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Accurate position tracking is fundamental to the safe and effective operation of unmanned aerial vehicles (UAVs), particularly during precision maneuvers near complex structures. In this scenario, a drone is programmed to perform a high-precision inspection of a vertical structure, starting at position ((x, y, z) = (3, 0, 0)), with an initial velocity oriented in the positive z-direction. The trajectory of the drone is governed by a time-dependent acceleration function a(t), which is predefined...

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The Measurement of Unsteady Surface Pressure Using a Remote Microphone Probe

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Urban Traffic Noise Analysis Using UAV-Based Array of Microphones.

Marius Minea¹, Cătălin Marian Dumitrescu¹

¹Department Telematics and Electronics for Transports, University Politehnica of Bucharest, 060042 Bucharest, Romania.

Sensors (Basel, Switzerland)

|February 28, 2023

Summary

This study introduces a low-cost, Unmanned Aerial Vehicle (UAV)-based system for mapping 3D urban noise pollution. The innovative approach effectively monitors traffic noise, aiding smart city environmental improvements.

Keywords:

UAV data collection intelligent measurement of traffic noise noise pollution sound pressure level

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Area of Science:

Environmental Science
Urban Planning
Acoustics

Background:

Smart city development requires attention to environmental factors and urban mobility.
Traffic noise is a significant environmental concern in urban areas, impacting quality of life.
Effective noise monitoring is crucial for sustainable urban development and infrastructure planning.

Purpose of the Study:

To propose and evaluate a simple, low-cost Unmanned Aerial Vehicle (UAV)-based solution for monitoring and mapping 3D traffic-generated urban noise emissions.
To demonstrate the feasibility of using UAVs for detailed environmental noise mapping in urban settings.
To provide a method for rapid data collection and analysis of urban noise pollution.

Main Methods:

Utilizing a UAV equipped with a specialized microphone array for sound recording.
Implementing post-processing techniques to filter out UAV rotor noise and vibrations.
Attaching location and altitude data to collected noise measurements to create a 3D noise profile.

Main Results:

Demonstrated successful field measurements of sound levels at various directions and altitudes.
Presented data illustrating the spatial distribution of traffic noise.
Validated the UAV system's capability to capture detailed noise information.

Conclusions:

Employing UAVs for environmental noise mapping is a minimally invasive and cost-effective solution.
The proposed method enables the rapid generation of environmental noise pollution maps.
This technology supports informed decision-making for urban planning and road infrastructure improvements.