2022
DOI: 10.3390/s22197100
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A Low-Cost Multi-Purpose IoT Sensor for Biologging and Soundscape Activities

Abstract: The rapid expansion in miniaturization, usability, energy efficiency, and affordability of Internet of Things (IoT) sensors, integrated with innovations in smart capability, is greatly increasing opportunities in ground-level monitoring of ecosystems at a specific scale using sensor grids. Surrounding sound is a powerful data source for investigating urban and non-urban ecosystem health, and researchers commonly use robust but expensive passive sensors as monitoring equipment to capture it. This paper comprehe… Show more

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Cited by 6 publications
(1 citation statement)
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“…On the other hand, Passive Acoustic Monitoring (PAM), which encompasses real-time analysis of data collected by acoustic IoT (Internet of Things) sensors, is becoming an increasingly important tool of ecological research [39] used in various types of surveys, from autonomous bird species recording [40] to urban traffic noise monitoring [41]. Due to the low cost, ease of installation, efficiency, and energy independence of these acoustic devices, it is possible to facilitate real-time and large-scale monitoring [42], acquiring important information on population diversity and dynamics, over a finer daily scale or more extended periods to complement traditional methods. Data processing includes identification algorithms to detect the presence of species within an environment, recognising distinct sounds and inferring species diversity.…”
Section: Introductionmentioning
confidence: 99%
“…On the other hand, Passive Acoustic Monitoring (PAM), which encompasses real-time analysis of data collected by acoustic IoT (Internet of Things) sensors, is becoming an increasingly important tool of ecological research [39] used in various types of surveys, from autonomous bird species recording [40] to urban traffic noise monitoring [41]. Due to the low cost, ease of installation, efficiency, and energy independence of these acoustic devices, it is possible to facilitate real-time and large-scale monitoring [42], acquiring important information on population diversity and dynamics, over a finer daily scale or more extended periods to complement traditional methods. Data processing includes identification algorithms to detect the presence of species within an environment, recognising distinct sounds and inferring species diversity.…”
Section: Introductionmentioning
confidence: 99%