Self-learning sensor systems for nature and technology

 

 

As part of the BMBF Cluster4Future program, the TISSS Lab at Johannes Gutenberg University is participating in the SENSORITHM Rhein-Main future cluster together with the partners Johann Wolfgang Goethe University Frankfurt am Main, Darmstadt University of Technology, Fraunhofer Institute for Structural Durability and System Reliability LBF, and the Institute for Animal Ecology and Nature Education. The interdisciplinary consortium combines expertise from physics, biology, computer science, mechanical engineering and social sciences. SENSORITHM will investigate how intelligent sensor technologies help avoid collisions of birds and bats with wind turbines and will develop self-learning sensor systems for monitoring technical components and installations.

In this way, Sensorithm can help resolve a green-green dilemma: On the one hand, the renewable energy generated by wind turbines is intended to halt climate change and thus ultimately safeguard biodiversity; on the other hand, rotor blades endanger rare bird species such as the red kite and various bat species. By introducing smart sensor technologies, the trade-off of climate neutrality vs. energy demand could be resolved with the help of innovation networks.

In the project, TISSS Lab director Prof. Dr. Ahrweiler and her team will be responsible for the social science analysis and design of the multi-dimensionality of this innovation network in the field of tension between technological, ecological, economic, political and social aspects.

For example, it is expected that approval procedures for wind turbines will change and that knowledge about new technological possibilities will find its way into political discourses. The Future Cluster is closely linked to partners from industry, universities, institutes, authorities and civil society (environmentalists, associations, NGOs, school classes) and will cooperate with them. The TISSS Lab will support participatory processes and ensure adequate involvement of relevant stakeholders.