The general objective of the BEEP (BIG DATA FOR ENVIRONMENTAL AND OCCUPATIONAL EPIDEMIOLOGY) project is to estimate, using Big Data, the health effects of air pollution and noise on the Italian general population, and to evaluate the risk of occupational injuries in sub-populations of workers. Noise estimates are usually provided by noise maps based on traffic flows that are defined upon road categories. In this paper, challenges of using social networks and mobile phone's data to produce more accurate noise mapping will be evaluated. Data from phones users will be used to improve existing noise maps for Rome and Pisa cities, using them as proxy for traffic flows, improving health outcomes relationships already found within Noise & Health project. In fact, even if traffic models are provided for rush hour, no proofs of daily variations are available. The use of such big data could improve traffic estimates, in particular in the night period, which are needed to evaluate the most common effects on health. Moreover, some issues related to the association of noise levels to exposed population will be discussed: the different estimates along back façades will be discussed according to the method of association.

The use of big data for improving noise mapping in epidemiological studies

Licitra G;Ascari E
2018

Abstract

The general objective of the BEEP (BIG DATA FOR ENVIRONMENTAL AND OCCUPATIONAL EPIDEMIOLOGY) project is to estimate, using Big Data, the health effects of air pollution and noise on the Italian general population, and to evaluate the risk of occupational injuries in sub-populations of workers. Noise estimates are usually provided by noise maps based on traffic flows that are defined upon road categories. In this paper, challenges of using social networks and mobile phone's data to produce more accurate noise mapping will be evaluated. Data from phones users will be used to improve existing noise maps for Rome and Pisa cities, using them as proxy for traffic flows, improving health outcomes relationships already found within Noise & Health project. In fact, even if traffic models are provided for rush hour, no proofs of daily variations are available. The use of such big data could improve traffic estimates, in particular in the night period, which are needed to evaluate the most common effects on health. Moreover, some issues related to the association of noise levels to exposed population will be discussed: the different estimates along back façades will be discussed according to the method of association.
2018
Istituto per i Processi Chimico-Fisici - IPCF - Sede Secondaria Pisa
analysis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/383858
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