DroneNoise: Addressing Public Health and Wellbeing Harms for a Sustainable Drone Sector

Lead Research Organisation: University of Salford
Department Name: Sch of Computing, Science & Engineering

Abstract

There is currently a risk that drones are taking to the air without sufficient consideration of their noise impact on public health and wellbeing. Government and industry agree that drone technologies will lead to a significant business opportunity. Drones are expected to support an efficient provision of public services, and therefore deliver substantial societal benefits. But there is a very real barrier to making this a reality - none of this can happen if noise issues are not taken care of at design, operation and policy levels.

The pandemic crisis has served to propel the use of drones to deliver food and medicines. It is now more certain that drone technologies will be widely adopted in the short future for a range of applications from parcel delivery to transport of people. These applications are set to grow thanks to the EC U-space and UK Future Flight initiatives, which are creating a clear framework to allow the creating of a market for drone services. However, the noise of hundreds of drones flying around will certainly lead to conflicts with communities.

To date, there is not a comprehensive understanding on how drone noise is perceived and what can be done to operate drones without affecting public health and wellbeing. Noise is already a serious issue. As reported by the European Environment Agency, environmental noise already causes approximately 16,600 cases of premature death in Europe each year, with almost 32 million adults suffering annoyance and over 13 million adults suffering sleep disturbance.

Assessing noise perception of drones and developing actions to mitigate their impact on communities is challenging, due to their unconventional sound signatures and operating procedures. Standard measures of sound power (proposed in EU Regulation 2019/945) are inadequate to characterise this. But it's also an opportunity to innovate in the way transportation noise issues are dealt with.

In this project, I will develop models to predict human response to drone noise. Integrated into the design cycle, these perception noise models will allow to noise issues to be anticipated early in the design process. This approach will avoid costly and inefficient ad hoc corrections at later stages, and therefore, will go beyond the traditional approach on aircraft noise assessment.

I will investigate how context influences drone noise perception. People won't perceive a drone delivering a parcel to their neighbours equally to a drone providing medical supplies. Furthermore, I will investigate noise annoyance and audibility for a comprehensive set of drone operating conditions, to define acceptable noise characteristics for drone operations. The outcomes of my project will inform how and where to fly drones to minimise impact on existing soundscapes.

The work in my project will be connected to industry design, policy making and organisations lobbing for noise abatement, through a steering group with the main drone stakeholders. I will develop a toolkit to aid manufacturers to reduce the noise impact of their vehicles. Developing quiet technologies will give the UK drone industry, which has over 700 entities, an edge in a highly competitive market both domestic & overseas. I will also write a policy brief to inform regulations for operating drones with less impact on people's health and wellbeing. Regulations for quiet drone operations would allow greater usage for the benefit of the people in the UK.

The outcomes of my project are planned to have direct impact in the small-to-medium size drone market, and set the foundations for potential future impact in drones for transport of people.

In summary, my work will address the noise issues related to the design and operation of drones, to aid drone stakeholders to ensure community acceptance, and contribute to the sustainable expansion of the sector. This will contribute to maintain the UK world-leading position on drone research and development.

Publications

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Casagrande Hirono F (2023) Acoustic and psychoacoustic characterisation of small-scale contra-rotating propellers in Journal of Sound and Vibration

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Ramos-Romero C (2022) Requirements for Drone Operations to Minimise Community Noise Impact. in International journal of environmental research and public health

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Torija AJ (2022) Investigation of Metrics for Assessing Human Response to Drone Noise. in International journal of environmental research and public health

 
Description Reducing Environmental Footprint through transformative Multi-scale Aviation Planning (REFMAP) - Call: HORIZON-CL5-2022-D5-01
Amount € 5,000,000 (EUR)
Funding ID 101096698 
Organisation European Commission 
Sector Public
Country European Union (EU)
Start 02/2023 
End 01/2026
 
