Department of Science and Industry Systems, University of South-Eastern Norway, 3616 Kongsberg, Norway.
Indra Navia AS, 1383 Asker, Norway.
Int J Environ Res Public Health. 2021 Dec 25;19(1):223. doi: 10.3390/ijerph19010223.
In recent years, there has been a rapid growth in the development and usage of flying drones due to their diverse capabilities worldwide. Public and private sectors will actively use drone technology in the logistics of goods and transporting passengers in the future. There are concerns regarding privacy and noise exposure in and around the rural and urban environment with the rapid expansion. Further, drone noise could affect human health. European Union has defined a service-orientated architecture to provide air traffic management for drones, called U-space. However, it lacks a noise modelling service (NMS). This paper proposes a conceptual framework for such a noise modelling service for drones with a use case scenario and verification method. The framework is conceptualized based on noise modelling from the aviation sector. The NMS can be used to model the noise to understand the accepted drone noise levels in different scenarios and take measures needed to reduce the noise impact on the community.
近年来，由于飞行无人机的各种能力，其在全球范围内得到了迅速发展和应用。公共和私营部门将在未来积极将无人机技术应用于货物的物流和乘客的运输。随着快速扩张，人们对农村和城市环境中的隐私和噪音暴露问题感到担忧。此外，无人机噪音可能会影响人类健康。欧盟已经定义了一种面向服务的架构，为无人机提供空中交通管理，称为 U-space。但是，它缺乏噪声建模服务（NMS）。本文提出了一种针对这种无人机噪声建模服务的概念框架，包括用例场景和验证方法。该框架基于航空领域的噪声建模概念化。NMS 可用于对噪声进行建模，以了解不同场景中可接受的无人机噪声水平，并采取必要措施降低噪声对社区的影响。
