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Open AccessArticle

Accurate Indoor Sound Level Measurement on a Low-Power and Low-Cost Wireless Sensor Node

1
Faculty of Electrical Engineering, University of Banja Luka, 78000 Banja Luka, Bosnia and Herzegovina
2
Faculty of Computer and Information Science, University of Ljubljana, 1000 Ljubljana, Slovenia
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Sensors 2018, 18(7), 2351; https://doi.org/10.3390/s18072351
Received: 20 June 2018 / Revised: 11 July 2018 / Accepted: 16 July 2018 / Published: 19 July 2018
(This article belongs to the Section Sensor Networks)
Wireless sensor networks can provide a cheap and flexible infrastructure to support the measurement of noise pollution. However, the processing of the gathered data is challenging to implement on resource-constrained nodes, because each node has its own limited power supply, low-performance and low-power micro-controller unit and other limited processing resources, as well as limited amount of memory. We propose a sensor node for monitoring of indoor ambient noise. The sensor node is based on a hardware platform with limited computational resources and utilizes several simplifications to approximate more complex and costly signal processing stage. Furthermore, to reduce the communication between the sensor node and a sink node, as well as the power consumed by the IEEE 802.15.4 (ZigBee) transceiver, we perform digital A-weighting filtering and non-calibrated calculation of the sound pressure level on the node. According to experimental results, the proposed sound level meter can accurately measure the noise levels of up to 100 dB, with the mean difference of less than 2 dB compared to Class 1 sound level meter. The proposed device can continuously monitor indoor noise for several days. Despite the limitations of the used hardware platform, the presented node is a promising low-cost and low-power solution for indoor ambient noise monitoring. View Full-Text
Keywords: environmental noise monitoring; noise sensing; A-weighting; hardware platform; wireless sensor network environmental noise monitoring; noise sensing; A-weighting; hardware platform; wireless sensor network
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MDPI and ACS Style

Risojević, V.; Rozman, R.; Pilipović, R.; Češnovar, R.; Bulić, P. Accurate Indoor Sound Level Measurement on a Low-Power and Low-Cost Wireless Sensor Node. Sensors 2018, 18, 2351.

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