Indoor and outdoor environmental data: A dataset with acoustic data acquired by the microphone embedded on mobile devices
Journal
Data in Brief
Date Issued
2021-06-01
Author(s)
Pires, Ivan Miguel
Garcia, Nuno M
Abstract
All mobile devices include a microphone that can be used
for acoustic data acquisition. This article presents a dataset of
acoustic signals related to nine environments, captured with
a microphone embedded on off-the-shelf mobile devices. The
mobile phone can be placed in the pants pockets, in a wristband, over the bedside table, on a table, or on other furniture. Data collection environments are bar, classroom, gym,
kitchen, library, street, hall, living room, and bedroom. The
data was collected by 25 individuals (15 men and 10 women)
in different environments around Covilhã and Fundão municipalities (Portugal). The microphone data was sampled with
44,100 Hz into an array with 16-bit unsigned integer values
in the range [0, 255] with a 128 offset for zero. The dataset
presented in this paper presents at least 2000 samples of 5 s
of data for each environment, corresponding to around 2.8 h
for each environment into text files. In total, it includes at
least 25.2 h of acoustic data for the implementation of data processing techniques, e.g., Fast Fourier Transform (FFT), and other machine learning methods for the different analysis.
for acoustic data acquisition. This article presents a dataset of
acoustic signals related to nine environments, captured with
a microphone embedded on off-the-shelf mobile devices. The
mobile phone can be placed in the pants pockets, in a wristband, over the bedside table, on a table, or on other furniture. Data collection environments are bar, classroom, gym,
kitchen, library, street, hall, living room, and bedroom. The
data was collected by 25 individuals (15 men and 10 women)
in different environments around Covilhã and Fundão municipalities (Portugal). The microphone data was sampled with
44,100 Hz into an array with 16-bit unsigned integer values
in the range [0, 255] with a 128 offset for zero. The dataset
presented in this paper presents at least 2000 samples of 5 s
of data for each environment, corresponding to around 2.8 h
for each environment into text files. In total, it includes at
least 25.2 h of acoustic data for the implementation of data processing techniques, e.g., Fast Fourier Transform (FFT), and other machine learning methods for the different analysis.
Subjects
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