Evidence map›Paper›PMID 28036065›Full record

ArticleSensors (Basel, Switzerland)2016

Design of a Mobile Low-Cost Sensor Network Using Urban Buses for Real-Time Ubiquitous Noise Monitoring.

Rosa Ma Alsina-Pagès, Unai Hernandez-Jayo, Francesc Alías, Ignacio Angulo

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Cluster Analysis of Urban Acoustic Environments on Barcelona Sensor Network Data.International journal of environmental research and public health · 2021
    Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. On the Coverage of Bus-Based Mobile Sensing.Sensors (Basel, Switzerland) · 2018
    Article
  11. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Rosa Ma Alsina-PagèsGTM-Grup de recerca en Tecnologies Mèdia, Quatre Camins, 30, Barcelona 08022, Spain. ralsina@salleurl.edu.
Unai Hernandez-JayoDeustoTech-Fundación Deusto, Avda. Universidades, 24, Bilbao 48007, Spain. unai.hernandez@deusto.es.
Francesc AlíasGTM-Grup de recerca en Tecnologies Mèdia, Quatre Camins, 30, Barcelona 08022, Spain. falias@salleurl.edu.
Ignacio AnguloDeustoTech-Fundación Deusto, Avda. Universidades, 24, Bilbao 48007, Spain. ignacio.angulo@deusto.es.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

One of the main priorities of smart cities is improving the quality of life of their inhabitants. Traffic noise is one of the pollutant sources that causes a negative impact on the quality of life of citizens, which is gaining attention among authorities. The European Commission has promoted the Environmental Noise Directive 2002/49/EC (END) to inform citizens and to prevent the harmful effects of noise exposure. The measure of acoustic levels using noise maps is a strategic issue in the END action plan. Noise maps are typically calculated by computing the average noise during one year and updated every five years. Hence, the implementation of dynamic noise mapping systems could lead to short-term plan actions, besides helping to better understand the evolution of noise levels along time. Recently, some projects have started the monitoring of noise levels in urban areas by means of acoustic sensor networks settled in strategic locations across the city, while others have taken advantage of collaborative citizen sensing mobile applications. In this paper, we describe the design of an acoustic low-cost sensor network installed on public buses to measure the traffic noise in the city in real time. Moreover, the challenges that a ubiquitous bus acoustic measurement system entails are enumerated and discussed. Specifically, the analysis takes into account the feature extraction of the audio signal, the identification and separation of the road traffic noise from urban traffic noise, the hardware platform to measure and process the acoustic signal, the connectivity between the several nodes of the acoustic sensor network to store the data and, finally, the noise maps' generation process. The implementation and evaluation of the proposal in a real-life scenario is left for future work.

Indexed as

acoustic sensingconnectivitydynamic measurementENDhardware platformnoise mappingsignal processingsmart cityubiquitous

Identifiers

PMID28036065
PMCPMC5298630

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.