Urban areas are increasingly affected by noise emissions, as a consequence of technological progress, among other things. Such urban noise can have a disturbing effect on inhabitants, impeding their quality of life. Especially temporary noise events (such as large public music events, construction works, or ruthless behavior of car drivers or motorcyclists) play an important role here. However, such events are hard to define and predict.
The »StadtLärm« project consortium is currently developing a system for capturing, describing and predicting noise occurring in urban areas. To do so, the project members have implemented a robust and cost-efficient sensor platform, which they use for comprehensive noise measurement. The collected data can be visualized in 3D and used for the development of noise-space models. Capturing noise data of both high temporal and spatial resolution allows prediction of future noise settings on the basis of past noise events. The system is self-learning, which means that the models and services incorporated in the system become more and more accurate as the number of measurements is rising. City authorities may use the system to assess current noise settings and predict future ones, especially with regard to singular noise events and noise sources.
Fraunhofer IDMT’s contribution to the project
Fraunhofer IDMT is responsible for developing the backend system’s and sensor platform’s analytical components in the form of a software module.
"Central Innovation Programme for SMEs (ZIM)", run by the German Federal Ministry for Economic Affairs and Energy
- Innoman GmbH, Ilmenau
- Software-Service John GmbH, Ilmenau
- Bischoff-Elektronik GmbH, Oberstadt
- Institut für Mikroelektronik - und Mechatronik-Systeme gemeinnützige GmbH (IMMS GmbH), Ilmenau