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Accurate Ambient Noise Assessment Using Smartphones

Department of Computing Engineering, Universitat Politècnica de València, 46022 València, Spain
School of Computer Science, Universidad Laica Eloy Alfaro de Manabí, 130802 Manta, Ecuador
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editor: Yuh-Shyan Chen
Sensors 2017, 17(4), 917;
Received: 27 February 2017 / Revised: 30 March 2017 / Accepted: 18 April 2017 / Published: 21 April 2017
Nowadays, smartphones have become ubiquitous and one of the main communication resources for human beings. Their widespread adoption was due to the huge technological progress and to the development of multiple useful applications. Their characteristics have also experienced a substantial improvement as they now integrate multiple sensors able to convert the smartphone into a flexible and multi-purpose sensing unit. The combined use of multiple smartphones endowed with several types of sensors gives the possibility to monitor a certain area with fine spatial and temporal granularity, a procedure typically known as crowdsensing. In this paper, we propose using smartphones as environmental noise-sensing units. For this purpose, we focus our study on the sound capture and processing procedure, analyzing the impact of different noise calculation algorithms, as well as in determining their accuracy when compared to a professional noise measurement unit. We analyze different candidate algorithms using different types of smartphones, and we study the most adequate time period and sampling strategy to optimize the data-gathering process. In addition, we perform an experimental study comparing our approach with the results obtained using a professional device. Experimental results show that, if the smartphone application is well tuned, it is possible to measure noise levels with a accuracy degree comparable to professional devices for the entire dynamic range typically supported by microphones embedded in smartphones, i.e., 35–95 dB. View Full-Text
Keywords: crowdsensing; smartphone; noise sensing; dynamic range crowdsensing; smartphone; noise sensing; dynamic range
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MDPI and ACS Style

Zamora, W.; Calafate, C.T.; Cano, J.-C.; Manzoni, P. Accurate Ambient Noise Assessment Using Smartphones. Sensors 2017, 17, 917.

AMA Style

Zamora W, Calafate CT, Cano J-C, Manzoni P. Accurate Ambient Noise Assessment Using Smartphones. Sensors. 2017; 17(4):917.

Chicago/Turabian Style

Zamora, Willian, Carlos T. Calafate, Juan-Carlos Cano, and Pietro Manzoni. 2017. "Accurate Ambient Noise Assessment Using Smartphones" Sensors 17, no. 4: 917.

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