Noise

Noise in the environment is a significant problem that affects quality of life. External noise, such as traffic noise from roads, railroad stations and railroads, contributes significantly to noise pollution. Modern technologies offer innovative approaches to noise reduction. For example, AI-based analysis of complex acoustic scenes and sounds enables precise detection and evaluation of noise sources. These methods are used in noise and traffic monitoring to develop effective noise reduction measures. AI systems can help to identify disturbing noises and analyze their distribution, which contributes to the planning and implementation of targeted noise protection measures. Particularly in heavily polluted areas such as train stations and along railroad lines, such technologies can be crucial in reducing noise pollution and thus improving the quality of life of local residents.

Noise maps are a tool for area-related noise immission control and are used to visualize noise immission in areas exposed to noise. The decisive evaluation parameter, the sound pressure level, is demonstrably only suitable to a limited extent for the assessment of actual noise pollution. Psychoacoustic parameters, such as loudness, sharpness and tonality, offer the potential to describe the actual perceived noise exposure more accurately and objectively with numerical values. The mapping of these parameters was implemented in the software of industrial partners. 

The expansion of photovoltaics (PV) on noise protection structures (LSW) is a means of achieving climate neutrality. In addition to the acoustic properties of sound-absorbing LSW, potential analyses must be prepared, taking into account legal and technical feasibility. Other important aspects such as plannability, connectivity and local energy consumers must also be taken into account. Of course, maintaining or even improving the acoustic function remains of central importance.