Participatory noise mapping works! An evaluation of participatory sensing as an alternative to standard techniques for environmental monitoring

D’Hondt, Ellie; Stevens, Matthias; Jacobs, An

doi:10.1016/j.pmcj.2012.09.002

Cited by 205 publications

(141 citation statements)

References 7 publications

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“…Some studies have tried to formulate a better traffic model by using dynamic noise mapping techniques [4,5] or even data extracted from participatory noise mapping techniques [6,7]. Moreover, the need to combine a holistic approach in environmental noise policy -by combining the noise mapping with the soundscape approach -has recently been raised by the European Environmental Agency (EEA) in the Good Practice Guide on Quiet Areas [8].…”

Section: Introductionmentioning

confidence: 99%

Soundscape mapping in environmental noise management and urban planning: case studies in two UK cities

Margaritis

Kang

2017

Noise Mapping

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Section: Introductionmentioning

confidence: 99%

Soundscape mapping in environmental noise management and urban planning: case studies in two UK cities

Margaritis

Kang

2017

Noise Mapping

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“…Recently, mobiles phones emerged as a potential solution for the participatory noise monitoring; this approach was proposed by D'Hondt et al in [14] and Kanjo in [15]. However, processing capabilities and power consumption of smartphones far exceed that of sensor nodes, which does not make them a viable solution for long-term noise pollution monitoring.…”

Section: Related Workmentioning

confidence: 99%

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

Risojević¹,

Rozman²,

Pilipović³

et al. 2018

Preprint

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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 a number of 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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“…Furthermore, focus in existing solutions e.g., (Rana et al, 2010;D'Hondt et al, 2013;Bennett et al, 2010) is mostly on noise measurement itself, especially in terms of sensor calibration or measurement/maps accuracy and quality while work remains to be done in order to properly represent the results to users so as to increase their awareness of their surrounding environment pollution, which can be a major harming factor to their well-being.…”

Section: Noise Monitoringmentioning

confidence: 99%

Sense2Health - A Quantified Self Application for Monitoring Personal Exposure to Environmental Pollution

Hachem

Mathioudakis

Pathak

et al. 2015

Proceedings of the 4th International Conference on Sensor Networks

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Abstract:Sense2Health is a Quantified Self application that monitors personal exposure to environment pollution and assesses its heath-related risks. The novelty of the application is that it requires little to no active involvement by users and unlike existing applications, it correlates the individual's well-being to their environment as opposed to their physical activity alone. Consequently, when health and environment data are acquired, our application enables users to better identify behavior changes towards enhancing their health by enhancing their environments. Furthermore, Sense2Health is an open platform for integrating existing domain-specific sensing applications (environmental and health monitoring) focused on decreasing required specialized development efforts. We present in this paper the design of Sense2Health in addition to a proof-of-concept implementation for a noise-monitoring use case. Afterwards, we assess its performance while integrating it with a dedicated open source noise sensing application.

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Participatory noise mapping works! An evaluation of participatory sensing as an alternative to standard techniques for environmental monitoring

Cited by 205 publications

References 7 publications

Soundscape mapping in environmental noise management and urban planning: case studies in two UK cities

Soundscape mapping in environmental noise management and urban planning: case studies in two UK cities

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

Sense2Health - A Quantified Self Application for Monitoring Personal Exposure to Environmental Pollution

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