of COVID-19 outbreak revealed by regional agent-based simulations for South Africa. Open Peer Review@F1000

Wacker, B., Schlüter, J. C.. Pipeline for Annual Averaged Wind Power Output Generation Prediction of Wind Turbines Based on Large Wind Speed Data Sets and Power Curve Data submitted@MethodsX

Working Paper

Grunicke, C., Schlüter, J. C., & Jokinen, J.-P. (12/2020), Implementation of a cost-benefit analysis of Demand-Responsive Transport with a Multi-Agent Transport Simulation. arXiv preprint arXiv:2011.12869

Persons Involved