Accurate indoor sound level measurement on a low-power and low-cost wireless sensor node
V Risojević, R Rozman, R Pilipović, R Češnovar… - Sensors, 2018 - mdpi.com
V Risojević, R Rozman, R Pilipović, R Češnovar, P Bulić
Sensors, 2018•mdpi.comWireless 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 …
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 …
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.
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