Title DNM_mics_line 
Description The code written in Python allows the processing of multi-channel acoustic data gathered with a microphone array for drone operations outdoors to build acoustic hemispheres for a set of acoustic metrics (LAE, Lmax, frequency bands, tonal vs. broadband noise). 
Type Of Material Computer model/algorithm 
Year Produced 2023 
Provided To Others? Yes  
Impact The code allows the processing and reporting of acoustic data according to the main existing guidance on drone noise measurements (published by EASA and NASA). 
URL https://github.com/cramosromero/DNM_mics_line.git
 
Title DroneNoise Database 
Description Ramos Romero, Carlos; Torija Martinez, Antonio Jose; Green, Nathan; Asensio, César (2023): DroneNoise Database. University of Salford. Dataset. https://doi.org/10.17866/rd.salford.22133411.v1 The database was constructed from sUAS noise recorded under field conditions during the measurement campaign in Edzell, Scotland, on 17 August 2022. The first part of the data includes only results from overflight operations. 
Type Of Material Database/Collection of data 
Year Produced 2023 
Provided To Others? Yes  
Impact This dataset includes audio recordings and acoustic metrics for a series of drone operations. This data can be used by researchers for developing models for drone noise, and also to conduct psychoacoustic research. 
URL https://salford.figshare.com/articles/dataset/DroneNoise_Database/22133411/1
 
Title pywopwop 
Description This package aims to provide an easier interface to interact with PSU-WOPWOP input files, mainly geometry patch files and functional loading files. A Python framework is provided to facilitate reading existing files, interacting and inspecting the data using a Python console, and creating PSU-WOPWOP input files from Python data. PSU-WOPWOP is a research code for acoustic prediction of rotor noise developed by Penn State University. 
Type Of Material Computer model/algorithm 
Year Produced 2022 
Provided To Others? Yes  
Impact This code allows the interface between Computational Fluid Dynamics data (acoustic pressure and geometry) and the acoustics prediction code PSU-WOPWOP. This code can be used by researchers working on the acoustic prediction of rotary systems. 
URL https://github.com/fchirono/pywopwop.git
 
Description Collaboration with NASA on Advanced Air Mobility noise 
Organisation National Aeronautics and Space Administration (NASA)
Department NASA Langley Research Centre
Country United States 
Sector Public 
PI Contribution In July 2022, I visited NASA Langley as part of my New Investigator Award. During this visit, I presented my research on drone noise, I was trained in aircraft noise auralisation and psychoacoustic methods, and also increase my network of potential collaborators.
Collaborator Contribution Training in the use of the NASA Auralization Framework and psychoacoustic method for assessing aircraft noise. First step in the potential formalisation for an international collaboration agreement between NASA and the University of Salford in the framework of Advanced Air Mobility noise.
Impact -Licence of the NASA Auralization Framework granted to the University of Salford. -Membership of the NASA Urban Air Mobility Noise (UAM) Working Group. -Invited talk for the NASA UAM Noise Working Group. -Ongoing discussion for the formalisation of an international collaboration agreement between NASA and the University of Salford in the framework of Advanced Air Mobility noise.
Start Year 2022
 
Description Drone Noise Research for Policy Making 
Organisation Department of Transport
Department Civil Aviation Authority (CAA)
Country United Kingdom 
Sector Public 
PI Contribution As part of this collaboration, we have fortnightly meetings with colleagues of CAA. The purpose of these meetings is twofold: 1. Collaborate with CAA in the development of a framework to inform policy development in drone noise. 2. Present the research outcomes of the EPSRC DroneNoise project to the colleagues of CAA and DfT, for them to critically appraise and guide to maximise impact.
Collaborator Contribution -Support and guidance in the design of a psychoacoustic experiment for the development of dose-response relationships for drone noise. -Collaboration in the planning of an measurement campaign of drone noise to produce a comprehensive database to aid research and policy development -Workshop with CAA and DfT colleagues to discuss the outcomes of this activity and contribute to defining a roadmap for policy making on drone noise in the UK.
Impact Funding for drone noise research to inform policy making provided by the University of Salford (UKRI Policy Support Fund 2022/23). Please contact Janet Morana (j.morana@salford.ac.uk)
Start Year 2022