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At Carnfield University, unmanned aerial vehicles (UAVs) were submitted to a sound measurement test in order to better understand their potential and environmental impact in urban contexts.

Because of the volume and frequency of noise produced by unmanned aerial vehicles, they are often an annoyance, especially when flying over metropolitan areas. According to recent research by the UK Regulatory Horizons Council, UAVs are becoming less popular in and around residential areas as a result of the noise they produce, which is becoming a significant problem as their usage for examinations and shipments grows. This study might help with the development of measuring tools as well as a better understanding of the noise produced by unmanned aircraft.

A series of tests conducted in collaboration with noise experts from the Envirosuite Group and the ARPAS-UK Skimmer Industry Group, as well as environmental noise experts from Cranfield University and CAA, found that microphones can effectively capture different levels of UAV noise at different heights, and that the spectrum can be used to identify different types of UAVs based on their unique noise.

As part of the measurement investigations, a large number of small to medium-sized multi-rotor drones flew in a variety of pre-defined flight patterns at Carnfield Research Airport. Noise levels from many drones flying above 100 feet were frequently in the 50-60 decibel (dBA) range, which is equivalent to noise levels in a packed restaurant.

Dr. Simon Jude, a senior lecturer at Cranfield University’s Environmental Center, told that the study highlights the need for greater research as well as public knowledge, involvement, and acceptability of noise from unmanned aerial vehicles. It claims that perceptions and attitudes toward unmanned aerial vehicles vary by culture, and that public concerns might be a significant barrier to effective adaptation and use of this technology.

The knowledge gained from these trials will hopefully educate the approaches needed to accurately quantify and comprehend UAV noise.